Final report for the agriculture sector study

SUSTAINABILITY IMPACT ASSESSMENT OF PROPOSED WTO NEGOTIATIONS

FINAL REPORT FOR THE

AGRICULTURE SECTOR STUDY

Prepared by

Oliver Morrissey, Dirk Willem te Velde, Ian Gillson and Steve Wiggins

Overseas Development Institute, London, UK

In association with:

Annie Dufey and Maryanne GriegGran International Institute for Environment and Development (IIED), London

Impact Assessment Research Centre Institute for Development Policy and Management

University of Manchester, UK

20 September 2005 (final revision)

Personal data in this document have been redacted according to the General Data Protection Regulation 2016/679 and the European Commission Internal Data Protection

Regulation 2018/1725

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This report was prepared with financial assistance from the Commission of the European Communities. The views expressed herein are those of the Contractor, and do not represent any

official view of the Commission.

This Report has been prepared for the European Commission under Framework Contract No Trade 01/F31 (Sustainability Impact Assessment of Proposed WTO Negotiations)

Specific Agreement No. 3.

Project Reports and information about the project are available from the project website:

http://www.siatrade.org

http://www.sia-trade.org/

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Table of Contents

EXECUTIVE SUMMARY ................................................................................................................ 1

LIST OF ABBREVIATIONS............................................................................................................. 8

1. INTRODUCTION....................................................................................................................... 9

2. SIA METHODOLOGY APPLIED TO AGRICULTURE ......................................................... 11 3. CONTEXT: TRADE LIBERALISATION IN AGRICULTURE................................................ 21

4. SIA FOR COUNTRY TYPES................................................................................................... 25

4.1. SIA – Major Exporting Developing Countries...................................................................... 31

Example: Brazil Case Study ........................................................................................................ 36

4.2. SIA – Highly Protected Developing Countries ..................................................................... 37

Example: India Case Study.......................................................................................................... 41

4.3. SIA – Least Developed Countries ........................................................................................ 42

Example: Tanzania Case Study.................................................................................................... 47

4.4. SIA – Lowincome Developing Countries............................................................................ 48

Example: Ghana Case Study........................................................................................................ 52

4.5. SIA – European Union......................................................................................................... 53

4.6. SIA – Other Developed Countries........................................................................................ 59

5. EXTENSIONS AND POLICY IMPLICATIONS ...................................................................... 63

5.1 Extensions and Elaborations .............................................................................................. 63

5.2 Product Standards and Agricultural Trade.......................................................................... 67

5.3 Interlinkages with Forest and Distribution Services SIAs ................................................... 72

6. MITIGATION AND ENHANCEMENT MEASURES .............................................................. 74

REFERENCES................................................................................................................................. 79

APPENDIX 1: COUNTRY CASE STUDIES.................................................................................. 85

Ghana Case Study ....................................................................................................................... 85 A Case Study of Indian Agricultural Sector ............................................................................... 103 Tanzania Case Study ................................................................................................................. 125 Agriculture, The Case of Brazil ................................................................................................. 152

SIA of WTO Negotiations – Agriculture Sector Final Report 1

Executive Summary

This Report presents the results of a sustainability impact assessment of the economic, social and environmental impacts of liberalisation of trade in agriculture. The coverage of the study is very broad, in that it aims to assess the significant impacts for all countries and all agricultural products. Consequently, the scope of the assessment is restricted to identifying impacts that are likely to occur, likely to be significant and are due to the liberalisation of trade in agriculture. In reading the Report, these should be interpreted as ‘directly attributable impacts’ (as distinct from feedback and longer run effects as economies adjust to these impacts having implemented flanking measures). Specifically, the impacts must be attributable to the trade liberalisation being considered, defined as the partial liberalisation proposals that are most likely to result from the current WTO negotiations on agriculture. The impacts are assessed at the level of six broad country types, defined below, and attention is confined to impacts that are likely to be observable at an aggregate (country) level. Furthermore, we aim to identify impacts of sufficient significance to contribute to (if positive) or undermine (if negative) sustainable development.

It is important to emphasise that our aim is to try and isolate the impacts of the trade liberalisation scenario. Other factors, such as technological change and growth in global demand, are likely to be more important drivers of trends in agricultural production than trade liberalisation (especially where reforms are partial and gradually implemented). Although the effects attributable to trade liberalisation may be marginal, they may nevertheless be significant. The assessment is essentially qualitative, to identify situations, countries and producers for which significant effects are probable. While quantitative information is used where available, the philosophy of the approach is that it is better to be approximately correct than precisely wrong.

Section 2 discusses how the SIA methodology is applied in this study, defines the partial liberalisation scenario employed and describes the country types for which the SIA is conducted. The scenario distinguishes the three ‘pillars’ of tariff reductions (market access), export support, and domestic support measures. Developed countries are required to implement the greatest degree of liberalisation; tariffs are reduced by 36%, export support is eliminated and tradedistorting domestic support is reduced by more than half. Developing countries implement less liberalisation; tariffs are reduced by 24%, export support is reduced by half and domestic support by 40%. The least developed countries are not required to make any commitments to liberalise. As few developing and no least developed countries have export or domestic support, tariffs are the major domestic reforms they will make. To the extent that we make any quantitative (as distinct from qualitative) assessments, these are largely based on tariff reductions. The assessment covers six country types: the EU, other developed, least developed, exporting, highly protected and lowincome developing countries.

Section 3 presents results from economic modelling studies that inform the initial assessment of the likely economic impacts. As OECD countries reduce levels of domestic and export support, prices received by OECD producers will be reduced, but world prices may increase (for the commodities affected, mostly temperate products. Studies that model the type of partial liberalisation scenario we consider suggest that world prices of some commodities could rise by up to five per cent on average, in particular wheat and other cereals, ruminants (live cattle and sheep, and beef and mutton or lamb), and oilseeds. These estimates of effects on world prices are used as the basis for our assessment of the first stage economic effects, to identify the direction and order of magnitude of effects on the prices of goods a country (type) exports and the border price of imports. The effect of tariff reductions is then taken into account to identify the combined effect of the scenario on prices and production incentives. Then, the causal chain analysis is used to identify economic, social and environmental impacts.


Section 4 presents the results of the SIA for the six country types. Significant impacts are likely to exist but will be specific to initial conditions in the country/regions producing, exporting or importing affected products. Some initial conditions are especially important: the responsiveness of producers is a primary determinant of economic impacts; the incidence of poverty and smallholder farming are major determinants of social impacts; and existing environmental stress and degradation are major determinants of environmental impacts. The study assesses the most likely broad impacts for each country type, and is necessarily both inherently qualitative (even if informed by quantitative assessments) and quite general (but illustrated with examples and country case studies).

A number of overall conclusions emerge.

Ø The overall economic impact is very likely to be positive and significant. Insofar as multilateral liberalisation reduces distortions it will facilitate an expansion of global trade and production, and will encourage increased efficiency in the allocation of resources to agriculture, globally and within individual countries. Thus, the overall gains will include increased volumes and efficiency of production, implying higher incomes, and lower consumer prices in general. The more vibrant and efficient agricultural sector contributes to sustainable economic development, globally and especially in developing countries suited to agriculture. Countries that initially have high levels of distortions (protection), including developed countries, will derive significant gains: losses to some producers will be more than offset by consumer gains and increased efficiency. Countries that are globally competitive will gain from increased market access allowing an expansion of exports. Poor developing countries are unlikely to derive any significant direct benefit; they will benefit only insofar as domestic production can be increased in response to improved incentives. The countries that will derive the least benefit, and may even incur losses, are those in which domestic agriculture has the least capacity to expand. These will be mostly poor developing countries and small island states.

Ø The overall social impact is also likely to be positive. Increased incomes in agriculture are likely to benefit the poor in developing countries (either directly as producers or indirectly through increased demand for labour and services), and lower food prices benefit poor consumers, even if the poor do not get the largest share of the gains. In all developing countries, agriculture is relatively important for the livelihoods of the poor and efficient growth in the sector contributes to the sustainability of social development. There is potential to reduce poverty and inequality, especially ruralurban inequality. In poor developing countries, however, this benefit is not automatic – the agriculture sector must be enabled to respond. Although there will be producer losses in developed countries, there are large consumer gains whilst agriculture is a relatively low share of the economy and these countries have the resources to accommodate the adjustment.

Ø The overall environmental impact is likely to be negative, increasing stress on natural resources and posing challenges for sustainable environmental development. Globally, a net increase in production is predicted and this implies that more land will be brought into use for agriculture and/or there will be increased intensity of use of agrochemicals. Increasing the land used will encourage deforestation or using land of lower quality (with associated risks of increased soil degradation). The adverse impacts will to some extent be offset by technological and resource management improvements that increase the environmental efficiency of agriculture, and by global shifts from less to more efficient producers. However, the net increase in volumes traded implies increased transport, suggesting a net increase in the emission of


pollutants that will only partly be offset by increases in efficiency. An important issue here is whether the increased volumes are shipped by air or by sea.

Within these overall impacts, there will be variations across countries, which can be summarised as follows:

• Major Exporting Developing Countries (MEDCs). This category comprises middle income developing countries that are significant net exporters of agricultural products. These countries, such as Argentina, Brazil and Uruguay, are unambiguous economic beneficiaries from liberalisation, although the welfare gain is unlikely to exceed one per cent of national income. The social impacts may be small but are also likely to be positive – increased agricultural production and exports offers opportunities to increase employment and reduce prices, both of which can benefit the poor. Environmental impacts will depend on the product in question but one expects they would be adverse, e.g. increased production may lead to forest conversion or more intensive use of chemicals. The category also includes some middle income countries that are significant exporters of a specific product, notably Mauritius in the case of sugar. In these cases the impact may not be beneficial.

• Highly Protected Developing Countries (HPDCs). This category comprises large middle and low income countries with a relatively protected agricultural sector, such as Egypt and India. These countries export some products (and such producers may gain) but import others (producers lose but consumers gain), so they face mixed impacts. The net economic impact is likely to be positive, as gains to consumers and exporters offset losses to some importcompeting producers. Social impacts are mixed but also likely to be positive. Smallscale farmers have demonstrated that they can respond to better incentives if complementary measures are implemented to enable them to do so, and increased rural employment tends to benefit the poor. Lower food prices for consumers can be a significant benefit for the poor. Environmental impacts will depend on whether liberalisation leads to a net increase in the use of agro chemicals.

• Least Developed Countries (LDCs) typically export cash crops to developed countries under preferential access (most have tarifffree access to the EU for example). Most of the products they export are largely unaffected by the liberalisation scenario, the major exceptions being sugar (but few LDCs export significant amounts) and cotton. As exporters, LDCs gain little in general from the liberalisation scenario. While global tariff reductions imply a reduction in their margins of preferences, the erosion of preferences is unlikely to have a significant effect on unprocessed exports for most LDCs, as globally tariffs tend to be low on the cash crops they produce. As many LDCs are net food importers, they suffer a welfare loss from higher world prices. This is an adjustment cost for consumers: if (and only if) domestic producers can respond to higher import prices, domestic production will expand and domestic prices may ultimately fall, implying a longrun gain to the economy. To the extent that the domestic sector expands, the social impact will be positive, favouring in particular the rural poor. As food production in LDCs tends to make low use of agrochemicals, adverse environmental impacts will be minimal and possibly offset by savings on transport as domestic products displace imports.

• Lowincome developing countries (LIDCs) are required to reduce domestic tariffs, unlike LDCs. This allows them to in effect offset the domestic impact of increased world prices for food imports, which is a benefit to consumers. This may mean that there is no price incentive for domestic producers, or at least dampens the incentive. However, liberalisation should eliminate dumping of subsidised food. If food imports are being dumped, this means that they are being sold at below the world price (hence below the price even competitive local producers would need to sell at), so the elimination of dumping implies domestic producers will only have to compete with


imports at the world price (higher than the dumped price). Thus, domestic producers should benefit (this argument also applies to LDCs). A second potential benefit is that the margin of preference available to LDCs with respect to LIDCs will be reduced, implying a marginal benefit in those products where LIDCs compete with LDCs. This may only be a significant impact for a few products, such as fruit and vegetables. The probable economic benefits are positive and as the structure and forms of production in agriculture in LIDCs is similar to that in LDCs, the social impact should be positive (benefiting the poor), if producers can respond, while the environmental impact is likely to be insignificant. It should however be noted that the loss of tax revenues could have adverse social impacts through a reduction in government expenditure, if the income is not made up from other sources.

• The European Union is expected to gain economically from agricultural liberalisation as the benefits to consumers and efficiency gains offset producer losses, but the net (welfare) gain is in the order of only 0.1% of GDP. Agriculture exports in some products will increase, notably relatively processed commodities (as inputs are cheaper), but imports will increase for those products that initially had high protection. There are large differences across and within EU countries: all gain from tariff liberalisation and most from reduction in support. Countries such as France are expected to lose some production of cereals. The cattle and beef sector in the EU declines. Processed food production will increase in some countries (e.g. Netherlands). Rural employment represents a small share of employment in most EU countries so social impacts will be small but concentrated and the EU has the resources and institutional capacity to ‘compensate losers’. Decreases in farm production will affect rural incomes, although the largest commercial farms with high average incomes and agribusinesses are expected to be the main losers of subsidies. No large overall environmental effects are expected, especially insofar as trade distorting domestic support is replaced by support to protect rural communities and land amenities. On the whole, environmental pressure is expected to decrease as long as trade liberalisation is likely to reduce overall production.

• Other developed countries (ODCs) gain from agricultural liberalisation. In the US for example, welfare gains would be similar in relative magnitude to the EU. Whilst aggregate production will remain largely stable under the combined liberalisation scenario, there are variations across US regions and products. Corn production is predicted to increase in all regions, soybean production is likely to fall in all regions, changes in wheat production are small and vary from declines to increases; while dairy production falls in general, there will be increases in production in some areas. Beef production would increase in some regions and decrease in others. Poultry would increase marginally in most regions. Overall changes are mostly small, certainly compared to normal year on year variations. Because the effects of trade liberalisation on trade and production are small, the overall environmental effects may also be small, although they mask increases in agricultural production and potential negative environmental impacts in some regions and decreases in other regions. In countries such as Australia and New Zealand with very low protection the economic gains from increased exports would be considerable, but increased production could increase environmental stress (especially in waterscarce regions).

• Not all agriculture exporting developing countries will gain from liberalisation. Some countries will lose because they are dependent on exports of a specific commodity the price of which falls, or for which their preference margin and market share falls (e.g. Mauritius for sugar). Others may lose because exports do not benefit and limited domestic production capacity means they are dependent on food imports, the prices of which rise (e.g. small islands)..


Summary Table: Key Drivers of Identified Impacts

Country Type Economic Social Environmental

MEDCs Export growth due to market access and higher prices leads to increased production.

Increases in incomes and employment in agriculture. Potential to reduce inequality and benefit poor.

More deforestation, loss of biodiversity and more intensive use of chemical inputs.

HPDCs Some export producers gain, importcompeting producers lose but consumers gain from cheaper imports (due to tariff reductions). *

Mixed impact on production, incomes and employment, but efficiency gains.

Lower food prices benefit poor.

Mixed – depends on balance of production effects.

LDCs Few direct effects on producers, no clear export benefits except for cotton exporters.

Food import prices rise (can be offset if domestic producers enabled to respond).

Tendency for higher food prices to have adverse effects on consumers and poor.

Possible employment and income losses in sugar, but gains in cotton.

Gains if domestic food production increases.

Significant impacts unlikely in general.

Increased cotton production may have adverse impact.

Lower sugar production may be a benefit.

LIDCs Few direct effects on producers, no clear export benefits except for cotton exporters.

Food import prices rise (offset by lower tariffs and if domestic producers enabled to respond).

Impact on consumers and poor depends on net effect of food prices.

Gains if domestic food production increases.

Possible employment and income losses in sugar, but gains in cotton.

Significant impacts unlikely in general.

Increased cotton production may have adverse impact.

Lower sugar production may be a benefit.

EU Producers tend to lose but consumers gain from cheaper imports (due to lower tariffs) and reductions in support. *

Lower production means income and employment losses (concentrated in certain regions), but efficiency gains.

Lower food prices benefit consumers and poor.

Net impact likely to be small but positive as production declines.

ODCs Producers tend to lose but consumers gain from cheaper imports (due to lower tariffs) and reductions in support. *

Exporting countries with low protection gain.

Lower production means income and employment losses (gains if exports increase), but efficiency gains.

Lower food prices benefit consumers and poor.

Net impact likely to be small but positive if production declines.

Adverse impact where production increases

Notes: * indicates that effects are mixed but consumer gains are likely to offset producer losses.

The principal results from the SIA for the six country types are outlined in the Summary Table, where the focus is on identifying the key factors determining the overall assessment (positive or negative) for economic, social and environmental impacts. In simple terms, exporters gain: this provides economic benefits and the increased incomes and employment represent a social benefit, but the increased production implies an environmental cost. On the


other hand, importcompeting producers in highly protected countries tend to lose out, but any economic costs are offset by efficiency gains and lower consumer prices. The implications of the results for impacts on the Millennium Development Goals are discussed in the overall project report for the SIA studies.

Section 5 considers the implications of the assessment, and discusses the mitigation and enhancement measures that could address the most important issues raised in the SIA. The first subsection comments on a number of negotiating issues that were not specifically incorporated in the scenario, such as tariff escalation, bound versus applied tariffs, food aid and export credits. The second subsection considers the issue of product standards as this is central to efforts of developing countries, especially the poorest, to expand their exports, in particular of food products to OECD markets. The third subsection outlines mitigating and enhancement (M&E) measures necessary to ensure that the potential benefits are realised and that efforts are made to offset and mitigate any adverse impacts. The final subsection considers linkages to the Forestry and Distribution Services studies.

On the basis that developed countries have the policy capacity to address and analyse issues for themselves, we concentrate on the issues of most importance to ensuring that poorer countries are enabled to benefit. In this respect, specific attention is paid to improving product standards, essential if they are to increase exports, especially of food, and the need for effective policies to reduce the constraints on domestic agriculture. As mentioned above, and reiterated throughout the Report, the direct impacts on the poorest countries (LDCs and LIDCs) are likely to be quite small. In general, the products they export are largely unaffected whereas the prices of food imports will tend to rise. In this sense the direct impact is negative. Only if domestic agriculture can respond, by increasing the volume and efficiency of production, can poor countries derive a net benefit. This beneficial supply response cannot be assumed to occur, especially as the countries in question are characterised as suffering from severely constrained agricultural supply response. Domestic producers must be enabled to respond, and this will require that wideranging investment and policy reforms (especially in agricultural factor and input markets) are implemented.

The key M&E measures can be identified for each country type: • MEDCs are net beneficiaries in economic terms but policy measures may be required

to enhance social benefits (by ensuring that landless labour and smallscale farmers share in the benefits). The essential mitigation measures will be required to protect environmental resources: deforestation should be regulated to maintain sustainable forests and more efficient environmental management methods should be promoted.

• HPDCs face mixed impacts and measures will be required to ease the adjustment of importcompeting producers (e.g. provision of subsidised inputs or credit to facilitate crop substitution). Social policies relating to employment and land reform will be important determinants of whether the poor benefit. Improved environmental management can prevent any adverse impacts.

• LDCs derive few if any direct benefits. The most important measures required, as discussed above, are promoting an efficient and competitive domestic agricultural sector, especially in food crop production. If domestic farmers are not enabled to increase production, LDCs will derive no benefits. In the short term, higher world prices for imports imply higher food prices for consumers, which would have an adverse social impact. Countries could offset this by unilaterally reducing tariffs. Some LDCS are net food importers for structural reasons (no domestic capability for food selfsufficiency) and special measures may be needed to help them meet the costs of higher food import prices (this also applies for small island states).

• LIDCs also derive few direct benefits, and the most important M&E measures are the same as for LDCs. We can also add, for both groups of countries, the need to enhance policy awareness that social and environmental issues are important and should be


addressed. Many poor developing countries have drawn up national poverty reduction strategies, which effectively recognise social issues and impacts on the poor. However, these strategies rarely address trade in any detail, and even more rarely to they include an environmental strategy.

• The EU will face the cost of adjusting to a less protected agricultural sector. The important issue here is that the costs (production and employment declines and farmers going out of business) will be concentrated in particular (rural) regions, and will be greater in some member states than in others. The key mitigation measures can be delivered through rural and regional policies, structural funds and environmental support (e.g. nontrade distorting support for farms that manage and preserve the countryside).

• ODCs fall into two groups. Those with high protection (e.g. US, Japan, Norway) are in a position similar to the EU. Those with low protection (e.g. Australia, New Zealand) will benefit and the principal issue will be mitigating any adverse impacts on the environment.

It is beyond the scope of this study to estimate the cost of such measures. However, the measures required for poor developing countries to be able to benefit fully from trade are in line with those advocated in the Report of the Commission for Africa, estimated as requiring an additional $25 billion per annum in aid to Africa to be achieved by 2010, with a further $25 billion per annum increase by 2015. Although not all of these measures are linked to trade, many poor countries outside Africa and small island states will also need resources to cover the cost of adjustment to agriculture trade liberalisation. Implementing the M&E measures for least developed and developing countries could have an annual net cost of some $25 billion, most in countries that do not have sufficient resources themselves to meet this cost (especially where tariff reductions mean lower tax revenue). It is not the task of the SIA to develop detailed costings for individual mitigation or enhancement measures. It is important to emphasise, however, that the M and E measures identified in this report are seen as an integrated programme of support: a piecemeal or partial approach to M and will not enable developing countries to benefit fully from trade in line with the attainment of the MDGs. There will also be costs in developed countries but, arguably, these are not additional as they could be funded from resources previously allocated to agriculture subsidies.

We conclude with an important caveat: the effects of the liberalisation scenario on prices and market access will be marginal relative to other determinants of agricultural production and trade. The ‘normal’ annual volatility of farmgate prices is very high relative to the predicted price effects of liberalisation, especially in developing countries. Population growth and consumer incomes have a greater impact on trends in global demand than do changes in trade policies. Technological change (e.g. high yield varieties, GMOs) is a more important driver of changes in production methods, and environmental effects, than are changes in trade policies. Changes in consumer preferences (e.g. willingness to pay a premium for organic products) are a more important determinant of demand for niche products than are changes in trade policies. Nevertheless, the trade liberalisation scenario will have significant impacts. The approach of the SIA is to try and identify the impact of the specified trade liberalisation scenario keeping these other factors constant. While the overall impact of trade liberalisation is likely to be a positive (marginal) impact, this occurs in a world of other factors, some of which exacerbate the trade liberalisation effects, whereas others weaken or swamp the trade liberalisation effects.


List of abbreviations

ACP African, Caribbean and Pacific group AgSSIP Agricultural Services SubSector Investment Programme AMS Aggregate Measure of Support CAP Common Agricultural Policy CCA Causal Chain Analysis CGE Computable General Equilibrium CUTS Consumer Unity & Trust Society DVS Department of Veterinary Services EBA Everything But Arms (EU preferences for LDCs) EFTA European Free Trade Association ERP Economic Recovery Programme EU European Union FMD Foot and Mouth Disease FIPE Foundation Institute of Economic Research (Brazil)

Fundação Instituto de Pesquisas Econômicas GDP Gross domestic product GFCF Gross Fixed Capital Formation GHG Greenhouse Gas GMO Genetically Modified Organism HPDC Highly Protected Developing Country IIED International Institute for Environment and Development IMF International Monetary Fund KEBS Kenya Bureau of Standards KEPHIS Kenya Plant Inspectorate Services LDC Least Developed Country LIDC Lowincome Developing Country M&E Mitigation and enhancement MEDC Major Exporting Developing Country MFN MostFavoured Nation MOFA Ministry of Food and Agriculture MOH Ministry of Health MOTI Ministry of Trade Industry MTADP Medium Term Agricultural Development Programme MTR Midterm Report NAFTA North American Free Trade Agreement ODCs Other Developed Countries ODI Overseas Development Institute OECD Organisation for Economic and Cooperation and Development PRSP Poverty Reduction Strategy Paper SIA Sustainability Impact Assessment SSA SubSaharan Africa TRQ Tariff Rate Quota URAA Uruguay round Agreements Act USDA United States Development Agency WTO World Trade Organisation


1. Introduction

The current proposals for multilateral liberalisation of trade in agricultural commodities under the auspices of the Doha Agenda of the WTO offer all countries, developed and developing, potential gains from trade. Economic analysis predicts that the net global impact will be positive. Although some producers in some countries, and even some producers in every country, will experience losses in production levels, market shares and/or net incomes, these will be more than offset by the global gains. These global gains are essentially of three types: i) exporters benefiting from enhanced market access, perhaps at increased prices; ii) consumer benefits from access to an increased variety of, often cheaper, goods; and iii) increased efficiency in the allocation of resources for production in agriculture (both globally as international distortions are reduced, and within countries that remove distortions). These global gains are not evenly distributed across producers and countries, nor are the adjustment costs that producers and countries will incur in responding to changes in prices and market access opportunities. More importantly, the complementary policies required to ensure that countries do benefit (measures to mitigate adverse effects and to enhance positive effects), and the costs and capacity required to implement them, will vary significantly across countries. In general, richer countries have both the resources and capacity to design and implement complementary policies, whereas poorer countries have neither the resources nor the capacity (and often require more extensive flanking measures).

Trade liberalisation will alter world prices and trade patterns, inducing changes in production patterns and incomes from farming, benefiting some producers but imposing losses for others. These changes, the economic impacts, will have social and environmental implications, both positive and negative. In general, at a global level, the social impacts should be positive, as overall incomes increase and consumers benefit. Globally, and for most countries, the numbers affected and magnitude of effects means that the gains exceed the losses. This may not be the case in poorer countries, where the incidence of poverty is high and extensive complementary policies are required to ensure net gains. The overall environmental impact is likely to be negative, as many of the regions in which increased production can be anticipated already face environmental stress. The overall increase in production and trade (transport) will increase pressure on environmental resources, although this may be partially offset by increased efficiency in environmental management.

The purpose of this study is to provide an overall assessment of the economic, social and environmental impacts of the trade liberalisation scenario proposed in the WTO negotiations on agriculture. This is a very broad remit and by necessity the study has a restricted scope. As it is an overall assessment, coverage is not comprehensive. We do not aim to cover the implications for each and every country and product that may be affected, nor do we address in detail every issue under negotiation in the WTO. Rather, we focus on the most important aspects of the negotiations (set out under our trade liberalisation scenario), identify the products that are most likely to be significantly affected and assess the impacts on a variety of types of countries. We do not claim to identify all possible impacts of the trade liberalisation scenarios, but we do try to identify any effects that are likely to have significant impacts. To conduct this assessment, our approach is informed by the realisation that the effects will differ across countries and products, i.e. gains and losses are not evenly distributed, even if globally there is a net gain. Thus, we consider types of countries.

Exporting countries (potential and actual) are expected to benefit from increased market access as globally barriers to trade are reduced. However, these benefits will not be evenly distributed across countries as some are better positioned to expand exports (both volume and market share) than others, and some countries currently benefiting from preferential access may lose as their margin of preference is reduced. From the perspective of importing countries, the effects are also likely to be mixed. To the extent that multilateral trade


liberalisation and the reduction of tariffs by individual countries imply lower prices for their imports, consumers will gain from access to a wider variety of cheaper goods. On the other hand, some elements of liberalisation will tend to increase world prices (e.g. elimination of export subsidies by developed countries) for certain commodities, at least in the shortrun, and consumers in importing countries will face higher prices. This adverse impact will be greatest for countries that are net food importers, especially if they are so for structural reasons (e.g. small island economies with limited domestic production capacity). The important issue in identifying impacts is whether the country is an exporter or importer of the affected product. The impact suggests possible responses, but these are discussed separately from the assessment of impacts as various responses are possible (see below).

The impact of multinational trade liberalisation on individual countries will depend on their ‘product profile’, whether they are importers or exporters, and on the competitiveness of domestic producers and their ability to respond to the change in incentives. Furthermore, these effects on trade and incentives to producers will affect patterns and intensity of production, within and across countries, and will therefore have economic, social and environmental impacts, both positive and negative. The purpose of the SIA is to identify the probable distribution of gains and losses associated with the variety of economic, social and environmental impacts linked to the multilateral trade liberalisation scenario.

Our concern is with impacts that can be attributed directly to the trade liberalisation itself. However, these impacts will reflect the responsiveness of the domestic producers or consumers. For producers, the ability to respond to changed incentives will often be limited by supply side constraints. The easing of these constraints therefore forms part of the discussion of mitigation and enhancement (M&E) measures rather than part of the impact assessment. For example, the effect of increased competition from imports on domestic producers depends on their ability to increase efficiency and competitiveness, suggesting domestic policy to support efficiency in agriculture. The final section of the report includes suggestions for mitigating and enhancement measures that can promote benefits, minimise losses and compensate losers from the likely impacts of trade liberalisation.

We attempted to keep this Final Report as concise and succinct as feasible, given the breadth of the issues covered, and do not repeat most of the detail that can be found in the Inception Report (June 2004) and the MidTerm Report (January 2005), both of which are available on the web. The four country case studies are available as Appendices (all except that for India are revisions of the studies included with the MidTerm Report). The Final Report is structured as follows.

Section 2 sets out how we apply the SIA method, in particular the definition of the trade liberalisation scenarios, the indicators used to assess impact significance, the choice of country types and the causal chain analysis underlying the impact assessment. The scenario distinguishes three ‘pillars’ of trade liberalisation in agriculture – tariffs and market access, export support, and domestic support measures – but the SIA considers the combined effects. We identify six representative ‘types’ of countries. The EU and ‘other developed’ are the two groups of developed countries. Four developing country ‘types’ are chosen: major exporters, countries with high levels of protection, least developed countries (LDCs) and lowincome countries that do not have LDC status. Within each developing country ‘type’ one illustrative country was selected for a case study to be undertaken by local researchers (Brazil, India, Tanzania and Ghana). The screening exercise also identified six products to receive specific attention (wheat, rice, beef, cotton, sugar and green vegetables), selected to represent broad categories of agricultural commodities and to ensure that a wide range of issues relevant to the negotiations can be addressed. An impact assessment for the six products can be found in the MidTerm Report and is not repeated here (a brief summary is provided in Section 4). More detail on the screening and scoping exercises for the study can be found in the Inception Report.


Section 3 sets the context with an overview of the importance of trade in agriculture for different types of countries and presents results from relevant economic modelling studies estimating effects of trade liberalisation. We do not undertake any modelling (just as the modelling studies do not attempt an SIA), but use the results of these studies to estimate effects on world product prices and trade patterns. A variety of modelling studies and related literature on trade liberalisation have been reviewed in the Inception Report and the Mid Term Report, to which interested readers are referred. We do not repeat the reviews here, but do report the most relevant results.

Section 4 provides the results of the impact assessment for the six country types, including a summary of the country case studies and specific issues related to specific products where relevant to elaborate the assessment. For each country type, the SIA results are summarised in tables listing the main impacts and their likely significance. The MidTerm Report presents a preliminary application of the SIA methodology to the six products and country types distinguishing the three pillars of trade liberalisation. The detail presented there formed part of the information informing the assessment of the combined impact for country types presented here.

Section 5 comments on a number of negotiating issues that were not specifically incorporated in the scenario, such as tariff escalation, bound versus applied tariffs, food aid and export credits. The second subsection considers the issue of product standards as this is central to efforts of developing countries, especially the poorest, to expand their exports, in particular of food products to OECD markets. The final subsection considers linkages to the Forestry and Distribution Services studies.

Section 6 discusses the mitigation and enhancement (M&E) measures that could address the most important issues raised in the SIA. It outlines mitigating and enhancement measures necessary to ensure that the potential benefits are realised and that efforts are made to offset and mitigate any adverse impacts.

2. SIA Methodology Applied to Agriculture

The SIA methodology has been designed to provide a framework within which the potential impacts of trade negotiating options could be assessed in a systematic, consistent and transparent manner. The Overall Project Inception Report for the current phase of the work programme (which covers Agriculture, Forest and Distribution Services), included an update of the SIA methodology that is being used in the current set of studies. This section elaborates how the SIA methodology is applied to agriculture in respect of four issues:

• Negotiation scenarios. The partial liberalisation scenario is defined to represent the proposals that currently appear the most likely to result from the negotiations. While we aim to include all aspects of the negotiations which may have a significant influence on sustainability impacts, issues on which no consensus proposals have emerged are not defined in any detail (some of these are addressed in Section 5.1).

• Indicators Assessment refers to a set of nine core indicators for sustainable development and two for sustainable development processes. Specific indicators are identified to elaborate interpretation of evidence on the core indicators.


• Country types and case studies. Six country types are identified, with incountry case studies for four selected developing and least developed countries.

• Causal Chain Analysis (CCA). The starting point for the assessment is the estimated effects of liberalisation on world prices and trade patterns. The manner in which country types adjust to these ‘global effects’ takes into account the liberalisation implemented by each type. The assessment is longrun in the sense that we consider the situation (equilibrium) that would prevail once the country type has adjusted to the effects of the trade liberalisation, assuming the only perturbation to the initial equilibrium is the trade policy changes. The adjustment assumed is that allowed by the existing features of the country or sector. For example, if the sector is characterised by constrained supply response, this is reflected in the adjustment (which would only be partial). A more extensive adjustment requires measures to address the underlying constraint, discussed under M&E measures.

Agricultural Trade Liberalisation Scenarios

The baseline scenario is the situation that would prevail without a new WTO agreement on agriculture. The SIA recognises that countries are not going to liberalise fully, and therefore a partial liberalisation scenario is used in the estimation of the impacts. This liberalisation scenario is defined as representing the strongest probable implementation of the negotiations agreed at the Doha Ministerial Conference, based primarily on the Derbez text as subsequently refined and elaborated.

The partial liberalisation scenario comprises three components or pillars:

Ø Tariff reductions – Developed countries are assumed to reduce tariffs by 36 per cent which is assumed to apply to all products. Developing countries are assumed to reduce tariffs by 24 per cent, again applied to all products, and subject to a maximum post liberalisation tariff of 40%. The scenario is implemented assuming that these average reductions apply to all products analysed, and to the applied tariffs on those products (i.e. the reductions are real). In practice there may be sensitive products for which the tariff cuts are less than the average, but the study does not go into this level of detail. Least developed countries have no reduction requirements.

Ø Reduction of export support – Developed countries are assumed to eliminate all forms of export support. Developing countries reduce export support by 50 per cent, and least developed countries have no commitments. It can be noted that the modelling studies cited in Section 3 and used to estimate effects on world prices usually only cover export subsidies.

Ø Reform of traderelated domestic supports – Developed countries are assumed to reduce tradedistorting domestic support by 60 per cent. Developing countries reduce domestic support by 40 per cent, and no reductions are assumed for least developed countries.

One of the objectives of the SIA is to assess the likely economic, social and environmental impacts of the fuller liberalisation scenario in various types of countries after they have adjusted to this trade liberalisation scenario. Most of the reduction in export and domestic support takes place in OECD countries and therefore affects the products they produce and subsidise, i.e. a limited range of (world prices of) products are affected.

As it is likely that the three scenario components will be negotiated as one package in the Doha round, the assessment is based on the combined impact (the MidTerm Report provides an assessment of the impacts of each of the three pillars).


Impact Indicators and Presentation of Significance

We adopt the general sustainability definition comprising the economic, environmental and social dimensions common to previous SIA studies (e.g. Kirkpatrick & Lee 2002). The same set of nine core indicators for sustainability impacts and two process indicators for effects on sustainable development are adopted for the three studies (agriculture, forestry and distribution services). A number of second tier indicators have been identified specifically for the agriculture SIA. These are elaborated with examples in Table 1.

Table 1: Sustainability Indicators for Agriculture SIA

Impact Dimension Core Indicators* Second Tier Indicators (probable effects on)

Economic Real income

Employment

Fixed capital formation*

Levels of production, income and trade (imports and exports)

Consumption (food prices)

Tax revenue

Levels of employment

Social Poverty

Equity

Health and education*

Whose employment?

Income distribution (e.g. by gender), quality of employment, land tenure and ownership

Public spending (affected by tax revenue)

Environmental Environmental quality

Natural resource stocks

Biodiversity

Environmental stress and intensive farming (water, agrichemical use, etc.), soil degradation

Deforestation rate, extensive farming

Process Policy framework (for sustainable development)

Institutional capacity

Existence of policies and international commitments

Government resources and capabilities

Notes: * indicates indicators that are not applied either because they are not directly affected in general (e.g. health and education) or they can be inferred from other indicators (e.g. investment follows changes in production incentives).

There is not always a unique correspondence between indicators and the impact dimension. For example, employment as income, and effects on levels of employment, are indicators of economic impact, whereas employment opportunities as livelihoods and the quality of employment or work conditions are indicators of social impact. The main value of the SIA comes not from the aggregate results for the dimensions or indicators, but from the identification of specific impacts that negotiators should be aware of and which might be


avoided, mitigated or enhanced through amendments to trade policy or complementary measures. The indicators used contribute to this.

The approach in the SIA is to use information on the secondary indicators to assess impact on the core indicators, e.g. evidence on effects of production of a particular commodity in a country and how it responded to changes in incentives (price, market access) in the past. In most cases it was not possible to get quantitative information on an indicator for particular country types, and the study used information on representative countries to identify the direction of the impact and significance. For example, it was often very difficult to make any definitive statements about impacts on biodiversity as this depends on local characteristics and details of the farming methods.

Table 2: Outline Presentation of Impact Assessments

Dimension, Core Indicator

Impact (issues, examples)

Direction and

magnitude

(q,s

,0,r

,p)

Current Stress

(L,M,H)

Extent

(L,M,H)

Reversibility

(yes, no)

Probability of

occurrence

(L,M,H)

Responsiveness

(L,M,H) Impact

significance (q,s,0 ,r,p)

Economic

Social

Environmental Institutional

Symbols to be used in the table blank or 0 nonsignificant impact r positive lesser impact p positive greater impact s negative lesser impact q negative greater impact ± positive and negative according to context – net effect is uncertain or varies

according to context s/r negative over an initial period of time but expected to become positive in the longer

term – similar combinations of symbols are used for other short term/long term effects (using 0 for nonsignificant impact)

L, M, H Low, Medium or High

Table 2 outlines the tabular form that is used to present the SIA results for each country type, with examples and elaborations of specific issues for countries or products included in the narrative text. For each of the impact dimensions, the table includes lines for each potentially significant impact identified and the columns are various assessments of significance. The table comprises two parts, the first relating to types and likelihood of impacts, the second to assessments of significance. The first three columns list the impacts and assess the direction of the effect (positive or negative). The next three columns evaluate the current situation (is there stress under the baseline scenario), the extent of the effect (in terms of coverage – does it impact on many or few) and reversibility. For our purposes, an impact is reversible if it can be reversed or offset by other effects due to the trade liberalisation. For example, reduction of export subsidies will increase the world price, so the effect on an importing country is a higher price of imports. However, the reduction in tariffs will offset (if not eliminate) the increase in consumer prices. Thus reversibility is interpreted independently of responses to the impact. The probability of occurrence is recorded as low, medium or high according to


the strength of the correlation between the trade measure and the impact. The column labelled ‘responsiveness’ refers to the effectiveness and capacity of policy and regulation, including policy actors that affect producers’ ability to respond to price incentives. The overall impact assessment in the final column is assessed according to the probability of the impact occurring, the likely magnitude compared with the base situation, the geographical extent and numbers of people affected, taking account of stress, reversibility, the effectiveness of relevant policy and regulatory frameworks, and the capacity to implement mitigation and enhancement measures. Each of these contributory factors is recorded in the table using the symbols shown. The assessments are inherently qualitative but informed by available quantitative evidence, and where the direction is assessed it is ‘graded’ as either mildly or clearly (lesser or greater) positive or negative.

Country Types

Six country types are covered in the study, two to represent developed countries. Four developing country types are distinguished, for each of which one country has been selected for an illustrative case study.

• Major Exporting Developing Countries (MEDCs), represent those developing countries that are significant net exporters for a wide range of products, most of which are in Latin America and South East Asia. This category includes the majority of middleincome developing countries except the small economies (especially small island states, see below). Their main concerns will be increased access to foreign markets, and they are unambiguous beneficiaries from liberalisation. Brazil is taken as the example.

• Highly Protected Developing Countries (HPDCs) have a relatively protected agricultural sector, exporting some products but importing others. This category includes most middle income developing countries not included as MEDCs (e.g. Egypt, China, Morocco and Tunisia) and some large lowincome countries (e.g. India and Indonesia). These countries can benefit from liberalisation in some (export) products, but lose in others (where they reduce protection), and thus face mixed impacts. As they gain for exports, and losses to producers of importcompeting goods are offset by consumer gains, the net impact is likely to be positive. India is the example.

• Least Developed Countries (LDCs) currently benefit from the most preferential treatment and the majority are in subSaharan Africa (SSA). They typically export cash crops that, with the exception of sugar and cotton, will not be directly affected by the liberalisation scenario and import food, especially grains (although many have constrained but significant domestic production capacity). These countries could benefit from liberalisation if they can increase exports or if higher import prices provide a stimulus to domestic producers. Tanzania is taken for the case study.

• LowIncome Developing Countries (LIDCs) are those that are not classified as least developed but are quite similar in terms of the pattern and efficiency of their agricultural sector. Most SSA countries that are not LDCs fall into this category. These countries are expected to reduce tariffs and compete with the more preferentially treated least developed countries in their export markets. Broadly speaking, the impacts on LIDCs will be similar to that on LDCs except that lower tariffs in LIDCs will offset any adverse effects on consumers from an increase in the price of food imports. Ghana has been taken as an example.

• The European Union (EU) comprises 25 member states but is treated as one group in the analysis, although we do consider variations in impacts across member states. In general, impacts will differ across regions and countries according to the products produced and scale and type of farming system. There will also be significant differences between impacts on the EU15 and the ten new members as the former have been subject to the


Common Agricultural Policy for a long period.

• Other Developed Countries (ODCs) are a disparate group as some exhibit agriculture protection similar to the EU (e.g. US, Japan, Switzerland) whereas others are major exporters with low protection (New Zealand, Australia).

In respect of developing countries (which as a category includes the least developed), the aim is to highlight two specific distinctions. The first is that between developing countries that are net exporters of products likely to be affected by liberalisation and those that are net importers (even if they export some of the products) and/or have high initial tariffs (so that reforms significantly increase competition from imports). Some countries are likely to benefit from increased exports whereas importers gain less, and may even lose. Many developing and least developed countries export few of the products that will be affected, as few tropical cash crops are affected by domestic and export support in OECD countries (two exceptions are sugar and cotton). The second distinction is between LIDCs that are expected to reduce tariffs and LDCs that have similar agriculture production structures but are not required to liberalise.

The classifications include all developed and most developing and least developed countries, but do not fully cover all countries. In particular, small economies, especially small island states, face particular problems. On 25 May 2005, twenty members (including several Caribbean states) of the WTO’s Committee on Trade and Development Dedicated Session on Small Economies presented a paper on the problems faced by small economies proposing issues to be addressed in negotiations (docsonline.wto.org, see also www.un.org/smallislands2005/ for discussions). Although many of the problems are not unique to small economies, the exposure of such vulnerable economies to multiple severe problems poses a major challenge. Many major WTO members (including the EU and US) oppose a specific designation or new category of ‘small economies’, but their needs should be recognized. In particular, given their limited endowment in natural resources and small domestic market, these economies tend to be dependent on imports, especially of food, with a limited capacity to earn export revenue.

Although some of these small economies are poor (including most that are landlocked), the majority of small island states are middleincome and therefore not explicitly captured in our LDC and LIDC categories. Mauritius, discussed as a MEDC, can be taken as representative of this group. On the one hand, they stand to experience an erosion of preferences on their exports, such as bananas or sugar, implying a revenue loss. On the other hand, they tend to depend on food imports, the price of which may rise. Even if reducing tariffs can offset the adverse effect on consumers, small economies suffer in becoming even more import dependent. The impact on small economies is broadly similar to that on LIDCs, with the proviso that they are especially dependent on food imports.

Causal Chain Analysis

Our analysis considers potential impacts for country types, analyses selected products in some detail, and includes four country studies. Analysis of current data and existing studies is used to make an assessment of the first order shortrun effects on prices and trade patterns. The longrun impacts occur after the sector has adjusted to these first order effects, which are the only ‘shocks’ considered. This provides an assessment of where significant economic, social and environmental impacts are likely to occur.

Short–run first order (adjustment) effects

The sustainability impact assessment requires a long term view of how the economy will ‘settle’ after adjusting to the liberalisation measures implemented, and the associated economic, social and environmental impacts. As a prior step, it is necessary to identify the

http://www.un.org/smallislands2005/


initial ‘shock’ of the trade liberalisation policy changes. This is referred to as the first order (economic) effect, represented by the price change associated with reducing tariffs or supports. This can be interpreted as the shortrun partial equilibrium impact. The shortrun effects in the case of agriculture are complicated by there being three pillars to the further liberalisation scenario. For a country that is itself liberalising under any pillar, there are domestic price effects. Other countries, however, are only affected in the shortrun if there are effects on world prices (e.g. due to reductions in export or domestic support measures by OECD countries) and/or on their market access. It is useful therefore to draw a clear distinction between effects on domestic prices, especially those due to one’s own tariff reductions, and effects on world prices. These can be separated when identifying shortrun impacts, although they should be integrated when considering longrun adjustments.

Longrun effects (causal chain analysis)

Causal chain analysis (CCA) is the fundamental assessment method used in the SIA. The aim is to identify the significant causeeffect links between the scenario and the eventual economic, environmental and social impacts. In most cases there will be linear causal linkage from the economic impacts to the social and environmental impacts, although reverse linkages are possible. For example, soil erosion may affect agricultural yields and hence returns for producers; the environmental stress associated with increased production may encourage the adoption of more efficient environmental management techniques (financed out of the increase in incomes). It may also have external impacts/offsite impacts on water pollution from increased pesticide use associated with increases in agricultural production, which in turn may affect the livelihoods of poor farmers further downstream or the access of the urban poor to clean water. Similarly, social impacts may have economic and environmental effects. However, most indirect or reverse effects are caused by particular responses to the impact or are caused by something other than the specific trade liberalisation, and are appropriately addressed under M&E rather than under CCA.

Economic impacts

We begin by identifying the price effects due to the trade measures identified in the scenarios (further information on price effects can be found in Appendix 1: Tariff Reductions and Domestic Prices, of the MidTerm Report). Changes in relative prices induce production (or adjustment) and associated net trade effects (distinguishing imports from exports) – these are the direct responses induced by price changes. Reduction of tariffs means that the price of imports is reduced. This should result in an increase in imports, unless domestic producers of competing products are able to reduce their prices (by absorbing lower profits and/or increasing efficiency). In general, consumers gain but importcompeting producers lose. In certain cases there may be very little effect on the volume of imports, especially if the domestic sector is efficient and/or flexible. The elimination of export subsidies will tend, in contrast, to increase world prices and therefore increase import prices, at least in the short run. For some importers of some products, the two effects can cancel out (the tariff reduction offsets the increase in world price).

Assessing impacts is made more difficult by the fact that a given price change can affect different producers in opposing ways. This is especially true in developing countries where the poorest subsistence farmers are often net consumers of the food crops they grow: a reduction in price benefits them as consumers but imposes a loss as producers (what they grow is worth less on the market). For example, Ashraf et al (2005) study the impact of a reduction in the price of corn on Mexico’s corn farmers. The poorest farmers are net consumers of corn and are largely unaffected (the consumer gain offsets the producer loss). Middle income farmers experience a loss in real income of over 50% (because they have limited ability to increase efficiency) whereas the largest corn farmers experience a 40% increase in real income because they can increase efficiency and take a larger share of the


market (displacing middle income farmers). In general, however, one can expect the most commercial farmers to gain from improved incentives whereas the least commercial (poorest) farmers must be enabled to gain (other measures are required to relax the constraints to supply response that they face).

Conventionally, in lowincome developing countries the literature distinguishes between cash crops and food crops. In general, cash crops are those produced primarily or exclusively for sale, typically for export. These can include food, but usually only foods that are not normally consumed by farm households, or at least are not major consumption foods, such as vegetables and fruits. In contrast, food crops refer usually to major consumption (or subsistence) foods; although production is often primarily for household consumption these can be sold for cash (the share sold is referred to as the marketed surplus). In lowincome countries this distinction remains valid as the majority of farm households that grow food only market a small proportion, and we use the distinction in discussing LIDCs and LDCs. Once the commercial farming sector expands, a larger proportion of producers are growing food mostly to market. Thus in middleincome developing countries the distinction is less important.

All of the reforms are likely to benefit competitive exporters as market access is improved and/or world prices increase. There are exceptions. Many of the export crops important to developing countries and LDCs are unaffected by the reforms (e.g. coffee, tea, cocoa), so there are no direct benefits to producers of these crops. However, as prices of other crops increase, the relative return to these producers declines, which may encourage crop substitution (e.g. from cash crops to the food crops for which prices have risen). Some LDC exporters may suffer a loss of preferences and therefore experience a loss. In the countries reducing export support, exporters overall will lose market share, although the more competitive producers should remain profitable. Similar concerns apply to reductions of domestic support. The overall impact on a country therefore depends on the initial composition of agricultural production and trade, the details of agricultural support measures in place and the competitiveness and responsiveness of producers.

There will be indirect effects through the impact on government revenue of tariff or subsidy reduction. Any countries required to reduce tariffs (i.e. all countries except LDCs under the scenarios) will face a loss of tax revenue. Whether this induces a significant adverse impact depends on: a) the importance of tariffs (on agriculture) in tax revenue; b) the scope for revenue replacement (substituting other taxes for tariffs); and c) the price elasticity of demand for agriculture imports (if demand is sufficiently elastic, the lower tariff on increased imports will be revenue neutral). In general, for developed countries a) is small and b) is high, so the impact would be insignificant. At the other extreme, for LIDCs, a) is large and b) is small so the impact may be significant, but offset by c) [the same applies for any LDCs that choose themselves to reduce tariffs, but this is not part of the scenario]. For other developing countries it is hard to generalise – HPDCs will be closer to LIDCs – a) is likely to be high, but effect is offset by b) and c); MEDCs may be closer to OECD – even if a) is high, the effects can be offset by b), c) and revenue from export sectors that expand. As these effects depend on how the government makes up revenue losses or reallocates expenditures they are not included amongst effects listed in the impact summary tables.


Social impacts

Price and production changes may directly and indirectly affect the wellbeing of different groups within a country, particularly disadvantaged groups, the poor, rural and urban, women and smallscale farmers, landless agricultural workers. Both financial and nonfinancial dimensions of wellbeing need to be considered.

Direct impacts on financial dimensions of wellbeing of interest in this context include changes in income, levels of employment, the price of food imports or domestically produced food insofar as they affect different groups in different ways. Increases in prices of food imports, for example, tend to hurt urban consumers, including the poor, in developing countries (and LDCs) but provide an opportunity for rural producers to increase domestic food production. The nonfinancial impacts on the wellbeing of rural producers include changes in vulnerability (linked to food security and ability to cope with external shocks), social stability and migration. However, these changes are difficult to measure and are likely to be the result of several factors or a chain of events and not trade policy alone. For example, trade liberalisation may provide an incentive to increase employment, but it is labour market conditions and regulations, not trade per se, that determine how this impacts on conditions of employment. Predictions about the impact of trade negotiations on these aspects of social sustainability can only be done in somewhat speculative qualitative terms.

The significance of the social impact will depend on the specific characteristic of each country. In most LDCs and LIDCs agriculture constitutes a large share of national income and employment. Smallscale farmers and women account for the bulk of staple food production and rural employment, and typically are significant producers of export (cash) crops. Changes in agriculture therefore may have significant impacts on inequality and on the poor. In higher income developing countries and in most developed countries agriculture accounts for a low share of the national product and employment. Social changes induced by agriculture trade liberalisation are likely to be more dissipated, and countries with higher incomes are generally better placed to bear adjustment effects. Furthermore, social impacts occur within a broader context of changes in the agriculture sector as an economy develops; commercialisation of farming is an underlying trend factor. In poor countries, the largescale commercial sector is relatively small and agricultural production, especially of food crops, is predominantly small scale and even subsistence. In this context, growth of the agricultural sector tends to benefit smallholders and the poor. In rich countries, at the other extreme, agriculture is highly commercialised and smallscale farmers tend to be poor and marginalised. Growth in production tends to benefit commercial farmers and poor farmers may be made even worse off (an issue to be addressed by M&E measures, such as rural assistance). Middleincome countries will be somewhere in between: in those characterised by high inequality (e.g. Latin America), smallscale and poor farmers may derive few if any benefits; in those with lower inequality (e.g. SouthEast Asia), smallscale farmers and the poor are more likely to benefit. Note also that the poor can benefit from increased farm and offfarm employment.

In cases where the economic effect is to reduce tax revenue, one can anticipate an adverse social impact (ceteris paribus, there is less revenue available to maintain public expenditures on social sectors).

Environmental impacts

Typically the impacts of trade liberalisation on the environment can be classified under five broad categories: product effects, technology effects, scale effects, structural effects and regulatory effects (see OECD, 1994). Product effects refer to the impacts, such as transport, related to the flow of products (or services) between countries. Some of these products may be environmentally friendly, while others may be hazardous to the environment. Overall product effects can be positive or negative, depending on the nature and volume of the


products traded. Technology effects occur when changes in trade policies lead to the transfer of production technologies, which can be harmful or friendly to the environment across borders. Scale effects refer to changes in the overall level of activity, which translates into higher use of natural resources unless technology is improved. Structural effects occur when trade liberalisation leads to changes in the sectoral composition of an economy. The resulting environmental effect will be positive if lesspolluting or less environmentally degrading activities are favoured, but negative if the reverse is the case. Finally, regulatory effects occur when trade affects environmental regulations and standards, and will be positive or negative depending on whether trade liberalisation induces better or worse environmental measures.

In the context of agriculture, environmental impacts are associated with changes in the volume of production, typically requiring the use of more land for production, switches between crops that have different environmental effects associated with them, and incentives for adopting new technology, changing the mix of land, labour and inputs such as fertilisers and pesticides in production. The nature of environmental impacts depends on the relative importance of these various factors and this is likely to be countryspecific. In some countries increased agricultural production is likely to lead to clearing of forests with consequent impacts for biodiversity, greenhouse gas emissions and soil erosion particularly where trees are felled on slopes (the Forestry study elaborates on these linkages). For example, expanded soybean production has been associated with the dramatic rate of deforestation in Brazil in recent years (note that this is a response to increased global demand and is not attributable to trade liberalisation). Other countries have to increase the intensity of land use, usually requiring increased use of fertilisers, pesticides and other chemicals (either to increase yields or reduce production costs) with consequent impacts on water and land quality. Agriculture can exacerbate pressures on water use, possibly reducing water availability elsewhere or with adverse effects on river systems. More intensive livestock farming can be associated with less consideration of animal welfare (e.g. battery farms). The significance of the environmental impacts also depends on the characteristics of the country concerned. Increased production of water intensive crops is likely to be more significant in a country that is waterscarce (e.g. Australia and arid regions of SSA) than in other countries where water availability is not a critical issue (e.g. Latin America or South East Asia).

Combined Impacts

A full assessment of the economic, social and environmental impacts would require a detailed countryspecific study analysing specific products and interactions (e.g. crop substitution). This broadbased assessment therefore concentrates on identifying the most likely significant impacts under each of the three areas. We do not generally consider interactions between economic, social and environmental impacts, and acknowledge that limitation, although we do refer to any significant feedback effects that are likely and consider interactions in discussing M&E measures. Nevertheless, by identifying many of the most likely impacts, the aim is to provide guidance to negotiators on the range of concerns that have bearing on the liberalisation scenarios proposed, and guidance to governments on the policy responses that may be required.

The nature and significance of social and environmental impacts in each country will depend on the combination of at least three factors. Firstly, the nature of the economic changes induced by trade liberalisation and their associated environmental and social impacts. Increases in economic activity are often linked with greater environmental pressure, although they might be offset if efficiency is improved or if higher economic growth translates into greater investment in environmental projects. Secondly, the social and environmental baseline conditions mediate the transmission of economic effects, e.g. are policies favourable to the poor being implemented and does the country have an environmental management strategy? Thirdly, the policies, regulations and institutions in place to safeguard against adverse social and environmental impacts are generally weaker in poorer counties (process indicators are


weak). We refer to these issues where possible, but emphasise that the SIA is essentially an exercise in identifying impacts that negotiators and policymakers should be advised to anticipate, so they can at least think about the policies that may be required to mitigate unfavourable impacts and enhance favourable ones.

3. Context: Trade Liberalisation in Agriculture

Existing studies of the effects of liberalisation of trade in agriculture have been an important source of information on likely effects to inform our impact assessment. There have been many studies reviewing and estimating potential economic effects of alternative scenarios for liberalising trade in agriculture, including reforms to export and domestic support arrangements (see the Inception and MidTerm Reports for literature reviews). Some studies use partial equilibrium analyses (e.g. Benjamin et al, 2003; Binfield et al, 2003; Fabiosa et al, 2003), which can be useful for detail on specific commodities. Other studies use computable general equilibrium (CGE) models (e.g. Hertel et al, 2000; ERS/USDA, 2001). These have the advantage of considering more of the interaction and indirect effects, but at a cost of operating at a higher level of aggregation. The various studies on multilateral trade liberalisation in agriculture are used for the SIA in two ways. First, to provide an indication of the magnitude of the effects of trade liberalisation on the different country types we consider in our analysis, i.e. estimates of the expected economic effects. Secondly, to provide estimates of the effect on world prices of agriculture products, an input to the CCA we employ (as described in the previous section).

Economic modelling studies are essentially concerned with the effects of specified policy reforms on prices; reported results for effects on welfare or trade (exports and imports) are actually derived from effects on prices. In simple terms, acknowledging that details and subtlety of analysis vary greatly, the policy reform is represented as a price change and the study models the response to this price change. Studies typically only consider responses to price changes induced directly by the policy change. Consider the example of removal of export subsidies by a country, where exporters in that country receive a lower price but the world price increases. Studies typically model three effects: lower exports by countries that remove a subsidy (a producer loss), higher exports by other exporting countries (producer gains), and more expensive imports for importing countries (a consumer loss). Studies rarely model the indirect effect on producers in importing countries, i.e. the possibility that they may increase production in response, and the subsequent effect this may have on domestic consumer prices, is rarely incorporated. Similarly, they rarely model indirect responses of consumers, who may alter the pattern of purchases. Furthermore, few studies allow for dynamic effects, i.e. they do not incorporate technical change by producers in response to price changes. In other words, most models are static: the policy ‘shock’ alters prices; affected producers (exporters) respond to this and the effect on consumers is determined by what happens to the (import) price they face. Models, subject to data availability, can address these issues, but rarely do (and even then usually only for a specific country).

In addition to the general limitations in the applicability of modelling studies outlined above, all model results are specific to the details of the scenario (policy change) and structure imposed, especially assumptions regarding response elasticities. Often, the latter assumptions are deeply embedded and not always transparent. As a general rule, the greater the degree of trade liberalisation represented in the scenario (policy shock) and the more responsive the economy is assumed to be (as represented by structural parameters), the greater the effect of liberalisation predicted by the model. As benefits accrue to the most competitive (more responsive) producers and losses are often incurred by the least competitive producers, if models have a bias it is towards overestimating potential gains. This is particularly the case of


estimates of effects on developing countries, as nonprice constraints on supply response are not always adequately captured in the models. This is one reason why the large gains predicted by models of trade liberalisation under the Uruguay Round have not been realised (another reason is that the liberalisation actually implemented was less than that represented in the scenarios).

The majority of economic modelling studies employ either partial or general equilibrium techniques. Partial equilibrium studies typically consider each product separately and only look at the direct effects of price changes on producers and consumers of that product. The advantages are that the data requirements are relatively undemanding (tariff, price and trade data at the product level; response elasticities can be estimated from historic data) and the study can address a high level of product disaggregation. The disadvantages are that interactions between different measures (e.g. the three pillars of liberalisation) or products are not captured. Nevertheless, such studies are useful to identify which products may experience the greatest effects, and this can be related to the trade and production patterns of countries in respect of these products.

General equilibrium studies consider interactions between producers, and therefore focus on changes in relative prices, and can allow for effects on factors of production (specifically labour income). For this reason, general equilibrium models can be very useful to simulate the distributional effects on households. For example, if relative prices of a product increase, producers will expand output and labour in that sector will earn a higher income. There is a mixed impact on consumers who are also producers, but a net loss for consumers who are not producers. In this context, Blake et al (2002) show that the effect of agriculture trade liberalisation is beneficial for Uganda, but the extent of the net benefit depends on the flexibility of labour markets, and the greatest benefit comes from unilateral rather than multilateral liberalisation. Another advantage of general equilibrium models is that they can capture interactions at a global level, i.e. they can model global effects and estimate impacts on individual countries or regions. The disadvantages of general equilibrium models are that they are relatively aggregated at the product level (and at the country level for global models) and they impose a strong structure on the economy (especially assumptions regarding responsiveness and flexibility of factor and product markets).

We summarise the results of some partial and general equilibrium studies to give a flavour of the types of effects of liberalisation of trade in agriculture estimated. It is useful to note that all of these models are predictions, and the magnitude of the results is very sensitive to the precise scenario modelled and the model structure assumed. In interpreting the models, one should not attach too much weight to the precise numerical estimates of effects, nor can one unambiguously assert that one model is ‘better’ or more accurate than another. What one can observe is the direction of change estimated and the relative magnitudes (for countries or products). In particular, one should ask if the models are consistent in the pattern of effects they predict, e.g. are there some (types of) countries consistently predicted to gain the most (or the least), and are the effects for some products consistently predicted to be greater than for other products. If a consistent pattern emerges, this is useful information for negotiators and policymakers. It is the direction, pattern and relative magnitudes of effects that provide information to our SIA.

Partial Equilibrium Estimates

Hoekman et al (2004) provide a good example of the partial equilibrium approach. They estimate the effect on world prices of a 50 per cent reduction in tariffs, domestic support and export subsidies separately for a sample of 267 commodities. They use the estimated world price effects to estimate the impact on exports, imports and welfare for 144 countries. For ease of presentation, and acknowledging heterogeneity across countries, these are aggregated into three groups – developed countries (OECD), developing countries and least developed


countries (LDCs). The findings indicate that developing country exporters of ‘supported’ agricultural products (i.e. those affected by export and domestic support) benefit from reductions in subsidies and trade barriers, whereas net importers may lose due to higher world prices. They also show that tariff cuts have larger impacts than reform to domestic and export support, partly because tariffs cuts would apply across all countries. Reductions in domestic support and export subsidies have little impact on exports, imports or welfare of developing countries as a whole, but certain types of countries are likely to gain whilst others lose. Combining effects of the three pillars, OECD and developing countries benefit whereas LDCs lose in terms of welfare; liberalisation by all countries compared with liberalisation by OECD only gives greater net welfare gains to OECD and developing and lower net welfare losses for LDCs. The simulations ignore trade preferences, which may understate losses to LDCs and overstate gains to developing countries and, as the estimates are partial equilibrium, they do not account for interaction effects. Partial equilibrium approaches are also quite suitable to explore ‘technical’ issues, such as the effects of tariff rate quotas (Laroche Dupraz and Matthews, 2004).

Laird et al (2004) also use a partial equilibrium model, but simulate the combined impact of the three pillars under various scenarios for aggregate groups of countries. They find large gains for developed countries, small gains for developing countries but net losses for the LDCs. For the LDCs the losses for consumers, resulting from higher world prices, exceed the gains to producers, whereas for developing countries producer surplus gains exceed consumer surplus losses (partly because tariff reductions dampen the domestic impact of higher world prices). Note that the latter effect refers to developing countries as a combined group; any individual developing country will not necessarily derive a net welfare gain, depending on the particular pattern of agricultural production and trade.

General Equilibrium Estimates

Global trade models using CGE estimation give projections for the effects on world prices, trade and welfare of different (types of) countries. Hertel et al (2002) model 40 per cent reductions in tariffs, export subsidies and domestic support, providing results disaggregated by region. The study predicts significant gains in global economic welfare, and significant changes in patterns of trade. In general, the welfare gains are greatest for those countries that are initially the most highly protected (including the EU) and for developing countries that are food exporters, especially in South America.

General equilibrium models can also be used to show that the constellation of policy reforms is important – the effects of removing one policy depend on what replaces it. Dimaranan et al (2004) provide a general equilibrium analysis (using a version of the GTAP model) but address only reductions in domestic support by OECD countries. The analysis predicts significant increases in world prices for wheat, coarse grains, oilseeds, ruminants and ruminant meat, with only sugar, dairy and a heterogeneous ‘other crops’ registering a decline in world prices. Thus, a ‘50 per cent reduction in domestic support for OECD agriculture leads to welfare losses for most of the developing regions, as well as the combined total group of developing countries’ (Dimaranan et al, 2004: 87). Major exporters such as Argentina and Brazil do gain, but there are large losses in farm incomes in OECD countries, especially Europe. However, if current domestic support measures are replaced with landbased payments to support farm incomes, as proposed by the EU, OECD farm incomes can be maintained. Furthermore, the reinstrumentation of OECD subsidies under this ‘comprehensive reform scenario results in increased welfare for most developing countries, with gains on other commodities offsetting the terms of trade losses from higher programme crop prices’ (Dimaranan et al, 2004: 88). In other words, OECD can feasibly eliminate trade distorting domestic support but replace it with measures that ‘compensate’ domestic producers and dampen effects on global trade.


Bouet et al. (2004a) examine multilateral agricultural trade liberalisation using an applied general equilibrium model. It is a very detailed study that deviates from other modelling attempts in at least two ways. First, it accounts for differences in applied and bound tariffs and between AMS ceilings and actual usage. Because applied tariffs are frequently lower than bound tariffs, a negotiated reduction in bound tariffs does not always translate into lower applied tariffs. Second, it accounts for existing preferences, for example granted by the EU to LDCs. Accounting for preferences is important because several African countries will face preference erosion under multilateral tariff liberalisation. On the other hand, not all products will have actually faced applied tariffs.

The study includes three different types of scenarios based on preliminary WTO discussions: • a 40% cut for tariffs lower than 15% ad valorem to 60% cut for tariffs higher than

90% • a 100% reduction in export support • a 55% reduction in elements of domestic support linked to outputs and inputs

The study presents estimates of each of these scenarios as well as a combined “Doha” scenario, applied to all products simultaneously, and estimates effects on welfare (GDP). Although exports increase for all regions, the effect is greatest (in percentage terms) for developed and South Asian exporters, and for the poorest countries (probably because these include South Asia).

Table 3: Multilateral agricultural trade liberalisation and agriculture welfare (GDP) % change, by region and component scenario

GDP (bn 1997 US$)

Domestic support

Export subsidies

Tariffs Doha agreement, 3

pillars EU 25 8235 0.0 0.0 0.1 0.1 USA 7952 0.1 0.0 0.0 0.1 Asia developed 5233 0.1 0.0 0.3 0.2 EFTA 408 0.0 0.1 0.5 0.6 Cairns developed 1092 0.0 0.0 0.1 0.0 Mediterranean 454 0.3 0.1 0.2 0.1 Cairns developing 2012 0.0 0.0 0.0 0.0 China 876 0.1 0.0 0.0 0.1 RoW 2026 0.1 0.1 0.1 0.1 South Asia 527 0.0 0.0 0.4 0.4 Sub Saharan Africa 207 0.0 0.1 0.1 0.1 World 29023 0.0 0.0 0.1 0.1 Richest countries 22920 0.0 0.0 0.1 0.1 Developing countries 5368 0.1 0.0 0.1 0.1 Poorest countries 734 0.0 0.0 0.3 0.3 Source: Bouet et al (2004a), table 6

These increases in exports do not translate into welfare gains for all regions, when the associated impact of increased prices is taken into account (Table 3). The estimates suggest that the welfare effects are small. Developing countries as a group are worse off. Although welfare increases for the poorest countries (due to the gains for South Asia), subSaharan Africa (SSA) is made worse off. Under the combined scenario, exports would increase by 8% (or US $ 26 bn) and welfare by 0.1 % (or US $ 29 bn). This is lower than other model estimates because of the use of lower actual AMS and applied tariffs than bound and including existing preferences.

The main gainers in terms of welfare are the developed countries (that would reduce their support to the agricultural sector), and developing countries (e.g. South Asia where exporters


also benefit from increased world prices for rice). The Cairns group would expand their agricultural output and exports. There are negative effects for the agricultural sector in the EU, EFTA and developed Asia.

The main losers include countries with existing preferences, especially SubSaharan Africa. These countries will experience a loss of trade preferences and hence increased competition from the Cairns group. Exports will increase marginally under the combined scenario, but welfare will decrease. The Mediterranean group will also lose, for example because it will need to import cotton at higher prices.

The main conclusions of modelling studies suggest that agricultural trade liberalisation results in modest gains in the order of 0.10.2 per cent of World GDP, but that the results differ markedly across type of countries, type of product and by type of trade policy (tariffs or subsidies removal). In applying the SIA, we address these variations across types of countries. However, for the SIA we make more use of the model estimates of effects on world prices for affected products. Although a number of modelling studies provide estimates of effects on world prices, they all differ in the scenarios simulated (and none use precisely the scenario we have adopted). These studies were reviewed in the MidTerm Report and are not repeated here. However, the world price effect estimates from those studies, such as Bouet et al (2004a), closest to our scenario are summarised in the next section. In fact, the range of estimates for price effects for particular commodities from these comparable studies is quite narrow. Furthermore, the estimated effects are quite low, rarely greater than a five per cent increase. As noted in Table 4 (below), none of these studies included cotton, so the price estimates are taken from other studies (and are significantly higher).

4. SIA for Country Types

Six country types are covered in the study. The four developing country types are: Major Exporting Developing Countries Highly Protected Developing Countries Least Developed Countries LowIncome Developing Countries

The developed country types are: The European union Other Developed Countries

The country types chosen allow us to address not only the differential impacts of liberalisation across countries, but also the tensions between different types of countries in the negotiations. Specifically, we have developed versus developing exporters, exporters versus importers among developing countries, and least developed versus lowincome countries. In general, among developing countries, food exporters will benefit and food importers will lose out unless domestic producers can respond. This impact is driven by reductions in export and domestic support. Ashraf et al (2005) analyse the impact of OECD agricultural support policies on the poor, noting that the majority of poor countries are net food importers. As OECD support reduces prices of food imports, this has provided a benefit to foodimporting countries (and a cost to foodexporting countries). The reduction in support removes this benefit.

Two related factors complicate the assessment for net food importing countries. First, one would like to know why they are net importers: is it because of structural reasons, such as having insufficient arable land to be selfsufficient (e.g. small island economies), or is it


because domestic production is underdeveloped and not competitive with imports (suggesting that it could become competitive). Second, one would like to know the price paid for food imports. In particular, are they receiving subsidised food imports, e.g. food dumped by OECD countries? If this is the case, although consumers benefit from the low prices domestic producers are being undermined by having to compete with imports at below the (market) world price. Liberalisation that brings imports up to the (increased) world price may therefore enable domestic producers to compete.

Although we discuss broad results for the six country groups, the actual impact will vary from country to country within any group. Hence, the country case studies included are no more than examples, and should not be generalised as applying to all countries of the relevant type. The MidTerm Report included an SIA for six major products: wheat, rice, beef, sugar, cotton and (green) vegetables. These results are not reported here in detail, but are important information used in the SIA for country types so the main results are summarised. In particular, these products were used as a guide to the impacts that could be expected as they tended to be important products for at least some country types. Note that in the case of sugar some of the most important effects are due to reform of the EUACP Sugar Protocol. Although this is not specifically part of the liberalisation scenario, the need for reform is to meet WTO rules and relates to the terms of the EU’s support for sugar producers. As it is such a closely related issue, it is included in the assessment.

To indicate the importance of these products for different country types, some information on trade shares for the six products is given in Table 4a. Note that the estimated impact of implementing the agricultural trade liberalisation scenario (all three pillars) on world prices is quite mild, unlikely to be higher than a 6% increase for wheat (and other cereals), a 24% increase for beef and other meats, and below 2% for rice and vegetables. The estimated impact on the world price for cotton is higher, in the range 1020%. For sugar, although the estimated effect on the world price is only 4%, the effect of reform on the price received by Sugar Protocol countries will be much greater (and negative). In general, the increases in world prices are less than the reduction in import prices that would result from proposed tariff reductions. In the MidTerm Report (Appendix 1) we show, for developing countries, that if the initial tariff was 40% the tariff reduction would reduce the price by six per cent (for an initial tariff of 20% the price reduction is 4%). This implies that the major global impacts will arise from changes in market access, including tariff reductions, although there will be significant domestic effects in countries (mostly OECD) reducing domestic and export support.

Considering exports first, we can note that none of the six products are major export products for the EU overall, although some are important for specific countries (e.g. beef for Ireland and wheat for France), whilst only beef and wheat are relatively important for the US. The more important export crops (excluded from the table) for the EU are beverages and dairy products, while for the US corn (maize) is a significant export. Furthermore, many countries (especially developed) are both importers and exports of most products.

Sugar and to a lesser extent beef are among the major export products for Brazil (coffee and soybean oil are others), whereas all except cotton are relatively important exports for India, especially sugar and rice. Ghana and Tanzania represent two types of SSA country, most of which have exports concentrated in a few products. For some, like Tanzania, these may include cotton or sugar. For others, like Ghana, the major exports are not products likely to be affected by the agriculture liberalisation scenario, e.g. cocoa or coffee. For many SSA countries, although typically not the LDCs, vegetables and fruit are becoming important. Wheat is a major import commodity for Brazil, mostly used as animal feed. Cotton and vegetables are major imports for India. Many SSA countries, LDCs and LIDCs, exhibit the pattern of major imports being sugar and grains (wheat for Tanzania, rice for Ghana, often maize for many countries).


Table 4b summarises the results of the SIA for the six products. The aim here is to identify which country types are most affected (and in what way), which clearly depends on whether they are net importers or exporters of the product and whether producers are currently protected. The Table also highlights the major social and environmental impacts.

Table 4a: The importance of Six Selected Products in Agriculture Trade, (percentage of product in total agricultural trade)

Imports Cotton Sugar Beef Wheat Rice Vegetables Total EU 0.6% 2.1% 2.0% 1.8% 0.5% 6.1% 13.2% US 0.0% 1.8% 5.9% 0.6% 0.4% 7.1% 15.9% Brazil 2.8% 0.3% 1.7% 27.4% 4.0% 5.7% 42.0% India 11.7% 0.5% 0.0% 0.0% 0.0% 19.5% 31.7% Tanzania 0.1% 12.5% 0.1% 21.8% 9.7% 2.1% 46.3% Ghana 0.0% 12.5% 0.1% 3.0% 21.0% 0.1% 36.7%

Exports Cotton Sugar Beef Wheat Rice Vegetables Total EU 0.2% 1.9% 2.1% 1.9% 0.4% 5.4% 11.9% US 3.8% 0.7% 5.5% 5.9% 1.3% 3.1% 20.2% Brazil 0.9% 14.0% 4.7% 0.0% 0.0% 0.1% 19.9% India 0.1% 7.5% 4.8% 5.5% 13.2% 4.7% 35.8% Tanzania 7.9% 2.9% 0.0% 0.1% 0.6% 5.9% 17.3% Ghana 0.5% 0.0% 0.0% 0.0% 0.1% 1.8% 2.4%

World Price 1020% 4% 14% 36% 12% <1%

Note: World Price gives the range of estimated changes in the world price for the commodity from studies that model the (combined) impact of scenarios closest to the scenario we use for the SIA. The studies did not include cotton, so reported estimates are from specific studies on cotton.

Source: SIA Agriculture MidTerm Report (Appendix Tables for world price effects).

Table4b: Key Identified Impacts for the Six Products


Sugar Production losses in EU and Sugar Protocol, gains in exporters (e.g. Brazil, India, Australia).

Income and employment gains/losses as per production.

General consumer gains from lower prices.

Adverse where production increases.

Benefits where production falls.

Cotton Production losses in US and EU, gains in exporters (includes some poor countries).


General consumer loss from higher prices (of textiles, clothing).



Wheat Production gains in exporters (e.g. OECD, MEDCs).

Losses in importing countries (HPDCs, LDCs, LIDCs)


OECD prices lower.

Elsewhere consumer loss from higher prices (offset by tariff cuts)

Generally mild.





Rice Production losses in OECD, gains in exporters (MEDCs and some HPDCs).


OECD prices lower.


Generally mild.



Beef Production losses in EU and Japan, gains in exporters (e.g. MEDCs, US, Australia).


OECD prices lower.




Green Vegetables Production losses in OECD and HPDcs; gains in exporters (includes some poor countries).


Minor price effects

Generally mild.



Note: Improved market access provides the major gains for exporters.


Box 4.1: The environmental impacts of sugar policy reform on developed and developing countries

The cultivation and processing of sugar produces environmental impacts through the loss of natural habitats, intensive use of water, heavy use of agrochemicals and runoff of polluted effluent. This leads to the degradation of soil, wildlife and water where sugar is produced and in downstream ecosystems. The adverse effects tend to be greater in the case of sugar cane (developing countries), where the land has no alternative uses in rotation, than sugar beet (predominant in temperate climates) as they can be offset through effective crop rotation. Domestic support to sugar production which encourages surplus production can aggregate these effects.

Impacts on soil erosion An estimated 56 million hectares of cropland is lost every year due to soil erosion and degradation. Cultivation of sugar crops can contribute to increased rates of erosion and soil removal at harvest. Erosion is a significant issue in areas under sugar cane or beet cultivation, particularly in tropical areas (where most cane is grown) because rates of erosion in tropical ecosystems are usually greater than the rate of soil formation. Three million tonnes of soil is lost per annum from beet farms in the EU. Estimates of soil losses from windgenerated erosion under sugar beet (where the fields are left bare over the winter period) range from 13 to 49 tonnes/acre per year in the US.

Impacts on soil health Soil health can be broadly defined as the sustained capability of soil to accept, store and recycle nutrients and water and maintain crop yields. Combined impacts of sugar cultivation can lead to a loss of fertility, particularly for cane sugar, which is generally grown as a monoculture. A particularly significant impact of sugar crop cultivation on soil health is compaction resulting from the use of heavy machinery. Soil compaction restricts the rooting ability of the crop and decreases water infiltration rates. Increased rates of surface water runoff can also lead to flooding. Salinisation and acidity of soils constitute other problems that principally affect cane growers as a result of overirrigation and inadequate drainage and fertiliser use. Salinity or acidity of soils has been linked to high declines in cane yields.

Farmlevel impacts (species and habitats) Intensive farming can create agricultural systems that are relatively lacking in biodiversity. With the possible exception of birds, animals present in cane fields are often regarded as pest species and subject to control. Weeds and pests may also provide important resources for other (nonpest) wildlife which play an important role in the food chain and health of the environment.

Landscape level impacts (Ecosystems) Agriculture is the main cause of wetland habitat loss. This occurs through the runoff of polluted effluent into water supplies or by altering the natural flow regime. The sugar industry in Australia has undertaken a number of major infrastructural projects including damming the Burdekin, Tully and Barron Rivers, which has altered the flow into the Great Barrier Reef. Sediment loads have been shown to increase damaging offshore reefs. In Florida, nutrientrich runoff from sugar cane fields is held largely responsible for the decline in the Everglades (a naturally nutrientpoor wetland where sawgrass used to thrive). In Spain, sugar beet irrigation in Andalusia is contributing to lower water levels in the Guadalquivir River, limiting the water reaching wetlands during the summer. Effluent from sugar mills and from processing biproducts (e.g. molasses) has been shown to adversely affect freshwater biodiversity, particularly in tropical rivers.

Source: Adapted from WWF (2004).

The broad nature of this study involves the selection of country types based on their trade and economic characteristics (without a gross trade impact, it is unlikely that social and environmental impacts are significant). Because social and environmental conditions may vary within the country types, the overall social and environmental impacts may not be representative for each country of a particular type and the nature and direction of


environmental and social impacts might differ among different countries. The SIAs report the most likely impacts to be observed in each country type.

Although impacts on all dimensions vary by product, this is most important for environmental effects. Of particular importance for determining environmental effects is the water and chemical input intensity typical in production. This is illustrated for the case of sugar in Box 4.1, a product that can have a number of adverse environmental effects. This is represented in the SIA tables under the column labelled ‘current stress’ (see summary impact tables below), where we assess the environmental pressures associated with the products most likely to be affected. For example, in countries where water is scarce and topsoil is fragile, relatively water intensive crops such as sugar and cotton are more likely to impose a stress on the environment than indigenous foods (or nomadic pastoralism). In such cases stress would be graded as High (H), implying that production increases are more likely to have adverse environmental impacts than in cases where stress was low. Typically, food crops have relatively low environmental stress, especially if local varieties are used, as do many cash crops suitable to smallholder production (e.g. coffee, bananas and cocoa). Farming that helps to preserve an environment (e.g. beef in the Pampas) could also be viewed as low stress. Plantation crops, such as sugar or oil palm, may be more likely to have high stress.

The SIAs also consider economic and social stress. Economic stress will be associated with price volatility and output variability (the economic implications of susceptibility to pests or variations in rainfall). For example, cash crop exporters face significant price volatility on world markets, typically greater than that observed for domestic food, and rainfed agriculture is more vulnerable to changes in rainfall than irrigationbased agriculture. In general economic stress would be higher for cash crops than food crops, or for export production compared to domestic production. To some extent, social stress is related to economic stress. For example, if prices are very volatile then incomes will tend to be very variable, putting pressure on social and risk coping strategies. More generally, exporters vulnerable to what happens in distant markets face higher stress than producers selling on the local market. Another dimension of current social stress is if poverty and/or inequality are very high, which will be related to economic stress (e.g. high inequality tends to be associated with policy distortions and restricted access to inputs such as land, so supply response is more constrained). These are the various issues we capture under the stress columns in the SIA summary tables.

A final point is worth noting here (and is returned to in Section 5). The world price effects of agriculture trade liberalisation are very small compared to the normal yearonyear variability in local prices faced by most farmers (and consumer or market prices are less volatile than farmgate prices for a host of reasons). Typically price volatility is ten times greater than the price change estimates in Table 4 (i.e. 2050% rather than 25%). Furthermore, in terms of world prices, the volatility is pronounced without any strong trend so it is extremely difficult to forecast prices. ‘If there is one stylised fact that tends to be applicable to commodity prices in general, it is that of general volatility rather than predictable trend movements’ (Newbold et al, 2005: 493). An implication of this is that most producers will not actually notice any world price changes that result from liberalisation – they will be hidden by the ‘noise’ of normal price volatility – although they will notice changes in export opportunities and import competition. As the SIA assumes that world price changes are observed, and that producers respond, our assessment is unlikely to understate the impact.


4.1. SIA – Major Exporting Developing Countries

Although there is considerable variability in the estimates from different studies, the combined impact of implementing the three pillars is likely to increase world prices (and market access) for a number of products. The largest price increases, about four per cent or higher, are likely for cereals, beef, dairy products and sugar, whereas moderate increases (2 4%) are likely for oilseeds. For convenience, we will refer to these five categories as the ‘affected products’ – those for which various studies consistently estimate world price increases in excess of two per cent. In general, developing countries that are significant exporters of these products are likely to benefit. Table 5 gives some examples, mostly Latin American countries, indicating the importance of affected products in exports of the countries and indicating some of the main products covered. Few African countries are major exporters of affected products, as they tend to export tropical cash crops (e.g. coffee, cocoa, tea), and Africa can be considered as covered in the LDC and LIDC groups (with North African countries and South Africa better treated as HPDCs). South American countries such as Argentina, Paraguay and Uruguay are not only major exporters of affected products (such as beef and cereals), but such products also account for a significant proportion (generally over a quarter, and in some cases more than half) of their exports. Although Brazil is also a major exporter of agriculture products in volume terms, they account for less than a quarter of total exports. Affected products are also significant for Central American countries, sugar and beef being the most important in these cases.

Mauritius is included to highlight that benefits do not accrue to agricultural exporters per se, but only to those exporting products for which world prices increase or market access improves. Mauritius is a major exporter of sugar, but is likely to lose from liberalisation because its preference margin is likely to be reduced (i.e. the price at which it can sell sugar to the EU under quota is reduced). In this context, it is important to note that although sugar is a product affected by the agricultural trade liberalisation, the effect of the SIA scenario is small relative to the effect of reform of the Sugar Protocol that benefits ACP countries, especially Mauritius. We return to this issue later as it has broader relevance in the context of EU trade preferences to ACP countries (not itself part of the SIA scenario), especially small island economies.

Table 5: Examples of Major Exporting Developing Countries

Country Export share (ave %, 199598)

products covered by OECD:

Major products (price change, country’s exports)

Domestic support

Export subsidies

Argentina 25.6 29.3 beef (+), wheat (+) Belize 46.6 47.5 sugar (+) Brazil 13.1 20.1 beef (+), soybeans (+), sugar (+)

Costa Rica 37.5 44.5 sugar (+) Guatemala 48.6 42.0 sugar (+), green vegetables (+) Mauritius 24.6 25.4 sugar (ve) Paraguay 55.1 27.0 soybeans (+) Uruguay 23.0 25.2 beef (+), grains (+),

Notes: Trade share is exports of products covered by OECD support measures (domestic and export) as a percentage of total country merchandise exports.

Source: Hoekman et al (2004) for export shares, authors for major products.


Obviously, the countries that benefit most are those exporting products the world prices of which are likely to increase significantly. As these developing countries are also expected to reduce their own tariffs, world price effects will not necessarily translate into domestic price changes. For example, if the initial tariff was 20%, the average 24% tariff reduction implemented by developing countries would reduce domestic prices by about four per cent. To some extent, the two effects will offset each other. For countries that are net exporters, domestic production is presumably efficient, i.e. domestic prices reflect local costs of production that will be below the world market price, so the overall effect will be a boost to producers. Although prices of some imports may increase (e.g. wheat for Brazil), any effects can be offset by tariff reductions and/or substitution with other products (e.g. soybean meal for wheatbased animal feeds).

Box 4.2: The economic impact of developed country cotton subsidies on major exporting developing countries: implications for Brazil

Brazil is one of the major cotton producers that can expect to benefit from reductions in OECD subsidies. In absolute terms Australia, Brazil, Turkey, India, Mexico, Uzbekistan and Pakistan would receive over twothirds of the increase in total world cotton earnings as a result of the removal of developed country cotton subsidies as they are the largest producers and often have the greatest capacity to increase supply in response to an increase in world cotton prices (Gillson et al., 2004).

In Brazil, 85 percent of cotton production is cultivated in the Cerrado region which has witnessed a dramatic expansion in cotton production over the last ten years (which is likely to have increased environmental stress in the region). Production in Brazil is predicted to increase to 863,000 tonnes in 2004/05 from 809,000 tonnes in 2002/03 (compared to 623,000 in 1980/81). Increases in cotton production have occurred primarily because Brazil has modernised its production, harvesting, ginning and cottongrading equipment. Research and development institutions have made available to growers seed varieties with not only longer and stronger fibres but also higher yields (which have risen from 208 kg/ha in 1980 to over 1000 kg/ha by 2004). Brazilian cotton growers have also started to employ better production practices to control water, fertiliser, insects and plant diseases. Furthermore, careful attention has been paid to ginning, so quality is maintained throughout the ginning process.

Cotton exports from Brazil in 2002/03 were at 170,000 tonnes, up from 147,000 tonnes in 2001/02. The main export destinations were Argentina, Japan, Indonesia and China. Cotton exports are predicted to rise to 200,000 tonnes in 2004/05 owing to increased production forecasts. Brazil has also experienced bumper crops of soybeans, sugarcane and coffee. As a result, transport and shipping infrastructure could come under strain during peak export periods.

The increase in efficiency of Brazilian cotton production has been particularly beneficial for Brazilian textile producers, as it has assured them a reliable source of raw cotton at competitive prices. The total consumption of raw cotton in Brazil in 2002/03 was 850,000 tonnes, with domestic production the main source. Brazil’s imports of cotton rose to 80,000 tonnes in 2002/03, from 50,000 tonnes in 2001/02. These consisted largely of US and Paraguayan cotton, but also include some West African supplies. Although Brazil was a net exporter in the early 2000s, it became a net importer from 2003; the removal of OECD subsidies would probably make Brazil a net exporter again.

Source: ICAC (2002)

Box 4.2 illustrates the case of cotton, with an emphasis on Brazil. Although there are very poor countries that export cotton (see the SIA of LDCs), they are minor suppliers to the world market. The point being made here is that overall and for most commodities the largest benefits from liberalisation go to those countries that are initially the most competitive producers with export capacity. Thus, the country types we classify as MEDCs can anticipate significant gains from liberalisation.


Economic Impacts: For significant exporters, the likely scenario is relatively stable domestic prices but an expansion of exports, influenced more by enhanced market access than by the change in world prices. This will lead to a rise in farm incomes, some of which should benefit labour (e.g. increased demand for harvesting labour), but some of which could be capitalised into land prices (especially for commercial farms). Overall, there will be a boost to the agriculture sector, and the net economic impacts are likely to be positive. Furthermore, multiplier effects can be strong, both in the supply chain as well as through consumption links as farmers spend their enhanced incomes, implying dynamic gains. For countries that are significant exporters of affected products, the beneficial effects should be significant. For countries that are minor exporters, or export products that are not significantly affected, aggregate impacts are unlikely to be significant (although in some cases certain producers may benefit). In the summary table (Table 6 below) we identify four different economic impacts: two are production (or real income), exporters and domestic producers competing with imports, and we also consider effects on consumers and net employment. In general, current stress levels are low as the sectors are competitive (but medium where world export prices are volatile) and the extent of effects is medium or high. The effects are generally positive, likely to occur in an environment where supply response (effectiveness and capacity of policy) is high, so a significant positive impact is expected.

Social Impacts. Where the economic benefits are positive, social impacts in terms of income and labour generation should also be positive, but less significant because they are dissipated. Therefore only part of any gain in farm incomes accrues to labour, especially relatively poor rural labour and in certain products. For example, gains to sugar exporters could benefit labour for harvesting, whereas gains for beef or cereals are more likely to accrue to commercial farmers or enterprises. However, some agricultural operations are highly labour intensive, as are many parts of processing and this is usually for 'unskilled' labour. There can be very strong links to farm wages following farm booms. In countries such as Brazil where agriculture, although a major sector, represents a small proportion of GDP and employment, the overall impact on real income gains and better quality of life will be modest. Given pervasive poverty and high inequality, social stress is high. Social concerns appear in terms of further smallfarmer marginalisation and rural migration although for the type of countries and exports considered here, smallfarmers are in decreasing importance. In Argentina, previous liberalisation together with the incentives to use more advanced farming practices such as fertilizers, irrigation, GMOs and mechanisation (with positive impacts on agriculture productivity) have led to a shift towards largescale commercial farming practices, marginalisation of smallscale farmers and rural migration (see Schapper and Parada, 2001). This suggests limited social benefits from further liberalisation. Urban poverty is likely to be indirectly aggravated by declining agricultural employment leading to migration from rural areas to urban centres (Maltais et al, 2002). This also raises concerns about income inequality, which is a critical sustainable development issue in most Latin American countries. However, inequality is more a reflection of inbuilt institutional bias, and there is considerable evidence that smallscale farmers are equipped to benefit from liberalisation (they are responsive to incentives). In other words, inequality is as much a constraint on supply response (captured under stress and the effectiveness column) as it is an effect of trade reform (so the impact on inequality is deemed positive, i.e. reducing inequality).

To the extent that increases in world prices are not transmitted to domestic food prices, either because tariffs are reduced or because domestic producers respond to better incentives, consumers will be largely unaffected. For exporters facing a reduction in preference margins, such as Mauritius, the social impact would be adverse. Because sugar plantations employ lowwage labour, the effect would be the greatest for the lowest social strata, raising concerns about increased poverty and inequality.


Environmental Impacts: In general, expansion of export production leads to extensification – if new land is available it will be brought into use as this option is cheaper than the alternative of using inputs more intensively. In land abundant economies where production increases are met by expanding the land areas under cultivation (against forestry, for instance), negative environmental impacts are expected as deforestation has been identified as one of the main threats to biodiversity, natural resources conservation and green house emissions. Livestock production in Latin America has been linked to forest conversion (Nicholson et al, 2001). Where access to new land is constrained, increased production requires increased application of agrochemicals, and there may be adverse impacts on the environment (increased residues, land degradation and loss of soil fertility).

Additionally, the competitiveness of global markets may encourage more widespread adoption of GMOs, insofar as these give higher yields and profits. Some varieties of GMOs, especially herbicide tolerant varieties, raise environmental concerns related to monocropping, geneflow to wild relatives, increased use of some agrochemicals, spillover effects on insect and wildlife and resistance to herbicides in crop and wild species (Toulmin, 2001). Other GMOs, such as Bt varieties, may discourage monocropping and reduce agro chemical use. The issue for environmental impact is not whether GMO but which type of GMO (consumer preferences are a separate issue that can, in principle, be addressed through proper labelling).

In some cases there could be environmental benefits, if for example higher incomes encourage better land and water management practices. For example, higher beef prices may help to preserve the pampas in Argentina. The growing demand for organic products and the existence of price premium in some cases may encourage their production. Most frequent environmental benefits associated to organic production are improvements in soil and water quality.

In practice, much will depend on the particular products that are affected, and we provide a more detailed consideration of environmental impacts when discussing individual products.

Table 6 summarises the expected impacts for major exporting developing countries.

Symbols used in the SIA Summary Impact Tables

blank nonsignificant impact

r,p positive lesser/greater impact (i.e. effect is beneficial, such as an increase in exports or a reduction in poverty)

s,q negative lesser/greater impact (i.e. effect is adverse, such as an increase in inequality or reduction in employment)

± positive and negative according to context – net effect is uncertain as there is no basis on which to ‘balance’ positive and negative effects

s/r negative over an initial period of time but expected to become positive in the longer term – similar combinations of symbols are used for other short term/long term effects (using 0 for nonsignificant impact)

L, M, H Low, Medium or High


Table 6: Summary of sustainability impacts for MEDCs

Dimension Core indicator

Impacts (issues, examples)

Direction and

magnitude

(q,s

,0,r

,p)

Stress

(L,M,H)

Extent

(L,M,H)

Reversible (yes,

no)

Probability

(L,M,H)

Responsiveness

(L,M,H) Impact

significance (q,s, ,r,p)

Economic

Exports rise p(exports)

M (price volatilit y)

H (many products) no H H p

Real income

(production)

Imports increase s(imports)

L (few products) no L L s/0

Mauritius case (sugar exports fall)

q(sugar, Mauritiu s)

L (Sugar Protoco l)

H (major sector) no H H q

Consumers Import prices (fall as tariffs reduced) r L L no L M r

Employment Net effect r

M (high unempl oyment )

L (no large increases in numbers)

no M M r

Social

Poverty

Employment of poor

r in general (s Mauritiu s)

H (high poverty in most countri es)

L (low numbers) M M r

Consumption

Real incomes of poor

r in general (s Mauritiu s)

H L (small effects) L M r/0

Equity Income inequality

r (lower inequalit y)

H (major issue)

L (small effects) M M r

Environmental

Environment al quality Chemical use

s (more chemical s)

L L M M s

Natural resources Water

s (more water used)

L L L M s/0

Land use (deforestation)

s (loss of forests)

H

L (for most countries )

H M s (in general)

q (forestry)


Dimension Core indicator

Impacts (issues, examples)

Direction and

magnitude

(q,s

,0,r

,p)

Stress

(L,M,H)

Extent

(L,M,H)

Reversible (yes,

no)

Probability

(L,M,H)

Responsiveness

(L,M,H) Impact


Institutional

Sustainable development principles

Are SD policies a priority?

r(encoura gepriority)

L (not given high priority)

L (given past record)

L r/0

Institutional capacities To address social and

environmental concerns

r(encoura geaction)

L (good capacit y)

L (not given high priority)

M (instituti ons exist)

M r/0

Example: Brazil Case Study Brazil is one of the world’s largest agricultural producers, with some 50mn ha under crops in the mid1990s, and a further 178mn ha in pastures. Given the size of the country, Brazil has many different climatic regions and produces a very wide range of crops and livestock, the major ones being beef, cassava, cotton, coffee, beans, maize, poultry, sugar, and soybeans. Agriculture accounts for some 10% of GDP, 20% of employment and 20% of export revenue. The principal export products are soybeans and soybean products, coffee, sugar, orange juice and meat. For most of these products, Brazil produces at costs that make its exports competitive with any in the world.

The farm sector is markedly varied by size of farm and capitalisation. Although the bulk of production comes from large farms and estates, there are still very many smallholders who rely on their farms for subsistence, above all in the North and Northeast (‘Nordeste’) of the country.

The effects of trade liberalisation were assessed by use of a social accounting matrix, tracking the effect of assumed changes in world prices for all the main products, through to the levels of output, prices, and incomes in the Brazilian economy (see the Brazilian case study by FIPE, in the Appendix).

Economic impacts:

The model predicts major increases in exports of soybeans, maize, sugar, rice products, and animal feed by 20% or more and substantial increases in beef, other vegetables, and other food products of 10% or more. But given that exports account for only a small part of total farm output, less than 3% in 1999, impacts on subsectors are lower. The largest would be seen for the sugar industry, up by 16%, and soybeans, up by 10%. The overall effect on the economy is positive, but limited. Real GDP would rise by 0.86%, real household incomes by 0.85%, and employment by 0.91%.

Social impacts:

Increases in household incomes are, unsurprisingly, larger for those households that farm than for others. They would rise by the largest margins for commercial farmers and their farm labourers, by 2.6% and 2.4%, respectively. These are the farms that produce most of the exports. Other rural households would see their incomes rise by 1.3% or more. Urban households, in contrast, would get income increases of less than 1%. Overall, income inequality within the country is marginally reduced, although within rural areas it may increase but fractionally. The changes expected would reduce the number of poor by 1.4%, or 160,000 persons; but by 2.3% in the Nordeste, the poorest region in the country.


Environmental impacts:

Increased farm production will be accompanied by increased pollutants, of chemicals and fertiliser runoff. Demand for water would rise by 2.6%. Soil erosion might also increase; although much depends on the techniques used to increase production. A notable development concerns animal feeds, principal among them soybeans. A 10% increase in soybean production is forecast. Much of this might well occur through an expansion in the tilled area. If all the increase were an area expansion, another 1.8M ha, or 18,000 km 2 an area more than half the size of the Netherlands might be added. Newlyopened fields would be likely in Matto Grosso and Pará on the margins of the Amazon. Forest lands, and areas with unusually high biodiversity, would thus come under pressure. The extent of this depends heavily, however, on development of road, rail and river transport links in which some significant investments are currently being made by both government and private companies. The model also sees a rise in emission of carbon dioxide by 1.4%.

4.2. SIA – Highly Protected Developing Countries

Some developing countries, in particular those in South Asia, currently have relatively high tariffs on agriculture imports, intended to protect domestic producers (often processors rather than farmers specifically). This implies a potentially large fall in domestic prices. For example, an initial tariff of 80% would imply a 10% fall in domestic prices after tariff reductions of 24%. This would encourage an increase in imports – the price elasticity of demand for imports in India is estimated as being in the region (minus) 0.30.5. Thus, a ten per cent fall in prices would suggest that imports increase by 35%. The combined components of liberalisation will increase world prices, but in most cases by less than four per cent. Thus, for countries with high tariffs, there is likely to be a net effect of domestic prices falling by at least five per cent, and imports will increase.

Just because countries have high tariffs does not mean that they are importers, or that they would be if tariffs were reduced. South Asian countries such as India are typically exporters of rice, and possibly of other grains (Box 4,3 gives the example of wheat). On the other hand, because protection is high, liberalisation could have significant impacts for particular products. For example, edible oils are a major import for India although tariffs are high. A more specific example is groundnuts, which is important for some producers even if not a major crop. Diop et al (2004) analyse the trade and welfare effects of groundnut trade liberalisation scenarios. Under free trade, African exporters would gain because they are net sellers of groundnut products. In India, consumers would be better off with lower consumer prices resulting from the removal of prohibitive tariffs and large imports of groundnut products. The cost of adjustment would fall on Indian farmers and crushers.


Box 4.3: The economic impacts of wheat policy reform on relatively protected developing countries: The case of India

Following independence, India has followed a policy of selfsufficiency based on increasing wheat production by improving crop yields through the planting of highyield varieties, adopting multiple cropping cycles and extending irrigation. In addition, the public sector subsidised fertiliser, electricity and irrigation water to increase yields. India also established a system of minimum support prices for wheat (US$138.5/tonne in 2003/04). Subsequently, India has witnessed dramatic increases in wheat production: growing on average by 3.5% per annum over the past three decades.

Trade restrictions on India’s imports of agricultural products have been gradually liberalised since 1991. Large wheat crops since 1999 have led to large accumulations of public stocks which eventually necessitated wheat exports, making India a net wheat exporter since 2000. In order to compete with other Asian exports, India adopted a policy of export subsidies for wheat. Exports peaked at 6 million tonnes in 2002/03 but wheat exports were halted in 2003 as stocks diminished following a poor harvest in 2003/04.

Source: Mitchell and Mielke (2004).

Obviously, the effects vary by product and country, but the general picture is one where domestic prices will fall and imports of some products will increase. There may be gains for certain exporters (e.g. of rice or sugar), but these are unlikely to offset the costs from cheaper imports. This is so because the gains in global market access are shared amongst all exporting countries, whereas the impact of increased imports (because initial tariffs are high) is borne by domestic producers. For these countries the net impact on producers is likely to be adverse, the less so the potential to expand exports.

Economic Impacts: The general effect will be a reduction in domestic prices; this imposes a loss on domestic producers and processors, but benefits consumers. Standard economic analysis would suggest that the net welfare impact is positive, especially if there are some export sectors gaining. However, this does not mean that the net economic impacts will be positive – adjustment costs are real whereas welfare gains are to some extent notional. The economic impact will depend on the ability of the economy to adjust, and particular what happens in the agriculture sector. This is incorporated into the scenarios as the implication is to liberalise in stages, reducing adjustment costs and providing time for adjustments to occur. The process of adjustment and how it is managed can only be analysed at a country level, and these issues are considered in the Indian case study. As the SIA is concerned to identify long run impacts, adjustment can be assumed. For these countries as a group, although detailed impacts depend on the product pattern of trade, we anticipate in general increased exports and reduced domestic production (or at least greater competitive pressure on domestic producers).

Social Impacts. For the types of countries and products considered here, smallholder farming is usually significant and these are mostly countries with very large rural populations (that is one reason why tariffs are initially high). As the costs of adjustment fall predominantly on producers, they will fall predominantly on rural areas. As small (semi) subsistence producers tend to be less competitive, they are likely to lose domestic market share to imports, whereas commercial producers are the most likely to be able to respond to increased competition. Some losses among domestic producers are likely, although there is no strong reason too believe that adverse effects will be more severe for smallholders (who often display remarkable resilience) than for larger, more commercial farms. The benefits of lower prices accrue to consumers: in rural areas this offsets losses, but in urban areas it suggests net benefits. This implies an increase in ruralurban inequality. Overall, however, the changes are


incomeequalising: the poor are net buyers of food in both rural and urban areas. The losers in this are farms producing surpluses, and the bulk of the surplus comes from the betteroff farmers (even if they are not large farmers).

A particular concern relates to gender issues. In some EastAsian countries women carry a heavy burden in the agricultural sector, as agriculture is in many cases the main source of women employment. However, because of distribution realities in these countries women are in the lowest segment of society, have restricted access to and control over land, access to capital, credit, poor educational levels as well as less mobility. All of these limit ability to respond to increased competition from international markets and to adequately improve productivity in an increasingly competitive domestic market. As such any change in agricultural patterns in these countries is likely to affect more women than men (Kanji and Barrientos, 2002). As the net effect of liberalisation is likely to benefit the poor, women as a group may benefit more than men.

On the other hand, Maltais et al (2002) note that both poverty reduction and agricultural growth have stagnated after the 1991 reforms in India, leading to concerns about future agricultural liberalisation via the WTO in terms of shortterm food security for the rural and urban poor. Moreover, the difficulties for smallfarmers and especially women imply distributional problems and increased ruralurban inequality. Overall, adverse social impacts are likely.

Environmental Impacts: most common environmental impacts associated with crop production are soil erosion, water pollution and sometimes inappropriate pesticide application, with consequences both for human health and for the surrounding environment.

In the context of highly protected producers, the general effect is one of substitution of suppliers –especially small farmers, as imports displace domestic production. But the impact on environmental pressure will depend on whether national production rises or decreases. Moreover if, in the case of specific products or countries, smallholder production methods tend to be more environment friendly than commercial techniques, then an additional marginal adverse impact is likely.

Table 7 summarises the expected impacts for developing countries with a protected agriculture sector. Economic stress is medium if the domestic sector is weak or faces volatile prices. Reversibility is considered possible (yes) if the actual changes in tariffs could offset (reverse) a world price effect. Social stress is considered high if poverty or inequality are pervasive.


Table 7: Summary of sustainability impacts for HPDCs

Dimension, Core indicator


Direction and

magnitude

(q,s

,0,r

,p)

CurrentStress

(L,M,H)

Extent

(L,M,H)

Reversibility

(yes, no)

Probability of

occurrence

(L,M,H)

Responsiveness

(L,M,H) Impact


Economic

Exports rise (e.g. rice, sugar)

p(exports rise)

M (volatile prices)

M (many products) no H M p

Real income

(production)

Imports increase (e.g. oilseeds, groundnuts)

q(imports rise)

M (weak sectors)

M (many products)

Yes

(tariffs) M M q

Consumers Import prices fall (e.g. groundnuts, oils)

Food prices fall or stable (e.g. rice)

r (lower prices)

M (many poor) M

Yes

(tariffs) M M r

Employment Net effect

0/r (small gain)

H L yes L L 0/r

Social

Poverty Employment of poor

r/0 (small gain)

H (many rural poor)

L L L 0/r

Consumption Real incomes of poor

r (lower food prices)

H (poverty) M L L 0/r

Equity Income inequality

0/r (poor gain)

H L L L 0/r

Environmental

Environmental quality

± (very mixed) M L L L 0/±

Natural resources Water ± (water

use) M L L L 0/±

Land use (degradation)

s (soil degradati on)

H L L L s/0

Institutional



r(encoura gepriority)

M (not a domestic priority)

L L L 0

Institutional capacities

To address social and environmental concerns

H (low capacity) L L 0


Example: India Case Study The agricultural sector plays a crucial role in India accounting for over a quarter of GDP. Three quarters of the population is rural and 70 percent of rural households depend on agriculture for their livelihoods. Agriculture accounts for around 60% of total employment. Though India has become self reliant in terms of meeting its foodgrains requirements, output in the agricultural sector fluctuates. Products such as rice, wheat, cotton and sugar are the lifeline of the majority of rural people while products such as cotton and sugar provide employment to a significant proportion of urban population as well (see India case study by CUTS, in Appendix).

Agriculture is the most dominant landusing activity. There has been an aggressive thrust towards commercial farming, especially to feed an insatiable export market. Cash cropping, already a threat to the smallscale biodiverse farm, has been given a major boost. New trends include floriculture, industrial aquaculture, and other forms of intensive farming, which leave little scope for biologically diverse production systems. Soil erosion is a serious cause of concern.

Economic impact of the Doha scenario

The net economic impact of future trade liberalisation of world agricultural trade is likely to be beneficial for India. However, the effects will depend on the type of product, and some sectors could suffer, such as oilseeds and cotton. It is expected that India would emerge as one of the important net rice exporters if further trade liberalisation takes place in the rice sector, while the richer countries such as Japan, Korea and the EU would be net importers. India will be one of the major beneficiaries of a liberalised sugar market. The possible elimination of cotton subsidies might help Indian cotton farmers, but the cotton sector is currently in distress (so ability to respond is constrained).

Social impact of the Doha scenario

Overall, the social impact of trade liberalisation is likely to be a mixed one. On the one hand, past benefits of liberalisation seem to have favoured large farmers more than the small ones. The regional disparity has also increased in the 1990s. There are possibilities that it may lead to a further widening of gap between small and big farmers and developed and underdeveloped regions. This may occur because of a rise in cost of production because of mechanisation, which Indian small farmers cannot afford. The backward regions like Bihar, Assam and Uttar Pradesh may suffer because of insufficient investment in agricultural sector. On the other hand, rice trade liberalisation has the potential to have a significant impact on poverty, followed closely by sugarcane, cotton and wheat. Except wheat, all crops have high average labour use (mandays per ha) in production. There is a positive linkage between rice prices and wages in India. Trade liberalisation in rice can bring social benefits to India, as the larger share of rice production comes from regions, which are extremely poor such as Uttar Pradesh, Bihar, West Bengal, Orissa, Andhra Pradesh etc. Crop diversification resulting from the trade liberalisation could also lead to positive impacts on employment generation and poverty eradication.

Environmental impact of the Doha scenario

Agricultural trade liberalisation can bring both opportunities and risks for the environment in India. The sudden increase in demand through the opening up of world agricultural market may force Indian farmers resort to excessive use of chemical fertilisers, pesticides, and insecticides for increasing production


through high yields. This may result in further degradation of environment. The continuing loss of topsoil as a result of land degradation is likely to cause adverse impact on farm production. However, the opening up of the international trade under WTO might lead to further organic farming. The European and US green markets provide scope for Indian exporters. Over 40% of Indian agricultural lands have remained untouched by any kind of chemical fertilizer or pesticide during the last 35 years of green revolution. India thus has large areas that are genuinely free of chemical pollution and are ideally suited for use of organic farming.

4.3. SIA – Least Developed Countries

Global models predict minimal gains or even losses for LDCs, as discussed above. Typically, LDCs export cash crops that are largely unaffected by reductions in domestic and export support by developed countries. The major exceptions are cotton, as West African LDCs are producers, and to a lesser extent sugar (this is not a major export for most LDCs): sugar exporters lose (as preferences are eroded) whereas cotton exporters tend to gain (as global market distortions are reduced). For the majority of LDC exporters, global tariff reductions imply a reduction in their margins of preferences. However, tariffs tend to be low for the majority of (unprocessed) cash crops they export, so this is unlikely to have a significant impact. In other words, the liberalisation scenario is unlikely to have a significant direct effect on LDC exports except for those for which sugar or cotton are significant exports. As many LDCs are net food importers, they suffer an initial welfare loss from higher world prices (this is the consumer loss identified in the studies reviewed in Section 3). However, in most LDCs these imports are ‘exotic’ staples, such as wheat and high quality rice, consumed predominantly by the urban nonpoor (for Uganda, see Morrissey et al, 2005). This does not mean that import prices are not important for consumers, but it does mean there is a very limited impact on the poor (especially the rural poor). As their prices rise, there is more scope for substitution by domestic staples tubers, maize, small grains (including lower quality rice). As there are only small export effects, the net impact will be determined by the ability of domestic producers to respond to increased import prices.

Economic Impacts: The global studies of economic impacts reviewed above tend to predict net welfare losses for LDCs. These arise for three reasons – negligible positive impacts on world prices of the products most export, increases in the prices of the products they import (not offset by domestic tariff reductions), and severe constraints in the ability of local producers to respond to increased production incentives (higher import prices). Consumer (food) prices are likely to increase, with few if any producer gains (the main exception being for cotton exporting countries). One sector that may deliver gains is in vegetables and fruits, as these are nontraditional export markets of increasing importance. Although producers are typically commercial, there is evidence that the employment impact of horticulture is positive, in the sense that relatively poor workers benefit (Humphrey et al, 2004). Global tariff liberalisation reduces the margin of preference granted to exporters of horticulture products, so there is no reason to believe that LDCs will be able to benefit significantly from increased world prices. Furthermore, relatively few LDCs have penetrated the market for vegetables and fruits, and those that have export very small volumes (Tanzania is one of the few to be reasonably successful). Although erosion of preferences is an important issue for LDCs, and ACP countries more generally (see Mold, 2005), the principal issues either do not relate to agriculture or are not part of the agriculture liberalisation scenario (e.g. reform of EUACP relations).

The increase in food import prices offers an incentive to domestic producers, although their ability to respond to this is constrained (McKay et al, 1997). The estimated world price


effects (e.g. Table 4a above) understate the effect on LDCs as their concern is regarding dumping of subsidised food. The world price refers to the supply price from the (competitive) global market. Export subsidies, as in OECD countries, cause downward pressure on this world price, but the subsidised exports are sold at a price below the world price. From the perspective of an importing country, the price of subsidised imports is below the (market) world price. Even if domestic producers could compete at the world price, the conventional definition of competitiveness, they may not be able to compete with subsidised imports (unfair competition). Liberalisation (in particular of export subsidies) will mean that the actual import price to LDCs (and other developing countries) increases by more than the change in the world price (because the subsidised imports are removed and the global market is more competitive). Thus, there is likely to be a significant price incentive to domestic producers. There is considerable evidence that farmers in lowincome countries do respond to changes in prices, especially changes in relative prices. In Tanzania, as the price for food crops increased relative to the price for cash crops, food production increased significantly; the longrun (relative) price elasticity is almost unity (McKay et al, 1999). Similarly, studies of farm households in Ethiopia reveal high responses to relative prices, although nonprice factors (especially access to inputs such as fertiliser, access to land and infrastructure and marketing) are more important than prices in determining how much of which crops is produced for market (see Abrar et al, 2004). Thus, domestic producers will respond to increased prices of imports, but there are measures that should be taken to enhance the response. As producers tend to respond to relative price changes, one would expect a shift away from cash crops towards food crops. This would be generally beneficial for the production sector: dependence on cash crop exports can be a problem, the liberalisation scenario implies few effects on tropical cash crops (except cotton and sugar), while multilateral liberalisation reduces the margin of preference available to LDCs (although this would have a negligible if any impact on exports of cash crops). In the summary of impacts (Table 8a) we recognise the problem of export dependence on unprocessed cash crops (high stress in the sector), but classify the extent of the impact as low because the scenario has no direct effects for these crops (cotton and sugar are treated separately, but here the extent is low overall because few countries are affected, although the impact is significant in those countries).

The overall effects are that domestic production of food crops will increase, to an extent depending on the supply response capacity. Although initial increases in import prices will impose a cost on (urban) consumers, in the longrun domestic production increases will permit lower prices, benefiting rural and urban consumers. Export cash crop production will tend to fall, either because of preference erosion or because farmers substitute into food crops. The major exception is cotton.

Social Impacts. The initial effect of higher import prices is that consumers lose whereas few producers gain (at least in the shortrun). For a typical country, such as Uganda, imported food prices rise with an adverse impact on consumers, especially in urban areas. However, these consumers tend to be nonpoor, and the poor rarely consume imported (commercial) food. Analysis of household surveys shows that the types of foods consumed by poor and nonpoor households differ (Morrissey et al, 2005). Thus the distribution of consumption effects is biased against the nonpoor. However, domestic food producers have an incentive to increase production and if they do so this will ultimately increase supply and lower prices for domestic staples. If this happens the social impact is positive – reducing ruralurban inequality and benefiting poor consumers and producers (of staples) more than richer consumers and producers. Overall, gains are likely to exceed (nonpoor) consumer losses. There are potential gains to the poor employed in horticulture production and processing. However, the ‘valuechain’ nature of such production (Nadvi, 2004) suggests that the economic benefit of access to the global market is to some extent offset for producers in LDCs as being the ‘weakest’ link in the chain, and as observed above LDCs are not strongly integrated in the chain.


In general, for domestic food production and any affected exports, an increase in overall production leads to increased rural employment, which tends to benefit the poor, and ultimately lower domestic food prices, which also benefit the poor. This suggests a social benefit. Box 4.4 provides the specific example of cotton, which offers significant social benefits for LDC producers. For most LDCs, where we may observe a shift from cash crops (grown for export) to food crops (and an increase in the share of food crops marketed rather than used for own consumption), there should be a slightly positive social impact. One would expect a benefit for producers (otherwise there is no incentive to substitute) and for consumers (as cheaper local food becomes available). If domestic production responds, the increase in prices of imported food will be a transitory (adjustment) cost.

Gender issues are important in most LDCs, especially in Africa. Women’s work in agriculture is extremely important but they are disproportionately represented among the rural poor and they tend to have fewer assets than men in terms of access to and control over land, access to capital, educational levels as well as less mobility. Insofar as the impact of trade liberalisation benefits domestic food production, women and smallholders will benefit, reducing social inequality.

Box 4.4: The social impacts of developed country cotton subsidies on Least Developed Countries

Empirical estimates confirm that the removal of cotton subsidies, particularly in the US and EU, would have significant benefits for Least Developed Countries for which cotton production is an important component of export earnings and GDP. Higher world prices resulting from subsidy removal would translate into both higher production and higher incomes for smallholder producers.

In low income economies where the majority of poor people live in rural areas, an increase in income from export cash crop production is widely recognised as being one of the best shortterm measures to reduce poverty. For example, Booth and Kweka (2004) blame the poor performance of Tanzania’s main cash crop sectors (including cotton) as one of the main reasons why rural poverty did not fall in Tanzania during the 1990s, despite sustained per capita GDP growth.

The large impact of increased income from export cash crop production on rural poverty occurs firstly because the benefits tend to be widely distributed within the rural population. There are over two million households (comprising over 10 million people) in West and Central Africa directly involved in cotton production (Oxfam, 2002) and an additional one million smallholder cotton producers in Southern and Eastern Africa (Poulton et al., 2004). Cotton production in African countries is often concentrated in the poorest regions (Deininger and Okidi, 2003) with the majority of households within these areas directly engaged its cultivation. For example, in a survey of Kwimba and Bariadi districts in Tanzania, 221 out of 301 households (73%) were found to have cultivated cotton during the 2001/02 season, whilst a further 51 households had ceased cultivation since 1999 due to low seed cotton prices (Poulton et al., 2004). Similarly, in a study in Montepuez and Monapo in Mozambique, 472 out of 663 households (71%) were found to have cultivated cotton (Govereh and Nyoro, 1999).

A second reason for the large impact of increased income from export cash crop production on rural poverty is that the consumption patterns of smallholder producers mean that much of any additional income is spent on locally produced goods and services. This generates large multiplier effects that benefit other poor households (Bautista and Thomas, 1999; Badiane and Ghura, 2002).

A third reason is that cotton is a labour intensive crop. Additional casual employment is generated as production increases in response to higher prices. In a 2002 survey of Tanzania, most cotton producing households were found to hire labour (for an average of 31 days) to assist with cultivation and harvesting of the crop (Poulton et al., 2004).


Environmental Impacts: Most impacts at the product level are quite marginal, i.e. changes in prices, and therefore in production intensity incentives, are quite small. The final environmental impact will depend on the combination of environmental effects associated to changes in production of different products affected. Cane sugar, whose production is likely to decrease, requires agrochemical (that runoff and pollute water and coastal ecosystems) and significant demands on water (in areas where often water is increasingly scarce). Cotton, whose production is likely to increase, has the greatest water requirement of all major crops (Clay, 2004) especially in regions where water is increasingly scarce, and usually involves pesticide application, with consequences for both human health and the surrounding environment. However, as evident in West Africa, cotton can be successful grown in relatively arid regions. As observed above, the sector where production increases are most likely are domestic foods (where chemical input use is often very low, see e.g. Abrar et al, 2004) and to a lesser extent in horticulture. Increased production of fruits and vegetables tends to require higher use of agrochemicals and water, raising issues related to water contamination and availability, but these effects are unlikely to be large or widespread. These potential adverse effects are likely to be offset by the slight reduction in cash crop production. This suggests a positive environmental impact, or at least that the overall impact is not significantly negative.

Table 8 summarises the expected impacts for least developed countries. The impact of increased import prices on consumers is considered reversible because countries could reduce tariffs, although they are not required to do so. Under the ‘responsiveness’ column, two issues are included. First, the responsiveness of producers to altered incentives which incorporates the support available through policy on agriculture; while farmers are responsive, policy support is often lacking. The second issue extends on this, as most LDCs are currently operating Poverty Reduction Strategy papers (PRSPs), and some are beginning to include trade issues in the poverty reduction strategy. This enhances the responsiveness. To the extent that multilateral liberalisation encourages countries to incorporate environmental and trade issues into their policy strategies, such as PRSPs, this contributes to process indicators (captured in the final two rows of the tables).


Table 8: Summary of sustainability impacts for LDCs



Direction and

magnitude

(q,s

,0,r

,p)

CurrentStress

(L,M,H)

Extent

(L,M,H)

Reversibility

(yes, no)

Probability of

occurrence

(L,M,H)

Responsiveness

(L,M,H) Impact


Economic

Exports rise (e.g. cotton)

r(cotton)

H (distort edmarket)

L (H for West Africa)

no H H r

Real income

(production)

Higher domestic food production (higher import prices)

p(domesti c food)

M (dumpi ng)

H (all countri es)

Yes (tariffs) H

M (depends on policy for agricultu re)

p

Exports fall (loss of preferences or crop substitution)

s(exports)

H (price volatilit y)

L (few product s)

L M s/0

Consumers

Import prices rise s(imports)

L (non poor)

L (urban non poor)

Yes M M s/0

Domestic food prices fall (long run)

p(domesti c food)

H (many poor)

H (rural and urban)

partial M M p

Employment Net effect p (net) H H M L r

Social

Poverty Employment of poor p

H (povert y)

L no M M (trade in PRSP) r

Consumption Real incomes of poor p H H (food) H M r

Equity Income inequality r(reduced) H M M M r

Environmental

Environmental quality Agrichemicals

r/0 (low use, food crops)

L M L L r/0

Natural resources Water s

(cotton) H L M L s

Land use (soil degradation)

r/0 (lower for foods)

M M L L r/0




Direction and

magnitude

(q,s

,0,r

,p)

CurrentStress

(L,M,H)

Extent

(L,M,H)

Reversibility

(yes, no)

Probability of

occurrence

(L,M,H)

Responsiveness

(L,M,H) Impact


Institutional

Sustainable development principles Are SD policies a

priority?

r(encoura ge)

M

L (few have SD policies )

L L (not in trade policy)

r (SD in PRSPs)


Social, environmental concerns 0 H L L (weak) r (Trade in

PRSPs)

Example: Tanzania Case Study

The Tanzania case study was undertaken by the Department of Agricultural Economics and Agribusiness, Sokoine University of Agriculture (see Appendix). More than 80% of Tanzanians live in rural areas: most of them are engaged in agriculture as their main occupation. Farming contributes more than 50% of GDP, while agricultural exports represented one third of the value of exports in 2003. Most of the land is cultivated in small parcels by households using at most rudimentary tools and few purchased inputs. Large scale commercial farming and ranching operations are few and far between. Tanzania is a large country with much variation in its geography so that it can produce a wide range of crops and animal products. Because of the size of the country and relatively sparse road and rail networks, transport costs are high.

Since Tanzania liberalised its economy, starting in the 1980s and with increased vigour in the 1990s, there have been several studies of the impact of overall, and specific trade, liberalisation on agriculture and on particular farm enterprises. By and large these show some favourable impacts in that farmers have usually seen both their share of the world price, and the absolute price for their produce rise. In most cases, farmers have responded by increasing their production. Their ability to do this, however, has been limited by rising costs of inputs, plus limited supply of these in the more remote areas where private dealers are reluctant to operate, decreased availability of formal credit, privatisation of previously free government services, and in some cases the imposition of new taxes and levies on profitable crops. Inability to meet international standards for hygiene and quality has prohibited exports of beef and impeded those of green vegetables. It is thus a working hypothesis that obstacles in the supply chain may play a greater role in affecting farmer decisions than price levels in the national market.

As a leastdeveloped country, Tanzania is largely exempt from the provisions of the Agreement on Agriculture (AoA). In any case, even if it were not an LDC, export subsidies do not exist, and domestic support to agriculture is minimal so that obligations would apply only to tariffs on imports. Hence in this, the analysis consists of examining the effects of assumed increases in the world prices of key products produced and consumed in Tanzania,


consequent on the rest of the world complying with the provisions of the AoA.

Economic impact of the Doha scenario The overall pattern is that increased prices will transmit to growers by more than the world price rise, perhaps as much as twice the change in the world market price. That will encourage increased production by an amount equivalent to the price rise, given a longrun supply elasticity of unity for most products. In some cases, however, failings in the supply of inputs, finance and marketing may limit producer response. But we can expect farmers and farm labourers to gain.


Price rises in wheat and rice will affect mostly urban middle classes, rather than the poor who are more likely to consume cheaper, domestically produced staple foods such as maize. Social conflicts between herders and cultivators may be exacerbated where the incentives are to expand production by increasing the land area used. This applies throughout much of lowland Tanzania, above all in the north of the country, where pastoralists and crop farmers live sidebyside using different parts of the ecosystem.

Environmental impact of the Doha scenario.

The environment could suffer from removal of trees and bush to create new crop fields, and from increased use of crop chemicals that potentially pollute watercourses and reduce biodiversity by poisoning some plant and animal species. The former is the more serious threat, but even this should not be exaggerated. Tanzania has considerable areas of unfarmed land, and even some of the cultivated land is in fallow cycles that allows the regeneration of local ecosystems. All this said, much depends on the ability of those in the supply chain from farmers grouped in associations to traders to processors and multinational corporations to resolve the current problems of inputs and finance; and on complementary measures by government, through investments in roads and other physical infrastructure, and public measures to remedy market failures. The more success there is in these two fields, the more likely the trade liberalisation effects are to be benign and significant.

4.4. SIA – Lowincome Developing Countries

In respect of the general pattern on impacts, and the underlying structure of agriculture (for all three impact dimensions), LIDCs are very similar to LDCs, and the general discussion for LDCs applies. The significant difference, in our context, is that LIDCs are required to reduce domestic tariffs (being defined as developing countries) whereas LDCs are not. A priori, this allows them to in effect offset the domestic impact of increased world prices for food imports. Typically, applied tariffs on food are in the region of 20%, implying that the required liberalisation will reduce domestic prices by about four per cent. This implies that tariff reductions will tend to offset world price increases for most food imports. To some extent, the price incentive to domestic producers in LIDCs will be dampened. As observed for LDCs, the concern of domestic producers is with dumping of food; this should be eliminated (and implies that in general import prices will increase up to the world price, whereas previously they were below it). If the initial situation is one of dumping, the import price will have been below the world price (i.e. the price that models use to estimate world price effects), so the actual increase in import prices will exceed the estimated increase in the world price. Tariff reductions may then be insufficient to reduce consumer prices. In principle, one would want


to distinguish those products (or countries) where domestic response is likely (i.e. there is competing domestic production capacity) from cases where it is unlikely (e.g. small islands that have very limited capacity to meet their food needs). In the former case, one would want price incentives to be transmitted to local producers whereas in the latter case one may desire tariff reductions to prevent consumer prices from increasing (this argument applies equally to LDCs). We acknowledge this issue in the impact summary.

A second potential benefit is that the margin of preference available to LDCs with respect to LIDCs will be reduced, implying a marginal benefit in those products where LIDCs compete with LDCs. This is unlikely to apply to a wide range of cash crops, as existing preference margins may be low, but could be important for horticulture (although few LDCs have significant exports). In general, the effect will be small. The erosion of preferences for LIDCs that are ACP countries, with respect to nonACP developing countries may be a more important concern (see Mold, 2005), but EUACP reforms are not part of the agriculture liberalisation scenario. The case of sugar highlights the issues (Box 4.5). In general, ACP countries benefiting from the Sugar Protocol will suffer losses (unless compensated in some way), whereas nonACP sugar exporters benefit (Milner et al, 2005). In practice, for ACP sugar exporters, it is difficult to separate the effects due to WTO liberalisation from those due to reform of the Sugar Protocol.

Box 4.5: The economic impacts of sugar policy reform on lowincome developing countries: An example of preference erosion

An exporting country experiences preference erosion when an importing country removes tariff preferences, expands the number of exporting countries eligible to benefit from preferential access to its market or reduces its mostfavoured nation (MFN) tariff to thirdcountry exporters without maintaining margins of preference (by reducing preferential tariffs).

The arguments on the effects of tariff preferences can be briefly summarised as follows. Positively, tariff preferences offer terms of trade gains to developing countries which can result in increased exports for the favoured sector or higher investment (through the associated income transfers) and diversification into new sectors (Subramanian and Roy, 2002). Negatively, tariff preferences can encourage the expansion of sectors in which the country’s long term competitiveness is in decline (e.g. sugar production in the Caribbean ACP states) and create an incentive for developing countries which receive them to lobby against liberalisation in the preferencegiving country (Ozden and Reinhardt, 2002). There have also been criticisms that the use of tariff preferences has been limited by uncertainty, although most nonduty free African exports to the EU use some form of preference scheme (Stevens and Kennan, 2004).

The losses from preference erosion can be estimated for all or individual countries. For the former, general equilibrium models have suggested that the impacts for groups of developing countries are likely to be small (Ianchovichina et al., 2001; Hoekman et al. 2001). Although they predict the aggregate impact from preference erosion to be insignificant, partial equilibrium approaches which can be used to measure the impact on individual developing countries provide evidence that for those countries with high dependence on exports in heavily protected sectors, the loss from preference erosion can be large (see Gillson and Page, 2003). The highest margins of preferences, and therefore the highest income transfers, are for sugar, bananas and clothing (Alexandraki and Lankes, 2004) which are often dominant in the export structures of those countries predicted to lose the most from preference erosion.

For sugar, Borrell and Hubbard (2000) estimate that complete liberalisation of the EU sugar market would lead to a loss in income transfers for the ACP Sugar Protocol countries of US$400 million per year. The greatest losses are for those countries which export sugar only or predominantly to the EU and have the biggest preferential quotas (Mauritius, Guyana, Fiji and Barbados), see Milner et al (2005). The permanent nature of preference erosion shocks implies that economic adjustment and restructuring needs to be the focus of any response.


Economic Impacts: Overall economic impacts are likely to be more positive for LIDCs than for LDCs. Domestic food producers can benefit from elimination of dumping, whereas tariff reductions offset world price increases in cases where there is no domestic production capacity. Cash crop producers competing with LDCs stand to benefit as relative preference margins for LDCs fall, but this is a small effect. Consumer (food) prices are likely to decrease in the longrun as domestic production expands, whereas there are also some producer gains for cash crop exports. The vegetables and fruits sector, nontraditional export markets of increasing importance, should benefit.

Social Impacts. In the shortrun, some consumers (generally urban nonpoor) will face higher prices for imported food, although this may be offset by tariff reductions. If domestic food producers increase output, consumers benefit from lower prices and this benefits the poor, rural and urban (reducing consumption inequality). There are potential gains in terms of income and employment if there are increases in cash crops and horticulture. The employment impact of horticulture has a positive social impact, in the sense that relatively poor workers benefit (Humphrey et al, 2004), although the gains are partially offset by the ‘valuechain’ nature of such production, where contract security may be limited (Nadvi, 2004). There are social concerns regarding the “quality” of the employment and how benefits are distributed along the value chain, especially for those at the lowest end of the chain. Gender issues also matter given the high importance of women employment in agriculture in lowincome countries (see previous discussion on this). Overall the social impact, security and integrity of livelihood, is likely to be mildly positive.

Environmental Impacts: Most impacts at the product level are quite marginal and likely changes in production intensity are quite small. In addition to food, the sector where production increases are most likely is horticulture, fruit and vegetables. Increased production tends to require increased use of agrochemicals and water, which raise issues related to water use and pollution. The most common environmental concerns are soil erosion especially if crops are extended to marginal lands (which has happened during recent years in several African countries) and demands on water in water scarce areas (see Abrar et al, 2004).

Table 9 summarises the expected impacts for lowincome developing countries.


Table 9: Summary of sustainability impacts for LIDCs



Direction and

magnitude

(q,s

,0,r

,p)

CurrentStress

(L,M,H)

Extent

(L,M,H)

Reversibility

(yes, no)

Probabilityof

occurrence

(L,M,H)

Responsiveness

(L,M,H) Impact

significance (q,s,0,r,p)

Economic

Exports rise (e.g. horticulture)

r(horticult ure)

L (small sector)

L (few countri es)

no M M r Real income

(production)

Higher domestic food production (higher import prices)

p(domesti c food)

M (dumpi ng)

H (most countri es)

Yes (tariffs) H

M (depends on

policy for

agriculture)

p

Exports fall (loss of preferences or crop substitution)

s(exports)

M (price volatilit y)

L (few product s)

L M s/0

Consumers Import prices rise (no domestic capacity)

s(imports, nodomestic capacity)

L (few countri es)

L (few countri es)

Yes (tariffs)

L (few countries )

M s

Domestic food prices fall (long run)

p(domesti c food)

H (many poor)

H (rural and urban)

partial M M p

Employment Net effect p (net) H H M L r

Social

Poverty Employment of poor p

H (povert y)

L no M

M (trade in PRSP)

r

Consumption Real incomes of poor

p(domesti c food)

H H (food) H M r

No domestic capacity

s (food deficit country)

L L yes L L s

Equity Income inequality r(reduced) H M M M r

Environmental

Environmental quality Agrichemicals

r/0 (low use, food crops)

L M L L r/0




Direction and

magnitude

(q,s

,0,r

,p)

CurrentStress

(L,M,H)

Extent

(L,M,H)

Reversibility

(yes, no)

Probabilityof

occurrence

(L,M,H)

Responsiveness

(L,M,H) Impact

significance (q,s,0,r,p)

Natural resources Water

s(horticult ure)

H L M L s

Land use (soil degradation)

r/0 (lower for foods)

M M L L r/0

Institutional



r(encoura ge)

M L L L (not in trade policy)

r (SD in PRSPs)


Social, environmental concerns

0 H L L L (weak)

r (Trade in PRSPs)

Example: Ghana Case Study Just over 60% of Ghana’s population live in rural areas, where rural livelihoods are based on agriculture and forestry. Together these sectors produce around 36% of GDP, and around 10% of all exports by value. Poverty is also concentrated in the rural areas. Farming in Ghana differs markedly by ecological zone. In cleared areas of the forest belt of the South the main crops planted include the export crops of cocoa, oil palm, coffee, and some rubber; with maize, plantains, cassava and cocoyams grown for food. The forestsavannah transition zone tends to be planted to maize, beans, yams, cocoyam, some rice, with tobacco, cotton and tomatoes and other vegetables grown for cash. In the northern savannahs, being the predominant cash crops maize, rice, are grown, to the north maize, sorghum, millet, cowpeas, some yams are grown for food while cotton, groundnuts and some tobacco are grown for cash. Livestock production is low, poultry, sheep and goats being most typical: cattlekeeping on any scale is restricted to the northern savannahs. Most farming is carried out by smallholders: 95% of the farmland is estimated to be in small plots. Ghana has liberalised its markets, including agricultural trade, since the early 1990s. While other parts of the economy have responded to new market opportunities, the growth of farm output was disappointingly slow in the 1990s.

For the six commodities studied, Ghana produces no wheat, and only small quantities of beef, sugar, and green vegetables (see Ghana case study by the Crops Research Institute, Kumasi, in Appendix). Cotton production is modest, although apparently with capacity for expansion, while rice is widely grown although much less so than other grains or the main tubers. Tariffs on beef, green vegetables and rice are 20%, but for wheat, cotton and sugar they are 10%. Domestic support to agriculture in Ghana is low and well within WTO limits; export subsidies are not used. The main impacts expected from liberalising agricultural trade arise from the combined effects of increases in the world prices of commodities arising from changes in policies in the rest of the world, and a reduction in the (modest) tariffs on imports.


Economic impact of the Doha scenario

For all commodities in this case, the fall in prices caused by reducing tariffs by onefifth, is less than the effect of the estimated rise in the international price: hence border prices rise. In all cases this should lead to a fall in domestic consumption and by significant amounts for those goods that have a high elasticity of demand, such as wheat products. Domestic production of all commodities except for wheat should rise, and there may be some incentives to increase output of domestic food crops that can substitute for imported wheat and rice, such as yams and maize. Price response, however, may be limited by the difficulties that farmers have in accessing capital or undertaking marketing.


Socially the changes are on balance positive: the increased prices of food apply to those consumed mainly by the urban middle class for example, bread and pasta, rice, and even to some extent sugar, and not those consumed by the rural poor. The latter should gain from more demand for farm produce, and for their labour from the larger farmers. Regionally, the changes may provide stimulus for cotton and beef cattle from the north of the country, where poverty rates are higher and development in general lags behind the rest of the country. We may thus expect liberalisation to help reduce regional inequality.

Environmental impact of the Doha scenario

Attempts to respond to prices will put pressure on resources. In particular, increased production of rice, and sugar and vegetables is likely to take place in lowerlying wetlands that tend to have higherthanaverage biodiversity and may provide services of water regulation within local ecosystems. But these effects should not be exaggerated: farming of wetlands in Ghana does not involve wholesale drainage, the ecosystem being modified rather than transformed.

4.5. SIA – European Union

The combined impact of implementing the three pillars is likely to increase world prices (and market access) for a number of products. The largest price increases, about four per cent or higher, are likely for cereals, beef, dairy products and sugar, whereas moderate increases (2 4%) are likely for oilseeds.

Reduction in tariffs will reduce domestic prices, stimulate trade and increase welfare, while reduction in domestic support and export subsidies will increase world prices, reduce agriculture production with weak welfare effects. The main CGE studies estimate welfare gains for the EU from agricultural liberalisation mainly through tariff liberalisation in the order of 0.1% of GDP. Agriculture exports would increase by around 10%. But there are wide differences amongst EU countries and groups within countries. Imports will increase by a similar amount. More details and references to the modelling underlying the results can be found in the appendix of the Mid Term Report.

Economic Impacts: All of Europe gains from tariff liberalisation and most of Europe from reduction in support. The main CGE studies estimate significant welfare gains from agricultural liberalisation. Bouet et al. (2004a) find that welfare will increase by 0.1% using


their “Doha” scenario (the equivalent of around US8bn), with most of the gains coming from tariff liberalisation.

Consumers gain, in particular in the form of lower prices through tariff liberalisation, which more than offsets the producer losses through increased net imports in those products. Beghin and Aksoy (2003) review several commodity studies of liberalisation and find that EU producers of cotton (production falls by an estimated 70% in the EU15) and sugar would lose. On the other hand, consumer gains in Western Europe are $4.3 bn which more than offset the producer losses at $3.3 bn. Welfare effects through lower prices often found in CGE models will depend on whether lower tariffs are passed onto lower consumer prices. Many agriculture products are dominated by large importers in global value chains, and they may temporarily fail to pass on lower import prices.

Table 10: Agricultural Liberalization Effect on EU Income, US$ mn

Constant Returns to Scale

Increasing Returns to Scale

50% tariff liberalisation



50% reduction in OECD support

100% reduction in OECD support

Netherlands 139 768 1436 16 119 France 657 1661 3312 2746 4320 Germany 809 2307 4855 1110 1534 Rest of EU15 2815 5042 8651 4576 7069 CEECs 263 1702 4348 2 202 Source: Francois et al. (2003), Table 41

Some studies find that agricultural imports will rise faster than exports under the combined scenario (Francois et al. 2003), while others find the opposite (Bouet et al., 2004). But since the difference in percentage point in both studies in close to 1%, it is plausible to assume that the net trade balance is likely to remain constant. But there are differences according to EU country, product, and trading partner.

It is expected that in the combined scenario, trade within EU25 will decline through preference erosion effects after MFN liberalisation. Total export and total imports will increase (small by the world standards), because of increased trade with partners outside the EU25. It is expected that extraEU 25 imports of sugar, cereals, cattle and dairy will grow faster than exports. However, extraEU exports of processed foods and horticulture will increase (e.g. for Netherlands and France), faster than extraEU imports.

The effects on domestic production are the results of two forces. First, liberalisation elsewhere will increase EU export opportunities and production, and secondly, reduced protection will lead to increased competition, increased imports and reduced production. The net effects differ by country and product (except for cereals where initial protection is high and production in all countries loses). Table 11 illustrates the pattern of impacts across products for a number of countries. The largest production effect is for a decline in cereals in the EU15. France is expected to lose some production owing to increased competition within the EU market. The cattle and beef sector in the EU declines due to increased imports from NAFTA and South America. Production of dairy is also expected to decline although some studies assume it remains unaltered because it stays within quota. Produced foods will increase in those countries with good transport infrastructure (Netherlands) where agglomeration effects can be reaped. Horticulture production is also expected to increase in most of the EU. EU producers of cotton and sugar would lose. The effects from lost production on real incomes can be reversed if alternative production activities can be found


for the affected workers in the rural areas. Table 11 also shows that the CEEC new member states may benefit, possibly because they have not been subject to the EU protection regime for a prolonged period (i.e. the distortionary effects of the CAP are not embedded in production structures).

Table 11: Percent change in production due to combined scenario

Netherlands France Germany Rest of EU15 CEEC new member states

Cereals 19 10 12 12 2 Horticulture 1 4 4 4 2 Sugar 0 0 0 0 4 Intensive livestock

1 2 1 1 1

Cattle 2 8 5 8 0 Dairy 0 0 0 0 3 Other agriculture

0 2 0 0 6

Processed foods

8 3 3 1 1

Source: Francois et al. (2003), Table 46

Social Impacts. Reform on the CAP is likely to lead to less support and more direct payments, hence implying shifting the costs of the CAP from the consumers to taxpayers. Such a shift will have positive distributional impacts since poor people spend a larger share of their income buying food relative to higher income social groups, while they pay less taxes than the betteroff. Trade losses might be offset by gains in efficiency from improved resource allocations and lower consumer prices, and as a result welfare gains are expected on the consumer side which includes the poor. Due to reduction of domestic and export support budgetary expenditures are expected to fall, constituting an important gain. Lower government expenditure can be spent on health and education. However, this might be offset by slightly lower tax revenues due to tariff liberalisation (though this only partly true as while there is tariff liberalisation there is an increase in taxable imports).

Rural employment represents a small share of employment in many EU countries, the major exception being some of the new members such as Poland (although these are less adversely affected than the EU15). National wide employment effects are likely to be limited in the aggregate in several EU countries with little agricultural employment (e.g. Belgium or the UK; agricultural employment is decreasing for all countries) although countries such as Portugal, Greece, Poland, Latvia and Lithuania depend on agriculture for more than 10% of total employment. However, the losses will be concentrated in particular regions within countries. Employment effects can be concentrated in areas where severe production losses occur. Decreases on farm production will affect rural incomes in particular as there will be a reduction in employment of cotton, dairy and wheat farmers, somewhat decreasing the poverty headcount. This can be counteracted if jobless workers can be reemployed in alternative activities. Big farms with high average incomes are expected to be the main losers of subsidies, so that may actually help equity. Detailed studies would be required to identify where adverse effects will be concentrated and to identify policies to mitigate these effects (see Section 5.3 below).

Environmental Impacts: As economic effects are likely to be relatively small, no large overall environmental effects are expected. However, there can be effects at the farm level. The most likely effect of liberalisation is an extensified farming system, with much reduced


applications of fertilisers and crop protection chemicals. In addition, much would depend on the most likely development of policy further towards green payments that will encourage farmers to conserve the environment. The final result will depend on the environmental features associated to the resulting mix of products. Moreover diverse impacts are expected in different areas. On the one hand, crops are expected to decrease in all EU countries, which may reduce pressure on natural resources such as soil and water. Likewise reductions are expected in beef and cattle (linked to water pollution); cotton (linked to water and health issues), sugar (less pressure on water) and probably small shrinks in dairy products (water pollution, ammonia, GHG emissions and reduced biodiversity). On the other hand, environmental impacts associated with processed foods (water pollution) are likely to aggravate as production is predicted to increase. Moreover the EU agrifood sector is associated with important impacts outside the EU through its dependence on raw material from developing countries, see Brah and Schelleman (2000). On the whole, overall environmental pressure is expected to decrease as long as trade liberalisation is likely to reduce overall production. On the other hand, farmers fulfil a role in maintaining the (local) environment, and in areas where farms, especially small farms, go out of business this role may be undermined. This can be addressed through appropriate rural and regional policies (see Section 5.3 below).

Table 12 summarises the expected impacts of the combined scenario for the European Union.


Table 12: Summary of Sustainability Impacts for the EU


Impact (detailed indicators)

Direction and

magnitud e

(q,s, , r,p)

Degree of stress in existing conditions (L,M,H)

Extent (L,M,H)

Reversibility (yes, no)

Probability of

occurrence (L,M,H)

Effectiveness and capacity of policy and regulation (L,M,H)

Impact significance (q,s, , r, p)


Sugar, Dairy, Cotton and Cereals: Production

q M

Concentrated in rural areas, and in certain countries

(Spain, Greece for cotton), extent is low

in the aggregate

Yes, if decoupled subsidies target rural

areas

H H

s

Processed goods, Horticulture : Production

r L

Concentrated, e.g.

horticulture and processed goods in

Netherlands and France, extent is low

in the aggregate


areas

H H

r

Real consumer incomes through lower prices

p M

Everywhere, but mainly

through lower prices of

cereals, beef and dairy

M, depends on pass

through of tariffs onto consumer prices

H

r

Fixed capital formation Employment

Agricultural jobs q H

Concentrated in rural areas, and in specific countries (e.g. Spain, Greece for cotton), extent is low

in the aggregate, in e.g. Belgium or the UK, but slightly higher

in e.g. Portugal, Greece,

Poland, Latvia and Lithuania


areas

H H

q

Social Poverty

Poverty headcount r M

Concentrated in rural areas, and in certain countries

(Spain, Greece for cotton)

Yes, if losers can

be reemployed

M H

Blank

Health and education

Government expenditure through

reduction in subsidies

r M Throughout

Yes, through lower tax revenues

H H

s

Equity Equity in subsidies recipients: Large farms loose most subsidies

r L Rural areas

Yes, rich farmers may capture part

of decoupled subsidies

M H

r

Change in factor return s M Everywhere,

factors prices Yes,

depends on M H




Direction and

magnitud e

(q,s, , r,p)

Degree of stress in existing conditions (L,M,H)

Extent (L,M,H)

Reversibility (yes, no)

Probability of

occurrence (L,M,H)

Effectiveness and capacity of policy and regulation (L,M,H)

Impact significance (q,s, , r, p)

may change in most of country

wage opportunitie s for less skilled workers

Environmental Biodiversity Environmental quality

Less use of chemicals due to loss

of production

p H Rural areas No,

production declines

H H

p

More use of chemicals due to

competitive pressure to intensify production

s M Rural areas

Yes, farms can decide not to adopt

new production methods

M H

s


Less use of water due to loss in sugar (and wheat) production, but more in processed goods

p /s H Rural areas, e.g. Andalucia

No, production declines

H H

p

Institutional Sustainable development principles

Productivity /efficiency through increased competition

r M Rural areas

No, farmer would stay

more competitive

H H

r


Attention to plight of farmers

r L Rural areas No, M H r


4.6. SIA – Other Developed Countries

The combined impact of implementing the three pillars is likely to increase world prices (and market access) for a number of products. The largest price increases, about four per cent or higher, are likely for cereals, beef, dairy products and sugar, whereas moderate increases (2 4%) are likely for oilseeds.

Reduction in tariffs will reduce prices, stimulate trade and increase welfare, while reduction in domestic support and export subsidies will increase world prices, reduce agriculture production with weak welfare effects. This SIA focuses on the US, but the effects may differ between developed countries that do and do not support their agriculture, and between net food importers and net food exporters (Cairns group). The main CGE studies estimate welfare gains for the US from agricultural liberalisation mainly through tariff liberalisation in the order of 0.1% of GDP. Agriculture exports would increase by just 6%, while imports would remain stable (the combination of negative effects from a reduction in subsidies and positive effects from a reduction in tariffs). There will be differences amongst US regions. More details and references to the modelling underlying the results can be found in the appendix of the Mid Term Report.

Economic Impacts: Real incomes in the US will increase under all scenarios. Most of the benefits come from trade reform in the trade partners of the US. While aggregate production will remain largely stable under the combined liberalisation scenario, there are variations across US regions and products. Corn production is predicted to increase in all regions, but especially in the Lake, Corn Belt and Northern Plains regions. Soybean production is likely to fall in all regions. Changes in wheat production are small and vary from declines in Southern Plane to increases in Lake region. While dairy production falls in general, there will be increases in production in Northeast, Appalachia, Southeast, Southern Plains, Delta and Mountain regions. Beef production would increase in Northern Plain, Delta, Mountain, and Pacific regions and decrease in Northeast, Lake, Corn Belt and Appalachia regions. Poultry would increase marginally in most regions. Overall changes are mostly small, certainly compared to yeartoyear variations.

In the case of (short to mediumterm) rice in Japan, because of its initial high protection, consumers are expected to gain due to lower domestic prices, but producers will lose out. Liberalisation would transform the farming in Japan.

While the US, EFTA and the EU gain in welfare because they reduce their own distortions, the effects on the developed countries in the Cairns Group (Australia, New Zealand and Canada) are different as they gain because of significant export opportunities. For them, liberalisation according to the combined scenario is likely to lead to new export markets in other OECD countries, against higher international prices. Despite this, most CGE models find only limited welfare effects of around 0.5%. This is in part because specialisation in agriculture draws resources away from sectors characterised by increasing returns to scale. Australia seems a major gainer in crops such as cotton and wheat.

Social Impacts. Where there are economic benefits some social impacts in terms of income and labour are also expected to be positive, but less significant because they are dissipated. This is especially true in countries such as US and Australia where agriculture contributes with a small share of the GDP and employment. In the case of US, trade gains are expected to be modest and concentrated in few large farmers exporting to the world market. They might be concentrated in some farmers, especially commercial farmers exporting to the world market. The current trend towards increasing largescale commercial farms against smaller farmers is expected to continue. Maltais et al (2001) suggest that US intermediate size farms


households tend to be below the average income in the US while commercial farm households are well above the average. Rural resident farmers are also above the average.

While rural residents tend to rely entirely on nonfarm related income and so are less economically affected by liberalisation in the sector, intermediately sized farms that depend on farm income will be negatively affected due to a lack of competitiveness in relation to largescale commercial farms. Largescale commercial farms, on the other hand, are the main losers of subsidies reduction. Therefore, social impact in terms of change in incomes and inequality depends on the context of large farmers benefiting more than intermediate. Lower government expenditure can be spent on health and education. However, this might be offset by slightly lower tax revenues due to tariff liberalisation.

In rural Australia, on the other hand, many social assessments often examine specific social problems related to education, crime and culture, although these effects are not always directly linked with agriculture trade liberalisation. Aboriginal issues are often addressed, particularly in terms of land rights issues. Most significant linkages between trade, agriculture (food crops sector) and social issues in Australia have been established through environmental problems (see next section on environmental impacts). Uncertainty and vulnerability associated with threatened livelihoods and uncertain futures in the sector are often identified, along with conflicting values between rural and urban residents.

Van der Mensbrugghe and Beghin (2004) find that agricultural trade reform would lead to substantial losses in employment in the US, but strong employment increases in the Cairns developed countries. In all of these countries, unskilled wages rise more than the wages of skilled workers. Thus there might be important and positive equity effects in these countries.

Environmental Impacts: Because the effects of trade liberalisation on trade and production are small in the US, the overall environmental effects may also be small, although they mask increases in agricultural production and potential negative environmental impacts in some regions while decreases in other regions. In the US cropping increases in Northern Plains would increase pesticides loading to ground and surface waters there. Sheet and rill erosion is likely to increase in the Northern Plain and Northeast regions, while it is likely to decrease in the Southern Plains, South East and Pacific. Nitrogen loss to water from crop production is also expected to increase in Northern Plain, South East and Northeast regions, while decreasing in the Southern Plains, and Pacific. The Northern Plains region would experience an increase in conventional tillage and in notill acres, and a decrease in mulch tillage and ridgetill acres.

In the Australian crop sector, most significant impacts relate to land and water degradation such as clearing of natural vegetation, over irrigation, inappropriate crop structures and tillage systems. They result in biodiversity loss, salinisation and soil acidification among others, with salinisation of special concern due to its sustainable development impacts. Salinisation leads to decreases in crop production, degraded water supplies, damaged infrastructure and higher production costs. Biodiversity loss is also aggravated by salinity. Australia’s economic costs per year of dryland salinity have been calculated in $700AUD million in lost land and $130 AUD in lost production (Maltais et al 2002).

Whilst dairy products production in US is expected to fall, it is likely to increase in Australia and New Zealand. Main environmental concerns associated to dairy products are increased water pollution, greenhouse emissions and reduced biodiversity.

Table 13 summarises the expected impacts for nonEU developing countries.


Table 13: Summary of Sustainability Impacts for Other Developed Countries



Direction and

magnitude

(q,s

,0,

r, p

)

Currentstress

(L,M

,H)

Extent

(L,M

,H)

Reversibility

(yes, no)

Probability of

occurrence

(L,M

,H)

Effectiveness

and capacity

of policy and

regulation

(L,M

,H) Impact

significance (q,s, 0, r, p)


Slight overall decline in US production (but low by normal year by year variations)

q M

Concentrat ed in

production areas of products such as

wheat and dairy

Yes, depending on

compensation M H

s

Increase in Cairns developed countries production

p M M H H p

Real consumer incomes through lower prices

r M

Effects bigger in US and other

protective countries than other developed countries

M, depends on pass through of tariffs onto

consumer prices

H

r

Fixed capital formation Employment

Agricultural jobs s H

Decreases in US dairy

labour, but increase in corn in certain regions

Yes, depending on

compensation H H

s

Agricultural jobs p H

Strong increase in employme

nt in Cairns

developed

H M

p

Social Poverty

Poverty headcount r M Concentrat ed in US

Yes, if losers can be

reemployed M H

Blank

Poverty headcount s M

Employme nt

opportuniti es for less skilled workers

M M

s

Health and education Government

revenues through reduction in subsidies

r M In US, but not Cairns group

Yes, through lower tax revenues

(lower tariffs but stable imports)

H H

r

Equity Equity in subsidies recipients:

Large farms loose most subsidies

r L US M H r

Change in factor return r M

Cairns group, factors prices change towards unskilled workers

M H

r




Direction and

magnitude

(q,s

,0,

r, p

)

Currentstress

(L,M

,H)

Extent

(L,M

,H)

Reversibility

(yes, no)

Probability of

occurrence

(L,M

,H)

Effectiveness

and capacity

of policy and

regulation

(L,M

,H) Impact

significance (q,s, 0, r, p)

Environmental Biodiversity

Biodiversity s M

Loss of biodiversit

y, salination and soil

acifificatio n in

Australia

Depends on corrective measures

M H

s

Environmental quality

Use of chemicals due to loss of production

r H Rural areas

No, production declines H H

r

Use of chemicals due to loss of production

s M Rural areas

Yes, farms can adopt

environment friendly

production methods

M H

s


Water use r /s M

Both positive and

negative changes depending on US region

M H

Blank

Institutional Sustainable development principles

Productivity /efficiency through

increased competition

r M M

No, farmers would stay

more competitive

M H r


Attention to plight of farmers r L M No, M H r


5. Extensions and Policy Implications The SIA has concentrated on identifying those impacts that are likely to be significant for the broad country types, providing an indication of whether impacts are positive or negative in respect to contributing to sustainable development objectives, and indicating the relative magnitude of impacts. Given the breadth of coverage, the assessments are necessarily qualitative. Some broad conclusions emerge: overall, economic and social impacts are likely to be positive, contributing to growth and poverty reduction (and hence to the broad objective of the Millennium Development Goals), but the overall environmental impact is likely to be negative, increasing pressure on sustainability of resource use. Within these overall impacts, there will be variations for countries, within countries and for products, as discussed above. A brief summary of the main results is provided in the Executive Summary, and we here focus on the implications, especially the types of policies that will be required to ensure that poor countries share fully in the global benefits.

Section 5.1 considers some of the limitations of the scenario we use and comments on a range of issues that we were unable to cover in any detail in the SIA. In most cases these simply add detail to the SIA, extending the coverage of effects or elaborating on the types of impacts. Lowincome developing and least developed countries (collectively we refer to these as poor countries) face the greatest challenge; only if they can achieve growth in domestic food production and expand exports can they expect net positive impacts. In regard to expanding exports, a major challenge is improving product standards, and this is the subject of Section 5.2. As indicated in the assessment, we believe that developed and richer (middleincome) developing countries have the institutional and policy capacity to identify the flanking policies required to address the impacts of trade liberalization (so too, in principle, do large poor countries such as India). Section 5.3 presents observations on how this study relates to the SIA studies on forestry and distribution services. The Overall Project Report brings together the three SIA studies and provides a more comprehensive assessment of cross linkages, so we focus on the linkages most important from the perspective of agriculture.

5.1 Extensions and Elaborations

The liberalisation scenario we considered was fairly narrowly defined, as are the scenarios considered in most modelling studies. Thus, what we considered were (uniform percentage) reductions in tariffs, export subsidies and broadbased reductions in domestic support. This excludes many trade policy issues important in negotiations, and some of these are considered in the first subsection below. We also concentrated the assessment on a selection of six products and ‘agriculture in general’ for six country types, but important issues arise for omitted products. Some of these are considered in the second subsection.

Other Trade Measures in Negotiations It is not a serious limitation of the SIA that we concentrated on average tariff reductions, as qualitative judgements on impacts are based simply on the observation that tariffs are reduced, and the impact tends to be greater the larger the reduction (there is no evidence that nonlinearities are important). Although we assume the reduction refers to applied tariffs, countries actually negotiate on bound tariffs and these are generally higher than what is applied. The difference, however, is unlikely to be sufficient to alter our assessment. Bouet et al (2004b) use a consistent, ad valorem equivalent measure of tariff duties and tariff rate quotas for 163 countries and over 5000 products. Among other things, they show (for a sample of countries including the EU, US, Brazil, India and other developing countries) that applied tariffs are actually very close to bound tariffs.

The assessment did not specify tariff escalation, but the assessment can easily be extended to this issue. Currently tariff escalation discriminates against exporters of relatively more processed commodities, and has been a factor keeping poor countries as exporters of


unprocessed commodities. Most tariff escalation facing poor (LDC and LIDC) exporters of largely unprocessed commodities has now been eliminated, although there are benefits from removing what remains. African exporters, at least, face limited tariff escalation on the agricultural products of most concern to them and product standards are a more important concern (Commission for Africa, 2005: 268), hence this is addressed in the next section. Nevertheless, developing countries historically have faced tariff escalation in developed country markets. An effect of this was to encourage export of unprocessed commodities so that efficient processing sectors were not developed, at least in the poorer countries. They are now late in establishing processing industries and the multinationals that dominate commodity markets have an interest in purchasing the unprocessed commodity (of course, if it became profitable there would be an incentive to process in poor countries). The more progress is made on eliminating tariff escalation, the greater the incentive for developing countries to increase production and exports of processed commodities. The pattern of impacts will be similar to that described in Section 4 as the poorest developing countries have the weakest processing capacity so are unlikely to derive shortrun benefits. In fact, promoting domestic processing will be more difficult than promoting domestic production. Among developing countries, the major exporters stand to gain most. Similarly, the assessments can easily be extended to accommodate sensitive or special products, as here domestic tariffs are reduced by less, therefore protection is maintained and efficiency gains are lessened. Many poor countries may consider food a sensitive product, and a case could be made to support domestic producers. However, protection is never the best form of support – input subsidies and measures to reduce supply constraints are always better.

The WTO negotiations under pillar two extend beyond subsidies to include other forms of export support, in particular export credits and food aid. The modelling studies reviewed in Section 3 often included reductions in export subsidies, but did not include scenarios for reductions in other forms of export support. In part this is because it is usually difficult to model other forms of export support as effects on world prices for a particular commodity, and in part it is because reduction proposals have yet to be clarified. The former difficulty arises because other forms of export support apply to specific commercial transactions rather than general production and export of a commodity. For example, export credits are granted to an exporter of a particular commodity to a particular market, and the terms of the credit can vary across transactions (by implication, the subsidy element varies by transaction, and is not therefore a single value applicable to the product in general). The same is largely true for food aid – the subsidy element can vary across (product/market) transactions. The core distinction is that whereas an export subsidy can be represented as a percentage of the producer (or export) price for the commodity, this representation is not so easy for other forms of export support. Nevertheless, the SIA can be extended to accommodate other export supports.

Export Credits The principle underlying the provision of export credits is one of insurance for risk of late payment (or in extreme cases nonpayment). As the level of risk can vary according to the characteristics of the product and importer (and the exporter, at least in respect of the capacity to bear risk), the level of insurance varies across transactions (even for the same product). In principle, insurance could be provided by the market (private sector) or by a public agency on commercial (financially sustainable) terms. The ‘standard’ problems in insurance markets apply (adverse selection, pooling and moral hazard) so the market would be inefficient and it is not difficult to make a case for public intervention. However, the issue under negotiation is the extent of the subsidy that should be provided in export credits.

The proposals for reform of export credits are intended to reduce the implicit subsidy. Thus, for example, proposals include limiting the duration of credits to 180 days, clarifying the minimum interest rates that should apply, and proposing risksharing arrangements (Bridges 9:1, January 2005, p. 9). Irrespective of the final detail agreed, the effect will be to reduce the implicit subsidy and therefore increase the cost of exporting. It is not possible to infer, in


general, how much of this cost increase will be borne by exporters (through higher premiums or risks) and how much by importers (through higher prices). One would assume, insofar as risk increases in price, that most of the cost is borne by exporters. This need not affect the volume of exports or the world price, as the increased cost would reduce the profit margin of exporters. However, as OECD countries tend to provide more generous credits than other countries, OECD exporters lose some of their advantage and may lose some of their market share. In general, the effects from our SIA perspective would be the same as reductions in export subsidies.

Food Aid Assessing the issue of food aid is complicated by there being two very different types (and the literature is not always clear on the distinction). On the one hand, there is food aid delivered as emergency relief, for example during a famine or humanitarian crisis. Much of this is delivered through the World Food Program and NGOs. By definition, there is a food deficit in the region (and procurement in neighbouring regions is not always possible), so a priori there is no adverse impact on local producers. On the other hand, a significant amount of bilateral food aid is a ‘vent for surplus’ – donor countries have excess production and use this as a form of aid for poor countries. The food is usually given to the government and sold on the local market at reduced prices. This could have adverse impacts on producers in recipient countries as the market price is reduced. For example, Italy, Japan and the US all give food aid in the form of rice to Ghana, yet Ghana is having difficulty in developing domestic rice production capacity. It is such food aid, rather than emergency relief, that represents export support in the context of the WTO negotiations.

The basic concern about food aid is that it increases the supply of food to the recipient at a price that undercuts local producer prices, therefore displacing local production. In this case, a reduction in food aid (or increase in price) benefits recipients, at least in the long run. This assumes, however, that there is local production capacity, whereas food aid is intended for countries (or markets) experiencing a shortfall in local supply and a limited ability to pay for imports (so that the food aid does not displace commercial imports). The literature suggests that food aid does not tend to have these adverse effects if it is filling a food deficit (there is no domestic production to displace) and/or it goes to a segmented market (the food is different to local produce and/or is sold on a market nor served by local producers,). For example, Levinsohn and McMillan (2005) use householdlevel data from Ethiopia to investigate the impact of food aid. They find that households at all levels of income benefit from food aid. Furthermore, because net buyers of wheat are poorer than net sellers of wheat, there are more buyers of wheat than sellers of wheat at all levels of income, and net benefit ratios are higher for poorer households, they find that the benefits go disproportionately to the poorest households. In other words, food aid appears to be ‘propoor’ in this case. The literature reveals examples where food aid has adverse effects on domestic producers, but reviews conclude that the disincentive effects can be mitigated (Isenman and Singer, 1993; Colding and PinstrupAndersen, 2000). The principal guidelines for preventing food aid from having disincentive effects are to ascertain that there is a food deficit, to target the food at the population facing the deficit and to ensure that the type of food provided does not compete directly with local products.

This implies that any reforms to food aid should not be allowed to deny the availability of food aid to food deficit countries. The important issue, for recipients, is that there is a deficit and the food aid is targeted to the segmented market where the deficit is (e.g. subsidised food to the poor who cannot afford local market prices). This does not prevent reductions in the prices paid to procure food aid in developed countries. If levels of agriculture price support are reduced under reductions in domestic support, then one would expect the price for procuring food aid to be reduced. In cases were the food aid is genuinely delivered to food deficit recipients (e.g. emergency relief), this price reduction could be passed on and would


benefit the recipients. In this way, the SIA can be extended to consider food aid, where the important issue is whether the recipient has a genuine food deficit.

While negotiated measures to address and eliminate abuses of food aid as a form of export support are desirable, it is important to recognise that such measures should not unduly restrict the legitimate uses of food aid to address the needs of food deficit countries and should not affect the availability of food aid for emergency relief. There is an issue as to whether WTO rules can and should deal with food aid that is not for emergency aid. Although WTO rules are intended to prevent market distortions, including in the market for agriculture products covered by nonemergency food aid, nonemergency (or programme) food aid can be used by (donor) countries as a hidden subsidy for agricultural exports by tying food aid (i.e. surplus production is exported as food aid). The difficulty, in a WTO context, is whether this should be addressed as a traderelated issue (hence WTO) or an issue regarding the definition and measurement of food aid (an OECDDCA issue). A forthcoming OECD DAC study on food aid suggests that tied aid can add 3350% on the costs of providing food, for example, the US requirement that US shipping must be used to transport US food aid adds substantially to the cost of providing the food. This requirement could be interpreted as a restriction on trade, and therefore be subject to WTO rules. Another issue is the price at which the food is procured in the developed (donor) country; however, this alters the value of the food aid as recorded by the donor (hence a DAC concern), rather than being in itself a distortion of trade.

It would be desirable if WTO rules can be designed such that they decrease the amount of tying and abuse of food aid as an export subsidy, while not decreasing the benefit to the poor consumers. The above suggests that at least 33% of the value of food aid resources can be saved if, rather than tied food, financial aid was provided to beneficiary regions (which would also give recipients the freedom to procure food at the best price available and/or from neighbouring countries with a surplus).. This would also reduce developed country induced distortions in the market for agriculture products. Obviously, changes in WTO rules should not lead to fewer benefits (e.g. less aid to address food needs, especially emergency aid).

Traderelated issues A number of issues are often discussed in relation to trade liberalisation although they are not inherently trade issues. Animal welfare is an example. As trade liberalisation is associated with increased competition, it may encourage more intensive animal farming methods, such as the use of growth hormones for beef, battery farming for poultry and trade in live animals (where conditions of transport are the issue). On the other hand, liberalisation facilitates greater market access for niche products, and may encourage producers of free range meat for example. The fundamental issue for animal welfare is that WTO rules do not permit discrimination according to the means of production. This is a concern that could appropriately be addressed in the context of negotiations on WTO rules, rather than specifically in negotiations on agriculture. Another example is provided by GMOs as compared to organic products. Trade liberalisation increases competitive pressures and GMOs may be promoted as more efficient on economic grounds, despite concerns regarding social and environmental impacts. On the other hand, liberalisation provides market opportunities and may encourage product differentiation into niche markets, such as organic or ‘fair trade’. In reality, these are traderelated issues. It is technology (and perhaps the actions of multinationals) that encourages the adoption of GMOs, rather than trade per se. Similarly, it is consumer preferences that determine the demand for niche products, whereas trade liberalisation makes it easier for suppliers to meet this demand. If consumers are willing to pay a premium for organic or fair trade products, they will be produced and traded. The important issue in terms of international trade is that products are labelled so consumers can be confident about what they are buying. This relates to product standards, to which we now turn.


5.2 Product Standards and Agricultural Trade

As discussed above, developing countries face a major challenge in improving product standards in order to reap the full potential benefits of liberalisation through expanding exports. Global competition in agricultural commodity markets has increased in terms of quality, price, supply chain management and reliability of supply. Consumer preferences are also changing due to higher incomes as well as the emergence of health (food safety) and other social concerns (e.g. over labour and environmentally friendly practices). These factors have led to the development of new codes of practice and enforcement mechanisms in agricultural markets. In particular, the development of product standards is being increasingly driven by firms higher up the distribution chain (retailers) as enforcement moves more towards primary commodity production. Changing consumer demand is also encouraging the development of national and international standards which requires regulatory agencies to become more effective in supporting the private sector and ensuring compliance. Developing countries, especially African countries (see Ghana case study), recognise that meeting the product standards required to export food to developed country markets is a major challenge.

Responding to these changes presents considerable challenges to governments, firms and farmers in developing countries where there are recognised capacity constraints in both the development of product standards, compliance and enforcement as compared with industrialised countries. Wilson (2001) categorises standards into two broad forms: product and process standards. Product standards define the quality, safety or authenticity characteristics that goods should possess (e.g. maximum pesticide residues on an agricultural product). Process standards concern the conditions under which a good is produced, packaged or processed (e.g. employment conditions for farm labourers, animal welfare).

Standards can facilitate trade by reducing transactions costs associated with imperfect information regarding product quality and safety. Standards can take the form of informal rules reflected in industry practices (voluntary codes of conduct) and mandatory rules i.e. technical regulations. For the latter, failure to comply prohibits a product from being sold in a given market. The former, in contrast, are often determined by consumer demand and failure to comply with them may hinder consumer acceptance but not necessarily restrict market access. In many cases, voluntary standards have stiffer requirements than technical regulations and may significantly add to production costs (especially for small firms). For many valueadded food products, including fruits and vegetables, fish, beef, poultry and herbs and spice, industry practices have moved well beyond basic provisions for food safety (Jaffee and Henson, 2004).

The process for defining, implementing and enforcing standards (national or international) can therefore be costly as well as complex. There is increasing concern about the use of standards as nontariff barriers to trade. Standards can, and indeed do, act to impede exports, either because explicit bans are placed on imports of particular products or the costs of compliance diminish competitiveness. The process of developing standards can result in excessively high levels of protection, in favour of domestic interest groups, which serve to block market access and restrict competition. Interest groups with less bargaining strength, who are unable to influence the standardsetting process, become standardtakers and may face all the compliance costs associated with these regulations. Complaints about standards from developing countries (especially African countries) to the WTO have been limited (Wilson, 2001). This is partly due to the fact that developing countries participate less effectively in the WTO and other foreign standardsmaking processes.

This raises a number of problems for developing country firms and farmers. First, as standardstakers, they may be vulnerable to sudden or frequent changes in foreign standards, especially when such changes occur with protectionist intent. This vulnerability is more


problematic when compliance costs are high and standards are defined ambiguously, without being underpinned by clear “scientific” evidence.

Second, the existence of multiple standards in export markets (imposed by different trading partners) increases production costs, especially when compliance requires different production processes or if different testing and verification procedures are needed for each export market. Agricultural product standards vary between countries due to differences in tastes, diets, income levels and perceptions that influence the tolerance of populations towards risk (differences in climate and in the availability of technology (e.g. refrigeration) affect the incidence of different hazards). Different country standards may also reflect the feasibility and costs of implementing standards (Henson, 2004). However, the existence of multiple standards serves to limit agricultural trade by reducing both the incentive to export to more than one market and the potential benefits from economies of scale that would accrue from uniform international standards.

Third, foreign standards can become ‘moving targets’ if domestic producer groups can successfully influence the development of national standards and make them more stringent once their competitors achieve compliance. In Kenya, for example, processed foods from Del Monte were restricted from accessing the EU market in 2001 because of new EU standards for worker safety and environment.

Finally, many firms and farmers in developing countries are dependent on local institutions for information regarding technical regulations in export markets. This can be problematic if the information management infrastructure is weak and there are delays in communicating changes in foreign standards to firms. Installing the necessary traceability, labelling and packaging systems can also have significant cost implications, particularly for small firms. For Kenya, Nyangito et al. (2003) find that: 1) large producers with direct contacts with exporters are more aware of foreign standards compared to small producers; 2) exports based on formal contracts with farmers create more awareness than informal sales; 3) the existence of export agents creates more awareness about standards; 4) exporters who sell directly to consumers rather than importers are more aware of standards required by export markets and demand that their producers meet these requirements.

Even when standards are harmonised and ‘fair’, compliance costs related to the upgrading of production and infrastructure systems and enforcement may still differ significantly across countries. The cost of complying with standards can be prohibitive depending on the type of standards applied, the stage of development of the exporting industry (or country) and the efficiency of support services available to the local private sector. This is due to differences in institutional capacity, human capital, and technological capacity, particularly in developing countries where there are often resource constraints. This can create a gap between existing national standards and enforcement capacity in developing countries, and those required on international markets the ‘standards divide’. The World Bank global study on technical barriers to trade (2003) found that over 30 percent of African firms believe that compliance with local labelling, testing and certification costs less compared to compliance with foreign regulations. The study also finds that African firms face additional costs through needing to invest in new equipment, labour and inspection activities in order to meet international standards.

Empirical research highlights the negative impact of standards on trade, especially in relation to phytosanitary and food safety regulations. Amjadi and Yeats (1995) find that approximately US$5.9 billion of OECD imports from Africa are subject to these measures. Through participating in the development of international standards, and implementing acceptable international rules, Africa could gain up to US$ 1 billion in increased agricultural export earnings.


Losses associated with divergent national regulations block developing countries from entering new product markets. In the case of EU food safety standards on African exports, Otsuki et al. (2001) find that the EU standard on aflatoxin B1 a contaminant found in agricultural products – costs African exporters over US$670 million per year in lost grain exports. Wilson and Otsuki (2002) propose that if all countries adopted international standards for pesticide residues in bananas instead of the stricter national standards set by many developed countries, then earnings from Africa’s banana exports would increase by US$410 million per year. For beef the use of international standards, rather than national standards, for maximum residue levels of veterinary drugs would increase South Africa’s beef exports by US$160 million per year.

There are, therefore, two main challenges facing developing countries with respect to standards (Box 5.1 illustrates the case for Kenya; Ghana would have similar concerns).

First, there is a need to invest in national standards development, monitoring and compliance in order to meet international standards. This requires the development of standardisation systems, quality control, and accreditation. There is an increasing need to strengthen the capacity of institutions involved in monitoring compliance to national and international standards. This is particularly important for African countries where liberalisation and the removal of commodity boards has undermined the quality of agricultural products (e.g. a problem, initially, for cotton exports from Tanzania). Streamlining the roles of standards agencies also creates better focal points of responsibility and improves monitoring and compliance. Where more than one institution is responsible for domestic standardsetting, quality systems have been shown to suffer (Nyangito et al., 2003). Transport, packaging and marketing also present enormous challenges in the distribution of agricultural products from the production point in developing countries to the final consumer. Port charges, delays and freight costs are significant constraints to exporting and the availability of adequate transport infrastructure greatly affects quality, especially where such products are perishable.

Second, there is a need to improve the participation of developing countries in the setting of international standards and the monitoring framework so as to minimise the use of standards as nontariff barriers facing their exports and improve transparency.

Incentives for improving compliance with international standards can be policy or market related. In certain circumstances, such as in Uganda’s coffee industry, policies and incentives provided to farmers may fail to encourage investments in compliance. Farmers may have an incentive to ignore product standards if the regulatory penalties against low quality suppliers are small compared to the costs of investing in modern production facilities (Rudaheranwa et al., 2003). The low volume and quality of local demand in developing countries may also reduce the incentive for firms to invest in compliance with international standards and may sometimes compel national standardsetting agencies to develop technical regulations that are lower than international norms. For many firms in developing countries, producing for the local market is a necessary first step in the export process but (due to poor consumers) some may exchange quality for affordable prices. However, in other sectors or countries (e.g. flowers in Kenya) investments in quality may be encouraged if rewarded through significantly higher prices on the world market.

The WTO Agreement on Sanitary and Phytosanitary Standards (SPS) was designed to address some of these challenges. The SPS Agreement aims to (Wilson and Abiola, 2003):

• Encourage the adoption of scientific measures in the adoption of standards; • Prevent discrimination between Members and reduce standardrelated restrictions on

international trade;


• Promote SPS measures based on international guidelines and risk assessment techniques; and,

• Encourage the adoption of standards developed through broadbased participation and consensus.

The SPS Agreement, therefore, sets out broad rules for the legitimate application of food safety and agricultural health regulations. However, the Agreement provides countries with flexibility in setting and applying standards so complications are inevitable, particularly in areas where no agreed international standards exist and scientific knowledge is incomplete. The agreement also provides a mechanism to assist developing countries in meeting compliance costs with SPS measures in their export markets. Members agreed to provide technical assistance (through bilateral and multilateral aid programmes) to developing countries in developing processing technologies, research, infrastructure, training, equipment and national regulatory bodies. However, this has yet to be implemented.


Box 1: Kenya and international standards compliance

International standards are important to Kenya because merchandise trade (of which agriculture is a significant component) contributes over 40 percent to GDP. The coordination of standards development and implementation is performed by the Kenya Bureau of Standards (KEBS), which also serves as a focal point for information on international standards. Three other public organisations are also involved in the development of product standards and implementation: Kenya Plant Inspectorate Services (KEPHIS), the Department of Veterinary Services (DVS) and the Ministry of Health (MOH). KEPHIS is responsible for standards relating to plant health and plant products. DVS oversees standards relating to animal health and animal products. The MOH is responsible for standards relating to food safety.

Most standards for Kenyan products are based on international standards and guidelines. However, not all Kenyan standards conform to internationally accepted norms e.g. standards for fruits and vegetables under the KEBS Act are weaker than international standards. This is partly due to constraints in financing attendance in international meetings by both public sector and private sector officials involved in standard setting but also because Kenya faces constraints in the implementation of international standards including:

1) weaknesses in export certification systems e.g. livestock products for export to the EU, Japan and US

2) inadequate testing facilities e.g. chemical tests for foodstuffs 3) poor capacity to undertake risk analysis and surveillance programmes for pests,

diseases, chemical residues and food safety 4) inadequate pest control which has led to restrictions on Kenya’s beef exports 5) poor infrastructure leading to long transportation periods which can damage fresh

horticultural products

Product standards have had different impacts on Kenyan industries:

Coffee Since the economic reforms in Kenya (which began in 1993) new privatelyowned processing factories, marketing agencies and millers have emerged from the formerly governmentowned sector. These organisations are adjusting to a new legal framework and face challenges in delivering improved standards implementation services to farmers.

Horticulture (fruits, vegetables and flowers) Horticulture has expanded rapidly in recent years. It is the second largest export industry, after tea. The industry is wellorganised in its production and marketing arrangements. Producers, exporters and private sector organisations coordinate the activities of the industry, which includes advice on standards implementation for export markets. The major challenges in standards are the ability to meet maximum residue levels in export markets, pest risk analysis and continually changing consumer preferences (with respect to social and environmental production methods). Costs of compliance vary with the type of crop grown. At farmlevel, farmers are required to invest in capacity and inspect produce for good agricultural practice. This costs approximately US$2,000 per month for a production capacity of five tonnes of fruits or vegetables or ten tonnes of flowers daily. Investment for quality controls from farms to portofexport for the same tonnages of fruit/vegetables or flowers, respectively costs about US$123,000. This investment is only affordable to large commercial farmers. Small growers are only able to achieve this through cooperative arrangements or contracts with larger growers.

Cotton The cotton industry in Kenya grew rapidly between 1960 and 1985 but suffered decline in the 1990s. The current focus is to revive the industry. Quality cotton production is hindered by a lack of quality seed, sustainable disease and pest control methods and outdated ginning facilities. A distribution system for seed cotton that ensures provision of quality inputs as well as an efficient marketing system for cotton lint is required to overcome these problems.

Source: Nyangito et al., 2003.


5.3 Interlinkages with Forest and Distribution Services SIAs

Crosscutting impacts are particularly marked between agricultural liberalisation and the forest sector. As identified in the impact matrices, increased incentives for agricultural exports lead to greater production, and in some cases forest clearance. The case studies for Brazil and Ghana are clear examples. In the case of Brazil, a further increase in soybean production is forecast, much of which might well occur through an expansion in the tilled area on the margins of the Amazon, putting increased pressure on areas with unusually high biodiversity. Expansion of beef exports can also be expected to accelerate deforestation. In Ghana, the principal export crops contributing to further deforestation are cocoa, oil palm, coffee and rubber. Similar effects can be expected to occur in many other countries.

A small interlinkage between agriculture and forestry also occurs in the opposite direction. Liberalisation in forest products may itself accelerate conversion of land to agriculture, and hence potential impacts associated with fertilisers, pesticides and herbicides. In general, however, the greatest pressures are expected to arise from liberalisation of agriculture itself.

Interlinkages in both directions also occur with distribution services. Global value chains increasingly dominate the market for green vegetables, encouraging a rise in production for export and associated agricultural impacts. The distribution chain can however generate beneficial effects in the production chain, through setting environmental and social standards for production. Meanwhile, the increase in international trade associated with the liberalisation of agriculture increases transportation through the distribution chain, with adverse impacts on environmental factors such as climate change.

We elaborate two types of interlinkages, interactions and cross cutting impacts, between the sectors.

Interaction of impacts of trade liberalisation across sectors Interlinkages between sectors occur in several ways. Firstly, the effects of liberalisation in one sector may depend on the level of liberalisation in other sectors. This occurs for example between distribution and agriculture liberalisation. A supply response in the agriculture sector to the emergence of more export opportunities after tariff liberalisation is more adequate when there are good quality local supplies and when an efficient distribution system is in place. The efficiency of the distribution may depend on the level of liberalisation. While the distribution system is already open to liberalisation in Brazil (see Distribution study), this is less the case in less developed countries. In essence, a liberalised and more efficient distribution system enhances (M&E measure) the positive effects of agricultural liberalisation. Conversely it is possible that a liberalisation of the distribution regime is more likely to draw in investment, and this is more likely for those countries that are faced with increased export opportunities, such as those through agriculture tariff liberalisation.

Related to this, competition policy governing the value chains that link agricultural producers in developing countries to large importers in developed countries may shift some of the profits towards agricultural producers. This is because more competition will increase the possibility that the importer will reduce the consumer price after a cut in tariffs. This may lead to more demand which filters through to the suppliers of farm gate products.

A similar liberalisation interlinkage occurs between agriculture and forestry. Liberalisation in forest products may itself accelerate conversion of land to agriculture, because it becomes relatively profitable to be engaged in commercial logging. This may have potential impacts associated with fertilisers, pesticides and herbicides. On the other hand, the possibility of commercial forestry may draw some resources away from agriculture, though the effects are likely to be small and localised. Conversely, agricultural liberalisation may lead to higher


returns to agricultural activities in countries such as Brazil, and this could lead to fewer incentives to be engaged in forestry activities.

Crosscutting impacts Secondly, liberalisation in one sector may have crosscutting impacts on another sector. Crosscutting impacts are particularly marked between agricultural liberalisation and the forest sector. As identified in many of the impact matrices, increased incentives for agricultural exports leads to greater production, and in many cases, land clearance.

The case studies for Brazil and Ghana are clear examples. In the case of Brazil, a significant increase in soybean production is forecast, much of which might well occur through an expansion in the tilled area on the margins of the Amazon, putting increased pressure on areas with unusually high biodiversity. Expansion of beef exports can also be expected to accelerate deforestation. In Ghana, the principal export crops contributing to further deforestation are cocoa, oil palm, coffee and rubber.

Similar effects can be expected to occur in many other countries. In those with high agricultural export subsidies the effects will be ameliorated, but the overall effect expected is one of increased agricultural exports and increased pressure on land clearance.

Conclusions Interlinkages between sectors occur, including amongst the distribution, forestry and agriculture sectors. However, it is expected that the main effects will come from agricultural trade reform, partly because initial protection is higher in this sector and partly because there are a host of complementary conditions that would lead to successful agricultural trade liberalisation, in which forestry and distribution take only a small role. Conversely, land clearance or deforestation may have many causes, and the spread of agricultural activities is only one factor (others include industrialisation, urbanisation, etc.).

The latter point highlights an important caveat to the SIA: the effects of the liberalisation scenario on prices and market access will be marginal relative to other determinants of agricultural production and trade. The ‘normal’ annual volatility of farmgate prices is very high relative to the predicted price effects of liberalisation, especially in developing countries. As mentioned above, the problem for exporters of unprocessed primary commodities is not simply that (world) prices are very volatile, but also that the annual changes are not predictable (Newbold et al, 2005). This is exacerbated by the longterm downward trend in real commodity prices, at least for most agriculture commodities. For example, between 1995 and 2002, prices of cereals declined by 20%, cotton and sugar lost about half of their value while coffee prices collapsed to almost a third of their 1995 value, although prices of cocoa and tea increased by almost 25% and 10% respectively (WTO, 2003). Population growth and consumer incomes have a greater impact on trends in global demand than do changes in trade policies. Technological change (e.g. GMOs) is a more important driver of changes in production methods, and environmental effects, than are changes in trade policies. Changes in consumer preferences (e.g. willingness to pay a premium for fairtrade products, which can be very important for developing country producers) are a more important determinant of demand for niche products than are changes in trade policies. While the overall impact of trade liberalisation is likely to be a positive (marginal) impact, this occurs in a world of other factors, some of which exacerbate the trade liberalisation effects, whereas others weaken or swamp the trade liberalisation effects.


6. Mitigation and Enhancement Measures

As it is not possible to do justice to the full range of possible complementary policies, or mitigation and enhancement (M&E) measures that could be considered to address particular impacts, we limit attention to identifying some of the most important challenges that emerge, and how these could be addressed. This Section considers the types of issues that should be addressed by M&E measures, especially in poor countries. Furthermore, as the crosslinkages are relevant to the M&E measures to recommend, the M&E issues most important for negotiators are also covered in more detail in the Overall Project Report.

Mitigation and enhancement of potential impacts may be taken through traderelated measures within the negotiation framework, such as adjustment to the timing or phasing of trade reforms, through domestic measures within the EU, domestic measures in other countries (particularly developing countries), development assistance provided by the EU, and contributions to international measures. These types of measures are identified in the following discussion of the overall needs for mitigation or enhancement.

In broad terms, the study reveals that an overall economic gain is available through agricultural trade liberalisation, primarily through increased allocative efficiency. In principle therefore, it should be possible to mitigate adverse social and environmental impacts while still achieving a net economic gain. More detailed studies are needed in order to evaluate the specific costs and benefits of particular policy measures, including any international measures which may be needed in order to redistribute costs and benefits between countries. The types of measures discussed in this section may be considered in more detailed studies of this nature.

Environmental impacts

As we identified the main overall concern as regarding environmental impacts, we begin with that. Since the main concerns relate to adverse impacts, the priority is for mitigation of such impacts.

• Policies to increase the environmental efficiency of agriculture are essential to mitigate the potential adverse impacts of expansion in agricultural production, a trend to which trade liberalisation contributes. This is important for all countries, but is especially important for poor developing countries, for which technical assistance can make a valuable contribution.

• Relevant policies include resource pricing, pollution pricing and associated economic instruments, and regulatory measures to manage externalities and protect the environmental interests of disadvantaged social groups.

The environmental impacts of changes in farming and food processing depend on a range of factors far wider than those changes in price incentives that arise from trade liberalisation. A great deal, for example, depends on the local ecosystems within which agriculture is carried out. Moreover, there are a priori reasons to expect that a price movement in either direction could improve or harm the environment. For example, a price rise may lead to more intensive use of natural resources, a change in the land use system, and increased applications of chemicals all of which may harm the environment. On the other hand, the same price rise makes the farming system that much more valuable, encouraging farmers to invest in conserving their land. Specific environmental measures are required to achieve environmental protection and the provision of natural public goods. Some technical changes may help: progress in integrated pest management, soil nutrient management, water conservation and management, and in plant breeding (including some forms of biotechnological genetic modification). Environmental management is not a priority in most developing countries, where poverty is generally the main concern, and issues of environmental sustainability are not always immediately apparent. Their capacity for monitoring and improving practices and


regulation is limited (for this reason they score low on the process indicators in the SIA). The types of measures required to address environmental impacts will vary by country type, as impacts vary, and capacity for environmental management varies..

In the middle income developing countries, a major issue is enforcing the regulations that exist (e.g. on deforestation) and encouraging the adoption of better environmental management practices. Assistance with developing expertise in environmental economics may make a significant contribution, in order to strengthen awareness among senior policy makers of the relationships between environmental and economic sustainability.

In poorer countries (LDCs and LIDCs) the issue is often the low priority given to environmental concerns and the lack of regulatory capacity. Even where policies on environmental management exist, they are rarely fully incorporated into national or agriculture development strategies, and the responsible Ministries are often underresourced (in terms of money and personnel). Aid agencies can make a major contribution by strengthening the environmental component of Poverty Reduction Strategies, through, for example, undertaking Strategic Environmental Assessments of these strategies, and supporting their development into full National Sustainable Development Strategies. Specific needs for technical assistance should be identified through, for example, the evaluation of existing environmental monitoring mechanisms, the practical implementation of environmental management mechanisms, and the effectiveness of existing law enforcement institutions.

The EU and other developed countries tend to have much better policies and regulatory mechanisms, so the issue is how to ensure that adverse social impacts do not cause adverse environmental impacts (e.g. by supporting the role of smallscale farmers in preserving the rural environment) or that potential gains from less intensive farming methods are actually realised (e.g. set aside).

Economic impacts

Increased world prices for some foods will have an adverse impact on food deficit (net food importing) countries. Mitigation measures should include policies to promote increased and more efficient local production, maintain competitiveness for traditional commodity exports, or support for diversification. However, in some countries that are structurally food insecure (e.g. many small islands), and more generally during the adjustment period, food deficit will need some support to maintain the volume of food imports. This could be met by appropriate food aid, although financial aid to compensate for higher prices would be preferable. In net food importing LDCs, mitigation should include measures to increase domestic food supply, to avoid the negative impact of higher import prices. In some countries, measures may also be needed to maintain competitiveness for traditional commodity exports, or support for diversification. Needs will vary according to specific circumstances, and so country specific analysis of impacts should be undertaken for all LDCs, as part of development assistance programmes. Country specific analysis should also be undertaken to identify appropriate implementation of the WTO special safeguard mechanism and arrangements for special products.

In countries where the economic impacts are positive, enhancement measures may still be required to facilitate increased production (e.g. ensuring that technologies are available to increase yields, thereby encouraging efficiency) and trade (e.g. avoiding transport bottlenecks). In the EU and other developed countries, the issue is one of providing income and employment opportunities in regions where farm production declines (treated as a social issue). As detailed throughout the report, there are few direct economic benefits for poor countries (LDCs and LIDCs) and enhancement measures are necessary if domestic producers are to be enabled to expand production and increase competitiveness (thereby providing a


benefit to such countries). The major concern of poor countries aiming to increase domestic food production has been identified as constraints to supply response:

• Poor developing countries need an effective agriculture sector development policy that addresses nonprice constraints on producers – poor transport and marketing infrastructure, lack of access to credit and inputs (especially seeds and fertiliser), limited access to new land and slow rates of adopting appropriate new technologies.

The key point in most developing countries is to facilitate response, above all by farmers and herders, to the changes in relative prices. The land is highly versatile, as are most farm workers, and many farm tools and physical investments can be used for a wide range of activities: prima facie, there are good reasons to expect producers to be able to respond. Improving access to inputs, markets and technology are the issues. There is nothing new in these observations – they underpin the agriculture development policies recommended for poor countries. The problem has been a lack of political will to push through major reforms (e.g. land reform) and a lack of resources for financing investment. The types of measures needed are detailed in Commission for Africa (2005), especially Chapter 8 on trade and Chapter 7.3 (‘Policies for Growth’ including agriculture and infrastructure). This also provides an estimate of the full cost, as a doubling of aid flows to Africa is recommended. Interestingly, the Report does not discuss the impact of imports or importcompetition on African producers (Morrissey, 2005), and therefore does not cover some impacts that are relevant in the SIA.

For developing countries, governments will require a policy response to any revenue loss due to tariff reductions. In principle, if tariffs are reduced tax revenue falls and governments must either i) increase other taxes (revenue substitution) or ii) reduce expenditure. Alternative forms of revenue substitution will have different effects, e.g. a rise in capital tax may weaken investment incentives, whereas the impact on growth from a rise in sales tax may be relatively neutral in relation to the reduction in import tax. In practice, tariff reductions need not reduce revenue, e.g. the volume of imports may increase (demand response to the lower price) so that a lower tax rate on a larger tax base yields the same revenue. However, especially in poorer countries where revenue substitution is more difficult and takes time, a temporary revenue loss should be anticipated. A case can be made for a temporary increase in aid to cover the adjustment period and prevent cuts in essential expenditures.

Social impacts

In the EU and other developed countries the mitigation measures must address protecting rural livelihoods, especially where smallscale farms may go out of business (regional and structural funds could be deployed for this purpose). Perhaps the most important measure would be studies by the Commission to identify where the adverse impacts will be greatest and what types of support policies are appropriate in affected regions (this is beyond the scope of the SIA study).

Developing countries that gain in economic terms have the potential to provide social benefits, although enhancement measures will be required. In particular, many of the Latin American countries that stand to gain are characterised by high inequality. The economic benefits will not translate into social benefits (gains for small farmers and the poor) unless redistributive measures, especially land reform, are implemented.

Insofar as poor developing countries can achieve economic gains, the social impacts are potentially positive, as agriculture development is generally propoor (the poor are more likely to be employed in agriculture and food comprises a larger share of the consumption of the poor). These positive effects should be promoted.


• Poverty reduction strategies should recognise the importance of agriculture and the rural sector, and the implications of trade for the sector. This is important for all countries. In developed countries it is already recognised through support for farm incomes and rural communities. The importance of agriculture for the poor in developing countries is recognised and central to PRSPs, but more could be done to incorporate trade effects. However, identifying the policies that should be implemented requires detailed impact studies at the country level, and poor countries will require assistance to conduct such studies and implement the necessary policy measures.

In poor countries, where capacity is limited, institutional reforms are very important. Adjusting to the impacts will be simpler and more rapid if there is some public action to help farmers adjust. In most countries the most pressing measures concern:

• Measures to reduce transport costs. This does not always require investment in physical infrastructure, as often reforms to Customs procedure, trade facilitation and the efficiency of road and rail distribution systems can deliver large benefits.

• Financial systems are often underdeveloped so that it is difficult for farmers to access funds for investment and purchasing inputs. Microcredit schemes are helpful on a smallscale, but larger scale interventions are required.

• Institutional strengthening of property rights (for land use if not ownership) and contract enforcement.

• Support for enhancing product standards, and trade facilitation more generally (e.g. better information on standards required for particular export markets).

• Research and extension services to facilitate the adaptation and adoption of appropriate technology, including increasing yields and more efficient environmental management.

Summary

In the EU and other OECD countries, actions which may be taken to minimise or avoid adverse effects include:

o Strengthening environmental regulations or marketbased mechanisms to counter potential pollution impacts (especially regarding transport).

o Protection of rural livelihoods and the amenity value of the rural environment by replacing agricultural support by WTOcompatible support for other activities such as tourism or recreation.

o The use of landuse planning and the designation of conservation areas to optimise the biodiversity and amenity value of rural areas.

o Education and training policies to assist and accelerate the takeup of new employment opportunities.

In developing countries, there is greater scope for enhancing beneficial impacts as well as mitigating adverse ones. A key factor is the extent to which agricultural employment losses associated with accelerated commercialisation of agriculture are countered by higher value added opportunities in other sectors of the economy. This will be strongly influenced by national development strategy and associated international support.


Possible actions to mitigate potential adverse impacts include:

o Strengthening environmental and health regulations, and the ability to enforce them, and marketbased environmental mechanisms.

o Promotion of appropriate agricultural technologies and management techniques associated with water use, nutrient control, fertilisers, pesticides and herbicides.

o Encouraging recognition by policymakers that economic, social and environmental impacts should be identified and addressed in national development strategies.

These may be enhanced by international measures:

o Technical assistance and capacity building for national actions (e.g. supporting countrylevel SIA studies).

o Recognising the specific needs of net food importing developing countries, especially small island economies. A case can be made for aid to compensate these countries for any (temporary) increase in the price of food imports.

o Greater international financing and support to protect against food security crises.


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Appendix 1: Country Case Studies

Ghana Case Study

1 INTRODUCTION

1.1 Background

The WTO negotiations and expected impact Member states of the World Trade Organisation (WTO) have committed themselves to reach agreement to liberalise agricultural trade. The Uruguay Round of talks cover the areas of market access, domestic support and export subsidies. Trade liberalisation is expected to bring benefits to exporters through improved access to markets in other countries, and to importers through cheaper goods.

Sustainability impact assessment (SIA) with six case study commodities and six case study countries The inception report of the study lists the commodities and countries selected for the study (see Morrissey et al, 2004). The six products selected are wheat, rice, beef, sugar, cotton and green vegetables. The six countries cover two developed countries the EU and USA (developed countries). The four developing countries include Brazil (net exporter of wide range of products), and India (relatively protected market and an exporter as well as importer). The others are Tanzania (least developing country that export cash crop and import food grain and benefit from preferential treatment), and Ghana (lowincome developing country not classified as least developed but with similar pattern and efficiency of their agricultural sector as that of a least developed country). Underlying the case studies, is the expectation that the extent of benefits will vary for different countries, and that there may be the need for measures to enhance benefits that accrue from liberalised trade.

1.2 Methodology

The study makes use of secondary information. The work started with a review of policies, particularly those relating to agricultural production and trade. Another broader issue covered was the importance of the case study commodities in the economy.

The Ghana study followed the methodology proposed by ODI for the country case studies. This started with identifying the trade measure and establishing the impact on production through the effect on the incentive structure. The economic, social and environmental impacts of the changes in production were assessed using the suggested indicators.

Data availability was a big challenge. Production data available at the Ministry of Food and Agriculture (MOFA) did not cover cotton and green vegetables. Official data on trade available at the Ministry of Trade Industry (MOTI) were detailed but did not cover many years (available for the period 1998 2003). The FAO web site was the primary source of the data used. In a number of cases the FAO figures on production and trade were different from the official figures of MOFA and MOTI. Among the case study commodities rice is the one on which data were more readily available. However, doubts have been raised over the reliability of rice production estimates (see Shiratori and Odoi, 2003; FSRPOP, 2003). As a result of limited information the causal chain analysis could not always be entirely adequately addressed, particularly with respect to quantitative assessments of causal relations.

This results reported here include the policies, importance of the case study commodities in production and trade. Also covered are the impact of price changes arising out of trade measures on production, and the effect of the production changes on economic, social and environmental indicators.


2 OVERVIEW OF GHANA’S ECONOMY AND POLICIES

2.1 Important socioeconomic indicators

National income and the contribution of agriculture

Agriculture (including forestry and logging) is the largest of the three broad sectors of the economy. It accounts for about 36% of the Gross Domestic Product (GDP)

Incidence of poverty

Poverty is highest among food crop producers, and women are predominant in this activity. Data from Ghana Living Standard Surveys, as reported by IMF (2003) [IMF. 2003. Ghana Poverty Reduction Strategy 20032005: An agenda for growth and prosperity] show that food crop farmers constitute 59% of the poor, making the contribution of food crop farmers to the national incidence of poverty far higher than their population size. Some of the factors accounting for this are: i) lack of access to markets, ii) high cost of inputs, and iii) low levels of economic infrastructure

Expenditure on social services

Spending on health and education and other social programmes is relatively low (2.0% and 2.8% of GDP on health and education respectively).

2.2 Overall policy framework

The Ghana Poverty Reduction Strategy (GPRS) forms the basis of current government economic and social policies since 2000.

Policy framework since the mid1990s. The policy framework since the mid1990s as presented in the GPRS 20022004 is summarised in this section.

Ghana Vision 2020: The First Step (19962000): This was the initial attempt to implement the overall Vision 2020 strategy which adopted a 25year perspective. It had the objective of improving individual and social well being. This policy document addressed issues of public and private sector roles, poverty alleviation, gender equity, employment generation and rural development.

The First Medium Term Development Plan (19972000): The MTDP was supposed to be an elaboration of the initial actions to implement Vision 2020 but it was belated. The plan was originally based on collaborative work between Ministries, Departments, Agencies (MDA). There were also regional and district level consultations with civil society. The MTDP covered five thematic areas: economic growth, human development, rural development, urban development and the development of an enabling environment. The plan was found to have limited success largely because of limited coordination between the National Development Planning Commission (NDPC) responsible for plan formulation and the Ministry of Finance (MOF) responsible for economic and fiscal management.

Ghana Poverty Reduction Strategy (GPRS) The GPRS envisage the implementation of medium term priorities aimed at generating growth and reducing poverty. The priorities over the period 20022004 are infrastructure, modernised agriculture based on rural development, enhanced social services, good governance and private sector development.

The modernisation of agriculture has the objective of developing the country to become an agro industrial economy by the year 2010. Actions envisaged include the reform of land acquisition to ensure easier access and more efficient land ownership and title processes. It is also expected that the government will serve as a catalyst to assist the private sector to increase the production of grains such


as rice, maize and tubers to achieve food security by improving access to extension and research services, irrigation facilities, and affordable credit to support the farmer. The other actions to be taken are encouraging the production of nontraditional cash crops such as cashew, and supporting the private sector to add value to traditional crops such as cocoa.

2.3 Agricultural policy

With the liberalisation of the economy initiated in 1983 as part of a structural adjustment programme initiated with the support of the World Bank and IMF Government set the producer prices of some commodities, including exported ones such as cocoa, cotton and palm oil. Minimum guaranteed prices were set for food grains such as maize and rice that were produced locally. Also, there were restrictions in international trade and imports were regulated through a system of import licensing. By 1990, agricultural trade had been liberalised and market forces allowed to determine prices. The exception is cocoa, which in spite of the abolition of the monopoly held by the Cocoa Board, prices are set by the Government. Currently, there are no subsidies or domestic support measures that contravene WTO rules. Indeed, apart from the Green Box subsidies (i.e. non, or at most minimally, trade distorting support), farmers in Ghana do not receive price or income support.

A medium term agricultural development programme (MTADP) was launched in 1991 to assure food security, increase rural employment, increase agricultural exports and increase production of raw materials through institutional reforms. Following the relatively slow agricultural growth in the 1990s (by just over 3% a year) the Accelerated Agriculture Growth and Development Strategy (AAGDS) was formulated with the aim of accelerating the annual growth rate in agriculture to 6% for the period 1997 2007. The main elements of the strategy are promotion of selected products through improved access to markets, development and improved access to technology, improved access to financial services, improved infrastructure, and enhanced human resource and institutional capacity. The Ministry of Food and Agriculture has more recently, formulated the Food and Agricultural Sector Development Policy (FASDEP) to provide a holistic policy framework, which takes cognisance of all ongoing efforts in the agricultural sector. FASDEP takes a sectorwide approach, in contrast to the discrete project approach of the past and aims at strengthening the private sector as the engine of growth (MOFA, 2002).

2.4 Environmental policy in relation to agriculture

The Environmental Protection Agency (EPA) has the responsibility of regulating the environment and ensuring the implementation of environmental policies (EPA, 1999). The National Environment Policy (NEP) was adopted in 1991 as part of the National Environmental Action Plan to ensure that in the formulation and implementation of development strategies and the specific economic activities that flow from them conform to the principles of sustainable development in relation to the environment. There is the recognition by the NEP that the environment is adversely affected in a situation when poverty levels increase as individuals will exploit the environment in a way that may not be desirable for the society at large.

The environmental constraints to sustainable agriculture identified by the EPA include drought, which is naturally occurring. The problems of soil erosion and declining soil fertility are caused by a combination of natural and human factors in that these problems are exacerbated by practices adopted. The communal ownership of land, which is widely practised, is perceived to discourage farmers from investing resources to conserve or improve fertility of land for sustainable agriculture. However, this perception overlooks the fact that there are longterm use rights.

Cultivation of watersheds to minimise risk of crop loss from drought, or in offseason production pose threats to the environment. Introduced technologies, such as the use of machinery for land preparation and harvesting may also pose a threat to biodiversity.

2.5 Environmental considerations of measures to promote agricultural production

The EPA, in its assessment of agricultural policies, observes that the MTADP, AAGDS and the Agricultural Services SubSector Investment Programme (AgSSIP) all recognise the need to address environmental issues for stated agricultural production objectives to be achieved. AgSSIP has the objective of putting in place institutional planning and implementation of agricultural development programmes, and creating the environment for accelerated agricultural growth (EPA, undated). The


AgSSIP, which has evolved from earlier measures, has positive environmental aspects built into its development objectives that are designed to improve rural incomes and reduce poverty. There are also mitigation measures that have been proposed to address environmental concerns that are likely to arise from the implementation of the programme.

2.6 Overview of Ghana agricultural commodity trade

Cocoa is the dominant agricultural export commodity. The other important commodities are coffee, sheanut and palm oil. The major agricultural commodities imported are rice, wheat and sugar.

Of the six case study commodities wheat, rice and sugar are important components of imports (each account for over 10% by value of total agricultural imports in 20012003, based on FAOSTAT data). Ghana is a net exporter of cotton and green (fresh) vegetables but the share of these commodities in total agricultural exports is not significant (less than 1% in 20012003).

2.7 Trade policy

Most of the information in this section is summarised from WTO (2001).

Export taxes and other export restrictions With the exception of cocoa, there are no export taxes on agricultural products. Restrictions on the export of commodities were removed in the 1980s as part of the liberalisation of the economy. Current policy is to reduce the tax on cocoa, which was around 45% in the 1970s and 1980s, when farmers received only 4050% of the international cocoa price. Farmers currently receive over 60% of the world market price. Apart from cocoa there is no state participation in the export trade, but even for this commodity the market has been liberalised. Up to the beginning of the 1990s the trade in cocoa was handled solely by a parastatal, the Cocoa Board. A number of licensed buyers now operate side by side with the Board’s company responsible for purchases.

Export promotion: As part of the implementation of an economic recovery programme (ERP) a package of incentives was introduced in 1983 to encourage nontraditional exports (this includes all exportable agricultural commodities with the exception of cocoa beans). This package currently includes a customs duty drawback, income tax rebate and full retention of foreign exchange earnings. There are no export subsidies for any product.

Import tariffs With the abolition of import licensing import quotas in 1989, tariffs are the only major trade measures that have direct impact on imports. There are four categories of tariffs, namely 0%, 5%, 10% and 20%. The zero and 5% tariff rates mainly apply to raw materials, the 10% to intermediate goods, and the 20% to consumer goods. In addition to the import tariffs all traded agricultural consumer goods are subject to a valueadded tax (currently 12.5% plus a national health insurance levy of 2.5% at the point of sale). This tax is not exclusive to imported goods.

Other measures

Technical standards and phytosanitary requirements are to ensure the safety of products. Fresh or unprocessed products require a phytosanitary certificate. Highrisk products (including foodstuff) are inspected at the point of shipment.

2.8 Export markets

The EU market is the major destination of Ghana’s exports, including agricultural products.

In general, Ghana has dutyfree access to the EU market, and there are no nontariff barriers to agricultural exports to the EU


Table 2.1 Value of Ghana’s external trade by region, percent Exports Imports

1999 2000 2001 19992001 Average

1999 2000 2001 19992001 Average

Europe % 78.69 76.69 77.52 77.45 56.41 52.23 58.79 55.92 EU % 56.72 49.01 46.81 49.44 54.33 49.99 57.28 54.03

Switzerland 21.38 26.94 30.22 27.42 1.03 1.36 1.32 1.28 UK 32.85 21.56 22.08 23.92 24.91 12.15 15.80 16.22

NonEU 43.28 50.99 53.19 45.67 50.01 42.72 NonEuropean 21.31 23.31 22.48 22.55 43.59 47.77 41.21 44.08 Note: The EU countries refer to those that were members in the period stated (i.e. excludes those that just joined the Union

Source: Based on data from Ghana Quarterly Digest of Statistics, December 2001

2.9 Contribution of trade to government revenue

Apart from cocoa, which account for a little under 20% of total central government revenue the other agricultural commodities do not contribute much to revenue. Reduction in import tariffs on agricultural commodities will deprive the government of needed revenue for development, but the impact may not be too adverse. Import tariffs are more crucial for the protection it affords producers in the absence of direct support to the agricultural sector.

Since the 1990s farmers receive about 60% of the fob price of cocoa, which is an improvement over the 4050% received in the 1980s. The policy of declining export tax of cocoa implies that this source of revenue will become less important. The concurrent reduction in import tariffs has the potential of further reducing the direct contribution of trade to government revenue. For the other commodities import tariffs, sales tax and special taxes, which currently total up to about 45%. These tariffs are perhaps more important for the protection it offers domestic producers from cheap imports than the revenue generated.

3 EXPECTED IMPACT OF TRADE LIBERALISATION MEASURES

3.1 Importance of case study commodities

The relative importance of the case study commodities in production and trade in Ghana are summarised in Tables 3.1 and 3.2. Rice and vegetables are important in production, while rice, sugar and wheat are important in trade. With respect to trade they are important as imports. The importance of a commodity in production and trade will determine the level of impact on the national economy from price changes that result from trade measures. Rice stands out as the commodity that is likely to have a major impact on the economy since it is the only crop that is important in domestic production and trade.

Table 3.1 The quantity of production and trade of case study commodities Quantity of

production, 2002 (MT)

Quantity of imports, 2002 (MT)

Quantity of exports, 2002 (MT)

Wheat grain 147,140 Wheat flour 63,090 Rice 280,000 314,626 1,989 Beef 24,125 231* Sugarcane 140,000 Sugar (raw equivalent) Not available 260,488 32,610 Cotton (seed) 18,313 6,297 Cotton (lint) 2,772


Green vegetables 634,950 15 6,005 *Quantity imported ranged fell from 23000 MT in 1991 to 10,000 MT in 1995 to 231 MT in 2002

Table 3.2 The value of imports and exports of case study commodities and total agricultural products Value of imports (1,000$) Item 2001 2002 2003 Average 200103 Wheat+Flour, Wheat Equiv. 56,171 66,066 77,005 66,414 Rice 102,455 75,167 66,356 81,326 Beef and Veal 50 234 370 218 Sugar,Total (Raw Equiv.) 59,930 76,210 110,600 82,247 Cotton total 167 123 470 253 Vegetables (fresh) 2 14 44 20 Agric. Products, Total 540,430 497,081 669,259 568,923

Value of exports (1,000$) Item 2001 2002 2003 Average 200103 Wheat+Flour, Wheat Equiv. 128 116 153 132 Rice 312 128 14 151 Beef and Veal 0 0 0 0 Sugar,Total (Raw Equiv.) 27 8,100 69,000 25,709 Cotton total 5,028 2,446 4,995 4,156 Vegetables (fresh) 62 7,294 9,496 5,617 Agric. Products, Total 495,307 659,223 1,030,288 728,273

Percentage of total agricultural product imports Item 2001 2002 2003 Average 200103 Wheat+Flour, Wheat Equiv. 10.39 13.29 11.51 11.67 Rice 18.96 15.12 9.91 14.29 Beef and Veal 0.01 0.05 0.06 0.04 Sugar,Total (Raw Equiv.) 11.09 15.33 16.53 14.46 Cotton total 0.03 0.02 0.07 0.04 Vegetables (fresh) 0.00 0.00 0.01 0.00 Agric. Products, Total 100.00 100.00 100.00 100.00

Percentage of total agricultural product exports Item 2001 2002 2003 Average

200103 Wheat+Flour, Wheat Equiv. 0.03 0.02 0.01 0.02 Rice 0.06 0.02 0.00 0.02 Beef and Veal 0.00 0.00 0.00 0.00 Sugar,Total (Raw Equiv.) 0.01 1.23 6.70 3.53 Cotton total 1.02 0.37 0.48 0.57 Vegetables (fresh) 0.01 1.11 0.92 0.77 Agric. Products, Total 100.00 100.00 100.00 100.00

Contribution of agricultural products to trade in 2001 Value of all imports, 1000$ 2,030,281 Value of all exports, 1000$ 1,445,261

Percent value of agricultural product in imports

26.62

Percent value of agricultural product in exports

34.27

Note: Data for specific products taken from FAOSTAT; data on total trade based on Ghana Quarterly Digest of Statistics data used to compute total trade (based on exchange rate of 7,000 cedis/$)


Agricultural products constituted 27% and 34% of the value of total imports and exports respectively.

Sensitivity of price changes on production and trade The demand elasticity shows the responsiveness of demand (import/consumption) of a commodity to a price change, while the supply elasticity shows responsiveness of supply (production/export) to a price change. The longrun elasticity for each of the case study commodities are shown in Table 3.3. The demand for commodities (imports) was very sensitive to price changes. On the other hand, supply (production) change in response to variations in price was low.

Table 3.3 Longrun demand and supply elasticity of case study commodities Commodity Demand elasticity Supply elasticity Wheat and wheat equivalent of flour

1.865**

Wheat 0.468* Rice 0.239 Beef and veal 1.160 Cotton (seed) 0.477 Cotton (lint) 1.414 Sugar 1.715** Green pepper 0.480** Chillies 0.260** **5% significant level *10% significant level

Notes 1. The elasticity for each commodity was estimated from data for the period 1989 to 2003 (or 2002 in cases where 2003 data were not available). Most of the distortions in production and trade were removed by1989.

2. Demand elasticity for wheat, beef and veal, lint cotton and sugar based on import data; supply elasticity for rice, green pepper and chillies based on production data; and supply elasticity of seed cotton based on export data

3. The values for seed cotton and lint cotton are contrary to what we should expect. This shows that the cotton industry’s production is not a response to world market prices. The possible explanations are as follows: i) Production is organised in outgrower schemes; actual production not actually what is planned because inputs supplied by cotton companies sometimes diverted by farmers to other crops ii) Small proportion of the commodity is traded: Just about 10% of the seed cotton produced is exported with most feeding the local textile industry.

The extent of substitution of imports for domestic products will depend on the crosselasticity between domestic and import variants of the same product, and between different products.

The possible crop substitutes for the case study products are: Wheat (flour): maize, cassava (part substitution in processing into flour) Rice: maize, sorghum, millet (substitution in consumption) Beef: mutton, chicken, pork (substitution in consumption) Sugar: vegetables, rice (substitution in cash objective and land requirement) Cotton: groundnut (cash objective and land requirement) Green vegetables: rice (cash objective and land requirement)


3.2 Expected impact of trade measures: Wheat

Production and consumption impact

The reduction of export subsidies or import tariffs is not expected to have much impact on domestic production. This is because wheat is not produced in the country and the product does not have close substitutes in utilisation. It is technically feasible for some locally produced commodities (maize and cassava) to be substituted for some part of the products for which wheat is used for (flour for bread, confectioneries, etc.). However, there is perceived “consumer aversion” to the use of possible substitutes for products for which wheat is traditionally used.

Table 3.4 shows the expected impact of trade measures on the imports of wheat. Import data for the most recent years and the longrun demand elasticity was used in the estimation. The higher purchase price, through the higher price at which the commodity is exported is expected to lead to reduced consumption of wheat products. However, given the low level of significance of wheat products in overall household food consumption at the national level, not much impact is expected. The high overall elasticity of demand shows that among households consuming the product there will be significant changes in demand. The high own price elasticity of demand is due to the fact that wheat products are not an essential part of food consumed. Lower prices from reduction in import tariffs will lead to a significant increase in the consumption of wheat products among households consuming the commodity. Overall, the price of wheat will rise by 12.6%, leading to a fall in imports (i.e. consumption) of 5.9% for wheat grain and 23% for wheat grain and flour combined. This implies that the fall in import is higher for wheat flour.

Table 3.4 Expected impact of trade measures on the imports of wheat 2000 2001 2002 Average

200002 Wheat grain Imports – Qty (Mt) 250,302 152,118 147,140 183,187

Demand elasticity 0.468 0.468 0.468 0.468 Import tariff 0.1 0.1 0.1 0.1 Import tariff (price) change, 0.24 0.24 0.24 0.24 0.24 World price change, 0.15 0.15 0.15 0.15 0.15 Domestic price change 0.024 0.024 0.024 0.024 Net price change 0.126 0.126 0.126 0.126

Overall change in imports, Mt 14,760 8,970 8,677 10,802 Percentage change in imports 5.9 5.9 5.9 5.9

Wheat grain+flour, wheat equivalent Imports – Qty (Mt) 277,530 191,973 210,230 226,578


Overall change in imports, Mt 65,217 45,112 49,402 53,243 Percentage change in imports 23 23 23 23

Although wheat does not have close substitutes it is expected that other staples, including imported rice and domestic staples, will substitute for wheat in overall food consumption.


Economic impact Marginal reduction in real income is likely to be experienced by individual consumers. This is more likely in urban centres since wheat products are consumed more among urban households. Unlike other consumer products, the final product from wheat that is consumed is processed by economic entities other than the household. The exact impact on economic variables will largely depend on the component of the import price of wheat in the final product. Wheat is first processed into flour, and the flour into consumer products. The processing into flour is relatively capital intensive while most of the processing into flour products (the major one being bread) is relatively labour intensive.

Social impact Income dimension of poverty is not expected to be adversely affected by the higher cost of accessing wheat products are not important in the food of households in the rural areas where poverty is more prevalent. On the social dimensions of poverty, the capacity of government to spend will be constrained by the reduced revenue from import tariffs. There will be more equitable income distribution between urban and rural (and higher and low income households) as the cost of increased price affect urban (and high income) households more.

Environmental impact

No environmental impact is expected.

3.3 Expected impact of trade measures: Rice


Changes in rice are likely to have a significant on both producers and consumers of the commodity. Also, it is one crop that has women as important producers, and significant to the rural economy in terms of production. In terms of consumption, it is a minor staple: 18kg per capita consumption in 1998/99 (Ghana Living Standard Survey estimate), compared to 57 kg for maize [for a better comparison estimate calories consumed]. However rice consumption is growing at a very fast rate (estimated to be about 6% per annum).

The government has identified rice production as a priority crop to reduce imports. This crop subsector is receiving attention in the provision of improved seed, extension on improved methods of production, farm equipment (tractors), processing facilities and packaging. Thus the structures to enable domestic production to compete with imports are in place. Donor support to improving rice production is also high. DFID, GATSBY, JICA and the World Bank, among others provide support to the development of rice. However, there is no direct support for rice production.

Table 3.5 shows the expected impact of trade measures (i.e. import tariff reduction and increased world market price) on domestic production of rice. Domestic price will increase by 10.2%. This will lead to an increase in production of about 7,0007,700 mt, which is equivalent to 2.4% of current production levels. With average yields of 2 mt/ha and cultivated area of one hectare per farmer, this is equivalent to additional 3,3003,900 hectares and the same number of farmers respectively. This increase is not significant at the national level when compared to the current state of production. Thus, even though among the case study commodities rice is the most important in terms of expected impact on domestic production this is not significant.

With respect to methods of production the higher price is likely to provide incentive for farmers to invest in new methods of production that are being promoted by the government to improve on yields and the quality of rice.


Table 3.5 Expected impact of trade measures on the domestic production of rice 2001 2002 2003 Average

200103 Current production 274,596 280,000 316,000 290,199

Supply elasticity 0.239 0.239 0.239 0.239 Import tariff 0.2 0.2 0.2 0.2 Import tariff (price) change, 0.24 0.24 0.24 0.24 0.24 World price change, 0.15 0.15 0.15 0.15 0.15 Domestic price change 0.048 0.048 0.048 0.048 Net price change 0.102 0.102 0.102 0.102

Overall change in production, Mt 6,694 6,826 7,703 7,074 Overall change in cropped area, ha (at 2 Mt/ha) 3,347 3,413 3,852 3,537 Equivalent change in farmers (at 1 ha/farmer) 3,347 3,413 3,852 3,537

Percentage change in production 2.4 2.4 2.4 2.4

It has been noted that local production does not respond in a way that competes with imported rice with higher prices. This is because the quality of the commodity, which is the major problem with locally produced rice, does not influence price (i.e. quality does not attract a premium price) [see study funded by DFID CPH Programme (R6688 ‘Improving the competitiveness and marketability of locally produced rice in Ghana’]. Therefore there is no incentive for producers to invest in quality. A study on rice production in Ghana by the ODI Rural Policy and Governance Group reveals the importance of noneconomic considerations (social status) attached to the consumption of imported rice in consumption centres in the south. Locally produced rice tend to be more appreciated in the rural areas where it is produced while urban consumers (in the south) have preference for the imported rice (see FSRPOP, 2003 synthesis of the Food Security and Rice Producers Organisation Project). Locally produced rice that is similar in quality to the imported ones attract lower prices in the urban centres. The need for local producers to overcome these noneconomic barriers will limit the attractiveness of local rice to urban dwellers used to imported rice.

Economic impact

The increased production will substitute for some imported rice but not likely to fully meet national requirements, particularly because of the low response of domestic production to price changes. There is likely to be an increase in valueadded activities, particularly packaging of rice to meet the standard of imported rice, which local production seeks to replace. We can expect increased capital formation in land and equipment for production, and increased informal employment, particularly farm work. Overall, the economic impact on the national economy would be minimal unless the preference for imported rice among urban households at the expense of locally produced rice, notwithstanding the quality of the latter, diminishes. Any change will be in the longrun and it will require an aggressive campaign to achieve the required change in attitude.

Social impact

There will be an increase in the price of rice to consumers of imported rice, while rice producers will benefit from higher income through higher production. On balance, since poverty in Ghana is largely a rural phenomenon, there will be a positive impact both in the reduction of poverty (through higher level of income received by producers in the rural economy). There will be more equitable income distribution between urban and rural but less equitable distribution between rural households as those who are able to invest to produce meet the higher demand for locally produced rice benefit from higher value of production. Also, there is likely to be less equitable gender distribution of income as men are more likely to invest to take advantage of new opportunities than women who are traditionally important in rice cultivation unless support is targeted at women. However, like the economic impact, these benefits will not be significant considering the marginal increase in production that is expected from the trade measures.


Reduced import tariffs, by reducing government revenue, limits the ability of the state to spend on health, education and other social programmes. However, this impact will be insignificant given the very small component of tariffs on rice in total government revenue.

The trade measures will lead to an increase in demand for land in inland valleys or that is irrigated for the production of rice types that are traded on the world market. This should not lead to changes in land tenure.


Following the current focus on the promotion of rice production in the inland lowlands as cheaper alternative to irrigated rice (see, for example, AfDB, 2001) expansion of production in inland lowlands is likely to have an adverse impact on these fragile environments. However, this effect is likely to be moderated by sedentary farming that is normally associated with larger scale production that the higher price is likely to induce. There is high cost associated with opening up and developing new land for improved practices.

3.4 Expected impact of trade measures: Beef


Generally, meat production and consumption is low. The production and consumption of other meat products are more important than beef. Even less important is the pursuance of animal production as a business. In the animal production sector poultry production (mainly undertaken in periurban and urban locations) is the most businesslike activity in this sector. Meat consumption is virtually absent in the diet of lowincome households.

Domestic beef production has increased over the years, reaching 18,570 MT in 2000 but contributes less than 30% of national requirement. Current policy geared towards support for breed improvement and extension (MOFA. 2002. Food and Agriculture Sector Development Policy). There is currently a project aimed at improving the production of livestock but this is not expected to bring about significant increases in production and trade in the short to medium term. Incentives to beef production (supply of breed, veterinary services, etc.) have declined since the 1980s following the downsizing of public role in the economy in the economic reforms pursued.

The expected impact of trade measures on the imports of beef and veal is shown for each year for the period 19892002 because of the wide variations in the figures. The difference is particularly wide for the period up to 1995 and the years that follow. The net effect on prices from world market price increase and reduced import tariff is a 10.2% increase in the domestic price of imported beef. This will cause a decline in consumption of imported beef by 12%. Locally produced beef and other animal products will substitute for imported beef.

Economic impact

The meat subsector constitutes a very small part of Ghana’s economy. Meat consumption is very low. FAO estimates put average consumption of bovine meat at just 1.3 kg/head/year in 200002. For all meat the consumption for the perion was 9.5 kg, and for fisf 33 kg. Also, there are virtually no downstream activities in beef production beyond slaughter and preservation. Therefore, trade measures are not likely to have significant economic impact in spite of the expected substantial changes in production and consumption. The gainers will be producers and sellers of locally produced beef and other meat products.

Social impact

The shift in consumption from imported beef to locally produced beef, other meat products and fish will increase incomes of local producers. This will improve income distribution between consumers (i.e. better off households) and producers. The benefit of increased consumption of locally produced beef will accrue to producers and traders in northern Ghana where cattle production and trade is concentrated. This will be a positive impact given that the north lags behind the south.



The increased cattle numbers from increased demand from domestic producers will create increased pressure on grazing land. This has the potential of increasing competition for land between food crop farmers and herders.

3.5 Expected impact of trade measures: Cotton

Cotton has been identified for special attention to supply the textiles and garments industry (MOFA 2002 – FASDEP). However, it is not a major commodity in Ghana and does not directly affect the balance of foreign trade. It is not a strategic export crop (according to the FAO, it only accounted for 0.2% of export earnings in 2001). Cotton (fibre and seed) accounts for less than 1% of the country’s total agricultural exports. In 2001, less that 10% of the total cotton fibre production was exported (FAO database, 2004).

Cotton is grown in the northern part of the country, where incomes are lower than the regions of the south where mainly because of cocoa and other favourable agricultural conditions (e.g. better rainfall) incomes are relatively higher. Cotton production was developed to provide raw material to the expanding traditional and modern textile industry in Ghana. The growth was the result of global industrialisation and import substitution policy of the postindependence period. A parastatal company was created to supervise production and market the crop. Production levels rose fast, and peaked in 1970. In the middle of the 1970s, production levels started falling as farmgate prices sank and extension services became far less effective. This made it difficult for the local textile industry to obtain its raw material. During this same time, several medium and large companies went bankrupt, their numbers dropped from 138 in 1973 to 72 in 1995. In 1982, the companies that had survived the crisis of the 1970s were only working at 5% capacity while they had reached 60% just a few years earlier (Seini, 2002). At the time of the cotton crisis in the 1970s, which lasted into the 1980s, the parastatal was gradually privatised. Thereafter, the cotton subsector was fully liberalised. At present there are 12 cotton marketing companies.

Production is organised as outgrower schemes by private companies, the largest of them (Ghana Cotton Company) being formerly stateowned (then known as Ghana Cotton Development Board). The producers, most of whom are poor, benefit from credit support in the form of land preparation, seed, fertiliser and pesticides. The farmers are obliged to sell the harvest to the company providing the support. The payments received by the farmers are net of the cost of the inputs supplied. Farmers sometimes divert some of the inputs for the production of other crops that they perceive to provide higher returns than the price offered by the cotton companies. Therefore planned production is not always achieved.


The price of cotton is expected to rise by 12.6%, based on the combined effect of 24% reduction in the 10% import tariff, and 15% increase in world market price. In the absence of meaningful estimates of the responsiveness of production (or export) of seed cotton and demand (or import) of lint cotton to price changes we can only make qualitative assessment of the expected impact of trade measures on cotton production. The net price effect would be an increase in the export price of seed cotton and import price of lint cotton. It is the change in the price in seed cotton that will affect domestic production. The cotton companies will increase production as a result of the higher price of the commodity on the world market. The higher price should make it possible for the cotton companies to pay good price to their farmers and thereby encourage production.


Table 3.5 Expected impact of trade measures on the import of beef and veal 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002

Imports – Qty (Mt) 900 6,000 23,000 22,000 15,530 13,763 10,000 380 70 67 248 90 45 231

Demand elasticity 1.16 1.16 1.16 1.16 1.16 1.16 1.16 1.16 1.16 1.16 1.16 1.16 1.16 1.16 Import tariff 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 Import tariff (price) change, 0.24 0.24 0.24 0.24 0.24 0.24 0.24 0.24 0.24 0.24 0.24 0.24 0.24 0.24 0.24 World price change, 0.15 0.15 0.15 0.15 0.15 0.15 0.15 0.15 0.15 0.15 0.15 0.15 0.15 0.15 0.15 Domestic price change 0.048 0.048 0.048 0.048 0.048 0.048 0.048 0.048 0.048 0.048 0.048 0.048 0.048 0.048 Net price change 0.102 0.102 0.102 0.102 0.102 0.102 0.102 0.102 0.102 0.102 0.102 0.102 0.102 0.102

Overall change, MT 106 710 2,721 2,603 1,838 1,628 1,183 45 8 8 29 11 5 27 Percentage change 12 12 12 12 12 12 12 12 12 12 12 12 12 12


Economic impact

Changes in the price will encourage cotton companies to increase investment in production as expected of profit oriented businesses. This should lead to better incomes for cotton farmers. On the consumption side, impact will be one of higher cost of production, as manufacturers of textiles have to pay higher prices for cotton. Part of this increased cost is likely to be passed on to consumers. The fall in demand for local textile products that is a consequence of the competition may lead to job losses.

Social impact

The trade measure will contribute to the reduction of poverty among cotton farmers in the north. The improved level of incomes also has the positive impact of bridging income gaps between the relatively poor north and the relatively endowed south. However, all consumers irrespective of income level, will face higher prices for textile products. Also while there will be the opening up of job opportunities on the farm, job losses are likely in the urban economy within which textile manufacturing takes place.


The expansion of cotton production and the adoption of modern practices that are associated with it will lead to increased use of fertiliser and pesticides. It is also likely that cotton will pose a danger to food production through the competition for land.

3.6 Expected impact of trade measures: Sugar

Sugarcane production has been identified for special attention to supply the sugar industry in the strategic plan of the Ministry of Food and Agriculture (see MOFA, 2002). At present there is no functional sugar processing plant. The sugar industry was vibrant in the 1970s when the government operated sugar production plants. However, even at the height of sugarcane production and processing only a small proportion of requirements was met. The current industrial demand for sugarcane is met by smallscale distilleries.


As a result of the high elasticity of demand for sugar, the 12.6% increase in the price of sugar from the trade measures is expected to lead to a decline in the demand (imports) and consumption of imported sugar by 22% (Table 3.6). In the absence of close substitutes for sugar, the effect would be to boost local production of sugar.

Table 3.6 Expected impact of trade measures on the import of sugar (raw equivalent) 2000 2001 2002 Average

200002 Imports – Qty (Mt) 140,974 223,942 260,488 208,468


Overall change, MT 30,463 48,392 56,289 45,048 Percentage change 22 22 22 22


Economic impact

Increased local production of sugarcane will increase farm incomes in the areas close the coast, where sugarcane production is concentrated. Distilleries will in particular increase their demand for products of locally produced sugarcane. The increase in domestic price of sugar will also serve as an incentive for the reactivation of manufacturing plants to process sugarcane to sugar for domestic use. The increased domestic farm and industrial production will boost employment.

Social impact

The higher financial returns to sugarcane, which is an industrial crop, will encourage farmers to crop it at the expense of food crops such as rice and vegetables, that use the same type of land (inland valleys). In addition labour may be switched from the cultivation of food crops to sugar cane.


The water requirement for sugarcane production restricts its production to inland valleys because of the high cost of developing irrigation facilities. Expansion of production will put pressure on this type of wetland. Cultivation in inland valleys is considered to be a threat to water bodies.

3.7 Expected impact of trade measures: Green vegetables

Production impact

Vegetable production is not a major economic activity. Vegetables are increasing in importance as nontraditional export crops and the production for export is a specialised activity. This type of production is on largescale and there is the adoption of modern practices of production and under irrigation. The producers select seed, some of which are imported, to meet varieties on demand on the world market, and adopt management practices to meet world market standards. There are two groups of producers who target the domestic market. There is the more commercially oriented who, like the exporters, adopt modern practices, except that fields are smaller and management less stringent. The second group consists of farmers who adopt largely traditional practices. Women vegetable producers are largely to be found in this group.

Table 3.7 shows the impact of different trade measures on the production of chillies and green pepper, which are major green vegetables that are traded. Reduction in import tariffs is expected to lead to a fall of 4.8% in the price of the vegetables if it were an imported product with no change in world market price; a rise of 10.2% if world market there is also an increased world market price. Excluding import tariffs is the more realistic scenario because green vegetables are traded as an export commodity. Without the import tariffs, net price change is the full world market price. Assuming a world market price rise of 15%, production increases by just 7%. This is because of the low elasticity of supply. This low elasticity of supply is explained by the stable production figures, which may not reflect the actual situation.

Economic impact

The trade measures will boost efforts to diversify exports from Ghana. However, in the short to medium term the higher export prices and the resulting increased production will benefit only the small proportion of farmers who are engaged in the commercial production of vegetables for export. Chillies and peppers, the major traded vegetable product, accounts for more than onehalf of total cropped area of all vegetables (see Table 3.8). However only a small proportion of total output is traded. The 6005 MT of all vegetables exported represents less than 3% of total production of chillies and peppers. Thus the impact of changes in the tariffs and world market price of vegetables on the economy will be negligible. However, the impact will be significant for farmers and exporters engaged in the trade of the crop.

Social impact

Smallscale gardening may be an enterprise for which women have experience, so that cash incomes are boosted.


Table 3.7 Expected impact of trade measures on the production of chillies and green peppers 200103 200103 200103 Average

200103 Current Production (Mt)* 270,000 270,000 270,000 270,000

Supply elasticity, 0.480 0.48 0.48 0.48 0.48 Import tariff, 0.20 0.2 0.2 0 0 Import tariff change, 0.24 0.24 0.24 0.24 0.24 World price change, 0.0 0 0.15 0 0.15 Domestic price change 0.048 0.048 0 0 Net price change 0.048 0.102 0 0.15

Overall change, MT 6,221 13,219 0 19,440 Percentage change 2 5 0 7 * The estimated production was 270,000 Mt annually (i.e. the same) for 2001, 2002 and 2003

Table 3.8 Production and trade of green chillies and peppers 1961 1981 2001 2002 2003

Production Vegetables, Total Area Harv (Ha) 46,700 57,000 138,905 138,905 138,905 Production (Mt) 160,000 222,200 634,950 634,950 634,950

Chillies&Peppers, Green Area Harv (Ha) 20,000 24,600 75,000 75,000 75,000 Production (Mt) 46,000 72,000 270,000 270,000 270,000

Trade Vegetables, Fresh Imports Qty (Mt) 0 0 2 15 Exports Qty (Mt) 0 0 138 6,005


Increased vegetable production will put pressure on lowlying wetlands suitable for irrigation. It will also lead to high use of fertiliser and pesticides.

SECTORAL LINKAGES

The commodities that are likely to have significant sectoral linkages are rice, beef and cotton. Wheat is not produced in Ghana. Sugar cane is grown but there are currently no processing plants in operation. Green vegetable production and marketing is a specialised activity engaged in by a small proportion of farmers and on a limited land size (with access to water provided naturally or by irrigation).

Most of the rice is produced in the north where there is little tree cover. Some of the farmers carry out the cultivation in valley bottoms. In the south, the focus of government agencies is to promote production in valley bottoms. While rice cultivation does not have an impact on trees, the intensification of production (in response to an increase in price) exposes the environment to the risk of agrochemical contamination. However, this potential adverse impact is mitigated through farmer education on the safe use of agrochemicals and controls over the types of fertilisers available in the country

An increase in the price of cotton on the world market will serve as an encouragement to cotton companies to increase output and possibly attract new entrants. This commodity will compete for land under food crops fallow in savanna environments of northern Ghana, where production is concentrated. The removal of subsidies will adversely affect the operations of local textile manufacturing firms to the extent that they face a higher raw material price.


Increased cattle numbers will lead to pressure on grazing fields and water. Increased cattle production in the south will affect destruction of crops and fallow fields but not the tree resource. Already, there is increasing conflict between crop farmers and migrating herdsmen over destruction of crops by cattle in the important agricultural production areas in the middle belt.

REQUIRED INTERVENTIONS TO IMPROVE IMPACT FROM TRADE

Improving access to production resources

The responsiveness of domestic production to price incentive is very low. This suggests that markets, though necessary, are not sufficient to induce increased production. Thus, there are structural bottlenecks that have to be addressed to facilitate investments in agricultural production. Improving access to capital and other resources may be required to enable potential investors respond to price incentives.

Improving social impact

Naturally, the benefits of trade cannot be distributed uniformly across all sections of the population. However, action can be taken to reduce the degree of income disparity that is likely to arise. One group that is considered disadvantaged is women. They undertake rice and vegetable production, two of the case study crops that are likely to benefit from trade liberalisation. While the problem of accessing resources to take advantage of price incentives is a general one, women are more disadvantaged. Baden (1998) notes that the distribution of benefits from agricultural market liberalisation has mainly favoured larger scale commercial producers and traders, or providers of support services to marketing. Therefore, women are less likely to benefit from liberalisation policies because of their smaller scale of operations. The Informal Working Group on Gender and Trade (IWGGT), a worldwide network of organisations concerned with gender issues, on the basis of results of a case study on Ghana concludes that women’s roles in the home and the economy at large restricts the benefits from trade liberalisation. To address the possible imbalance in the benefits from trade, there is the need for specific interventions. For example, women may be assisted to access resources to invest in the production or trade in the commodities that have enhanced returns as a result of the trade measures


Rice, sugar and vegetables hold promise to improving incomes as a result of measures to liberalise trade. These crops are normally cultivated in the lowlying fields to because of the water requirement throughout the season. We should, therefore, expect that pressure on inland valleys would increase. To minimise negative impacts on the environment, farmers will have to be educated on the sustainable use of these fragile environments, and the proper application of agrochemicals.

REFERENCES

Baden, S. 1998. Gender issues in agricultural liberalisation. Topic paper prepared for Directorate General for Development (DGVIII) of the European Commission (revised) Report No 41

DFID CPH Programme (R6688)… ‘Improving the competitiveness and marketability of locallyproduced rice in Ghana’

EPA (Environmental Protection Agency). 1999. Environmental Protection Agency at a glance. Accra: EPA

EPA… Strategic Assessment of Agricultural Services Sector Investment Programme (AgSSIP) of the Ministry of Food and Agriculture. Accra: EPA

FAOSTAT data, 2004.

FSRPOP (Food Security and Rice Producers Organisation Project). 2003. 10 years of studies on the Ghanaian rice sector: Synthesis

Ghana Statistical Service (…) Ghana Living Standard Survey 1991/921998/99


GyanBaffour, G. undated. The Ghana Poverty Reduction Strategy: Poverty Diagnostics and Components of the strategy. Accra: National Development Planning Commission

National Development Planning Commission (…) Ghana Poverty Reduction Strategy 20022004

IMF. 2003. Ghana Poverty Reduction Strategy 20032005: An agenda for growth and prosperity

IWGGT (Informal Working Group on Gender Trade). 1998(?). A Preliminary Note highlighting the Conceptual and Policy Links Between Gender and Trade [Accessed in November 2004]

MOFA. 2004. Ghana national average wholesale prices 19702004

MOFA (Ministry of Food and Agriculture). 2002. Food and Agriculture Development Policy (FASDEP)

MOFA. 2004. Production of some major crops in Ghana: 19702003

AfDB (African Development Bank). 2001. Inland Valley Rice Development Project: Appraisal Report

MOTI (Ministry of Trade and Industry). 2004. Imports of Rice 19982003

MOTI (Ministry of Trade and Industry). 2004. Imports of Sugar 19982003

MOTI (Ministry of Trade and Industry). 2004. Imports of Wheat 19982003

Morrissey, O., Willem te Velde, D. and Gillson, I. 2004. Inception report for the sustainability impact assessment of proposed WTO negotiations: Agriculture sector study. ODI, London, UK

National Development Planning Commission (2002) Ghana Poverty Reduction Strategy 20022004

Seini, A. W. 2002. Agricultural growth and competitiveness under policy reforms in Ghana. Technical Publications No. 61, Institute of Social, Statistical and Economic Research, University of Ghana, Legon.

Shiratori, K. and Odoi, J.S. 2003. The rice industry in Ghana: constraints, potential, and prospects for cooperation between MOFA and JICA.

USAID (United States Agency for International Development). 1997. Food aid in Ghana: An elusive road to self reliance, PN–ABY–237 1997, Number 3

WTO (World Trade Organisation). 2001. Trade policy review, Ghana 2001. Geneva: World Trade Organisation


A Case Study of Indian Agricultural Sector 1

I. Agriculture: Significance for Indian Economy

There are no two opinions that the agricultural sector in India dictates the general pattern of growth and distribution in the Indian economy. It provides employment to 40 million farm households comprising 67 percent of the total population and its contribution to the GNP is still about 2526 percent. Besides supplying much needed nutrition to over 1 billion people and raw materials to the industry the agricultural sector in India is playing a significant role in earning foreign exchange.

Despite numerous long standing constraints such as unpredictable monsoon, vast patches of drought and flood prone areas, low public investment, proliferation of marginal and small holdings, varying availability of agriculture input across regions etc. the sector has achieved respectable growth rates and made India selfsufficient in food grains. Today India is among the first ten countries in most of the crop production in world.

Liberalisation of world trade in agriculture has opened up new vistas of growth. India has a competitive advantage in several commodities for agricultural exports because of near selfsufficiency of inputs, relatively low labour costs and diverse agroclimatic conditions. These factors have enabled export of several agricultural commodities over the years such as marine products, cereals, cashew, tea, coffee, spices, oil meals, fruits and vegetables, castor and tobacco. For certain commodities like Basmati Rice, India has a niche market access in spite of competition. Agricultural export has sizeable share of about 1520 percent in total exports of the country. Agricultural imports are about 56 percent of total imports in the country. Only a few commodities like edible oil, cotton, pulses and wood & wood products are imported.

The sustainability impact assessment of Indian agriculture sector has an added significance. As mentioned above agriculture is a source of livelihoods for millions of poor people in India. Unlike developed countries and some of the large developing countries Indian economy is still predominantly rural in character. Therefore, any policy changes either at international or national levels, which disturbs the status quo of farm sector in India, is bound to have significant economic, social and environmental implications.

The current paper has been organised into eight sections. Section II gives a brief account of the commodities, which have been selected for study. Section III discusses the agricultural trade liberalisation in India, both because of India’s own initiative and induced by the WTO Agreement on Agriculture (AoA). Section IV analyses how the trade liberalisation of agricultural sector has impacted on the overall growth of the economy, production of the farm sector itself and exports and imports of agricultural products. Section V looks at how the trade liberalisation, necessitated by the WTO AoA, influenced the various economic, social and environmental sustainability indicators. Section VI is the most important as sustainability impact assessment of future trade liberalisation has been done. Section VII explores the possibility of intra and intersectoral linkages. Finally, in section VIII discusses what kind of policy preparedness are required to face the existing and future challenges which may emanate from WTO AoA.

II. Major Agricultural Commodities

The present study focuses on four commodities, viz, rice, wheat, cotton, and sugar. There is a lack of availability of uniform data on green vegetables and since beef is neither an important domestic consumption item nor a major exportables from India, the study, therefore, examines only four out of the six products. Here it is worthwhile to give a brief account of each of the four product categories.

II.1 Wheat

India’s wheat economy is expanding rapidly. The production increased sharply after the Green Revolution in mid 1960s. At present it accounts for 35 percent of the total foodgrains production. The area under the crop was 26.62 million hectares with a production of 72.06 million tonnes in 200304. Between 195051 and 200304, there has been a huge increase in area under wheat cultivation and the total output. The improvement is also seen in the productivity, which rose to 2619 kgs/ha in 200203 due to the use of High Yielding Varieties (HYV) seeds. The share of India’s wheat production in the world’s production is about 12 percent and is the second largest producer of wheat in the world.

1 Draft study provided by CUTS Centre for International Trade, Economics & Environment in India to the ODI, December 2004


Wheat is almost nonexistent in the South, very limited in the East. The Northern and western States comprising Haryana, Punjab, Rajasthan, Himachal Pradesh, Jammu & Kashmir, Madhya Pradesh, and Uttar Pradesh are the major wheat producing states in India. These states approximately contribute 35 percent of the total production of wheat. As reflected from the Agricultural Census data, area allocated to wheat is increasing. This increase is uniform across different farm holdings, but the increase in the larger size of holding is higher than the group of small and marginal farmers.

II.2 Rice

Rice is an important cereal and consumed as major food item in most of the states in India. It has the largest share in foodgrains production, accounting for 42 percent of the total. Rice is grown in all parts of the country but the highest production comes from Eastern region, which produces 29 million tonnes, followed by the South at 24 million tonnes, and the North at 23 million tonnes. Andhra Pradesh, Jammu & Kashmir, Orissa, Punjab, Uttar Pradesh, Tamil Nadu and West Bengal are the major rice producing states. In 200304, the area under the crop was 42.41 million hectares with a total production was 87 million tonnes. The yield was 2051 kgs/hectare, almost three times more than the yield in 1950 51.

The yield levels were uneven as certain regions lagged behind. In order to improve the yield levels, the government of India implemented the rice programme for Eastern states and later, and Integrated Cereals Development Programme (ICDP) for rice. The growth rates in rice production experienced a step up due to this programme during the eighties, which continued in nineties as well. This has also been corroborated by increase in the consumption of fertilisers in Eastern and Western regions during the eighties.

II.3 Cotton

Cotton is a commodity of global economic significance enjoying comparative advantage for India in cost and quality. India accounts for approximately 20 percent of world’s total cotton area and 11 percent of global cotton production. Over 49 percent of the total Indian cotton production is of long and extra long staple varieties. The total output in 2003 04 is about 13.5 million bales (of 170 kgs). Productivity of the crop was 220 kgs/ha in 200102 In the case of HYV, the yield per hectare was around 226 kgs per hectare, which was lower than the world average of cotton yield well over 550 kgs/ha. The growth rate of the area under the crop has significantly increased from just 0.11 percent between 1960 and 1971 to 2.4 percent between 1990 and 2000.

Gujarat, Andhra Pradesh, Haryana, Maharashtra, Punjab and Tamil Nadu are the major cotton growing states. The data from Agricultural Censuses show that the area share of cotton is increasing across all the size classes, but substantially in the medium and large size of holdings. The export of raw cotton was quite high compared to imports up to 199697. In 19992001, export of cotton was 0.1 million bales of 170 kgs, against the import of 1.9 million bales. In contrast to this, the mill made fabrics and clothes and readymade garments constituted around 20 percent of our exports.

II.4 Sugar

Sugar is an all time commercially important crop. It was grown in an area of 1.71 million hectares in 195051, which increased to 4.32 million hectares in 19992000 with a production of 299.22 million tonnes. The per capita net availability of sugar increased from 13.15 gms per day to 42.74 gms per day during 19502000. This is a remarkable progress. The growth rate of area under the crop was quite impressive. The growth rates in area stepped up from 1.02 percent between 1960 and 1971 to 1.81 percent between 1990 and 2000.

About 45 million Indian farmers and their families are dependent on the sugarcane cultivation. Uttar Pradesh alone accounts for 35 percent of India’s total sugarcane production.

Presently, India is one of the sugar surplus countries. The export of sugar in 200203 was of US$375mn as against the import of US$6.8mn. This implies that the country is a net exporter of sugar. The crop is mainly cultivated in small and semimedium holdings. As seen from the Agricultural Censuses data, the area share under the crop has been increasing during the last three decades. The contribution of the crop to the GDP of agriculture was 6.97 percent and 5.75 percent of the total value of the agricultural output in 199899.


III. Agriculture Trade Liberalisation in India

During the last five decades there have been highly interventionist trade policies practiced by India, which have discriminated against agriculture, particularly in the category of basic foods such as cereals. International trade in cereals by the private sector was practically banned during the period 195095, with the exception of Basmati rice exports and maize imports for the poultry sector. These restrictions on the external front were supplemented by substantial controls over pricing, procurement, stocking, marketing and transport of food grains at the domestic front.

When India embarked on to the process of comprehensive economic liberalisation in July 1991, the agriculture sector was not in the agenda items. It mainly touched upon external sector, industrial sector and fiscal reforms. The trade reforms undertaken as a part of larger external sector reforms included devaluation of the rupee and gradual dismantling of import, export, and exchange controls. Although a very little headway was made in the matter of liberalisation of agricultural trade, the devaluation of the rupee in 1991 made many Indian agricultural products competitive in the international market.

The exports of all merchandise including the exports of agricultural products from India recorded a significant increase in growth during the 1990’s. Besides, gradual liberalisation of trade in India and dismantling the process of controls also contributed to growth of agricultural exports. The total agricultural exports recorded an annual growth rate of 8.12 percent during the nineties compared with a low growth of only 2 percent during the eighties (Bhalla, 2004).

III.1 Agriculture Trade Liberalisation in PostWTO Era

The major impetus towards agricultural sector liberalisation in India came after the establishment of the WTO in 1995. India is a founder member of WTO. In order to fulfil its obligations under the WTO AoA, India has undertaken several policy measures to reform its farm sector. India’s obligations under the WTO AoA fall mainly under four broad areas namely market access, export subsidies, domestic support, and Sanitary and Phytosanitary Measures (SPS).

III.1.1 India’s Obligations Under Market Access

According to he WTO AoA, all nontariff barriers to agricultural trade were to be tariffied and converted into their tariff equivalents. Further, tariffs resulting from this “tariffication process” were to be reduced by a simple average of 36 percent over a period of 6 years in the case of developed and 24 percent over a period of 10 years in the case of developing countries. In addition to this, for countries, which had tariffied, there was also an obligation to maintain current and minimum access opportunities and to establish a minimum access tariff quota of a minimum of 3 percent of domestic consumption in the base period 198688. This was to be gradually increased to 5 percent of base period consumption over the implementation period.

Along with many developing countries, India was permitted to offer ceiling bindings instead of tariffication. These bindings were not subject to the reduction commitments. India was also allowed to maintain quantitative restrictions (QRs) on account of balance of payment problems. But since India had not tariffied and was, instead allowed to bind its tariffs, it did not have any market access commitment. But like many developing countries, which decided to bind their tariffs, India is also not entitled to use the Special Safeguard Measures (SSG) of the AoA, which can be used by only a few (36) developed countries, which had tariffied.

Since, AoA allowed members either to tariffy in all cases or to bind their tariffs, during the Uruguay Round, India chose to follow the latter route and bound its tariffs for 3375 tariff lines which constituted 65 percent of India’s total tariff lines defined at 6digit HS level. Out of these 3375 commodity groups, 683 commodity lines at 6digits of HS classification belong to the agricultural sector. Simultaneously, India continued to have QRs, which it was permitted to impose because of BoP reasons. Like many other developing countries, except for a few commodities, India bound its tariffs at 100 percent for primary products, 150 percent for processed products and 300 percent for edible oils. But, for certain items (comprising about 119 tariff lines), which were historically bound at a lower level in the earlier negotiations (Table 1), the binding levels were very low, in some cases, even zero. But these zero or low tariffs had no relevance because India was allowed to use QRs.

The USA and some other countries in the Dispute Settlement Body (DSB) of WTO challenged India’s continuation of QRs on the plea of BoP position. In view of its improved position in the matter of foreign balances, India lost the plea for retention of QRs on account of BoP position both at the DSB as well as at the Appellate Body. According to the understanding arrived at between the parties regarding the reasonable period of time latest by March 2001, India removed the QRs on 714 items including 142 commodities belonging to the category of agricultural commodities


during 199900. On the occasion of Export and Import Policy announcement on 31 st March 2001, the Minister announced the removal of QRs on the remaining 715 items, thereby ending the muchmaligned “License Permit Raj”.

With the removal of 715 items from the list, which include 42 groups belonging to agriculture, quantitative restrictions on imports have been completely abolished and the obligation to replace QRs by tariffs has by and large been fulfilled (except for a few strategic commodities). After the decision to remove QRs, India was under GATT Article XXVIII, allowed to renegotiate the tariffs bindings on those commodities for which it had very low or zero tariff bindings. Consequently, in December 1999 India successfully negotiated and the bindings levels were suitably revised upward to provide adequate protection to the domestic producers. Out of these low bound tariff lines, bindings on 15 tariff lines, which included skimmed milk powder, spelt wheat, corn, paddy, rice, maize, millet, sorghum, rapeseed, colza and mustard oil, fresh grapes etc. were revised to a level ranging between 45 percent to 75 percent.

Table 1. Tariffs and Bound Rates on Agricultural Commodities/Groups Under Study S.No. Products Basic Customs Duty

(%) (As on 01.03.04) Bound Duty (%) (As on 01.01.04)

1. Wheat 50 100 2. Rice

Rice in the husk 80 80 Husked (brown rice); broken rice 80 80

3. Sugar 60 150 4. Green vegetables

Frozen vegetables – peas, beans, spinach, sweet corn etc.

30 150

All other vegetables 30 100 5. Cotton 10 100 Source: Agricultural Statistics at a Glance, August 2004, Ministry of Agriculture, Government of India.

III.1.2 India’s Commitments Under Export Competition

Export subsidies were subject to reduction commitment, in the area of export competition, though several kinds of direct payments were exempted. The export subsidy commitment is either in the form of budgetary outlay reduction commitments or in the form of export quantity reduction commitments. Export subsidy outlays in budgets are to be reduced by 36 percent for developed countries and 24 percent for developing countries over a period of 6 and 10 years respectively. The volume of exports receiving subsidies is to be reduced by 21 percent per product or group of products for developed countries and by 14 percent for developing countries over the same time period. These reductions are to be made by taking 198690 as the base period. The LDCs are not subject to any reduction commitments. The commitments are defined over commodity aggregates rather than individual lines.

Export subsidies of the kind listed in the AoA, which attract reduction commitments, are not extended in India. Indian exporters of agricultural commodities do not get direct export subsidy. The only subsidies available to exporters of agricultural commodities are in the form of: (i) income tax exemptions on profits from export sales and (ii) subsidies on costs of freight (export shipments) of certain products like fruits, vegetables and floricultural products.

Since these payments are exempt for developing countries from reduction commitments during the implementation period, they will not cause any adverse impact on agricultural exports from India, at least during this period. Therefore, India is making use of these subsidies in certain schemes of Agricultural & Processed Food Products Export Development Authority (APEDA), especially for facilitating export of rice, wheat and horticulture products. But once the export supplies become selfsustaining during the adjustment period, these will have to be withdrawn.

III.1.3 India’s Commitments Under Domestic Support

The AoA distinguishes between three types of production support, grouped into “boxes”, which are given the colours of traffic lights: green (permitted), amber (slow down – i.e. to be reduced), blue (subsidies that are tied to programmes that limit production). There are also exemptions for developing countries in the form of Special and Differential Treatment (S&DT).


Domestic support measures, according to the Agreement, are meant to identify acceptable measures of support to farmers and curtailing unacceptable trade distorting support to farmers. The trade distorting domestic support is measured in terms of what is called the “Total Aggregate Measurement of Support”, which is expressed as a percentage of the total value of agricultural output and includes both product specific and nonproduct specific support.

According to the AoA, all nonexempt domestic support calculated as Aggregate Measure of Support (AMS), has to be reduced by 20 percent by developed countries in 6 years (19952000) and by 131/3 percent by the developing countries in 10 years (19952004), taking 198688 as the base period. However, domestic support given to the agricultural sector up to a deminimus level of 10 percent of the total value of agricultural produce in developing countries and 5 percent in developed countries is allowed.

AMS is further classified into productspecific and nonproduct specific support. All the support/policies directed at producers of various agricultural products and provided on productbyproduct basis constitute the product specific AMS. These support measures can be classified into three broad categories namely Market Price Support, the Non exempt Direct Payments and other Product Specific Support. The only one measure that is relevant for the calculation of product specific support in India is the market price support since the other two namely the Nonexempt Direct Payments and other Product Specific Support do not constitute a significant proportion of support in India. The market price support in the form of minimum support prices is announced by the government for different commodities, based on the recommendations of the Commission for Agricultural Costs and Prices (CACP). The nonproduct specific support is the measure of support given to agriculture by way of subsidised supply of inputs such as fertilizers, irrigation, electricity, credit and seeds.

Gulati (2001) calculated that in case of India the product specific support in the year 199596 was negative to the extent of 38.5 percent. Bhalla (2004) has prepared a new set of estimates for both the product specific and nonproduct specific support to agriculture. The results show that the productspecific support is negative both at fixed price based on TE 198688 or even if current price base is taken (see Table 2). However, the nonproduct support that is input subsidies is positive (see Table 3). But they do not exceed the de minimus level either individually or in the aggregate. Since India’s total product support continues to be negative it has proposed to the WTO that the negative support should be offset against positive nonproduct support while calculating the AMS. No final decision has yet been taken on this issue.

Table 2: Product Specific Support for Selected Commodities in 199900 as % of Value of Output of Respective Commodity

Product Specific Support Item Fixed Price Base Current Price Base Rice 54.77 52.52 Wheat 97.25 8.56 Cotton 215.58 192.79 Sugar 10.04 41.39

Source: State of the Indian Farmer, Vol.19, Ministry of Agriculture, Government of India, May 2004

Table 3: Nonproduct Specific support as % of Value of Agricultural Output Items 199596 199697 199899 199900

Irrigation 1.58 1.59 1.52 1.44 Credit 0.07 0.07 0.04 0.07

Fertiliser 2.08 2.12 2.25 2.47 Power 3.97 3.90 4.09 4.58 Seed 0.00 0.00 0.01 0.00

Total non product support

7.70 7.67 7.90 8.57

Source: State of the Indian Farmer, Vol.19, Ministry of Agriculture, Government of India, May 2004

This notwithstanding, as of now India does not need to have any reduction commitment regarding its domestic support to agriculture. This is in sharp contrast with the developed countries that provide very high levels of support to their farmers.


IV. Impact of Trade Liberalisation on Production

From the above analysis, it appears that of the three commitments that India has given under the URA, at least two are unlikely to have any impact on Indian agriculture because: (i) India is not required to reduce its domestic subsidy levels, as its AMS being much below the cutoff point of 10 percent, being in fact negative in case of product specific; (ii) India has not subsidised its exports of agricultural commodities, and hence, it remains unaffected by the export subsidy reduction commitments. So the only commitment, which can affect Indian agriculture, is that of market access or tariffication of quantitative restrictions (QRs) for Balance of Payment (BOP) reasons. However, the BOP justification for India's continued use of QRs, has come under increasing pressure because of the increase in foreign exchange reserves. In the ExportImport Policy announced on 31 st March 2001, with the removal of quantitative restrictions on 715 items the obligation to replace QRs by tariffs has by and large been fulfilled.

When the QRs were abolished in 2001, there was an apprehension that Indian market would be flooded with cheap farm imports from the West. But that did not happen. India along with the removal of QRs simultaneously raised the tariff rates on many agricultural commodities in the late 1990s. The average agricultural tariff (excluding the special additional duty, or SAD) rose from 33.8 percent in 199798 to 41.7 percent in 200102. The majority of agricultural productrelated tariffs are in the 35 percent to 50 percent range. Hence, as international prices crashed in the late 1990s, imports did not increase significantly as import tariffs were adjusted upwards (World Bank 2004).

India’s agricultural export policies were progressively liberalised beginning in 1994, subject to occasional reversals. Export policies pertaining to agricultural products changed frequently, often several times a year, and therefore did not follow a general trend. The policy reforms include reductions in products subject to state trading, relaxation of export quotas, abolition of minimum export prices, and increased credit availability for exports.

India introduced export subsidies for cereals in early 2000. Government of India had to resort to export subsidies for rice and wheat as world cereal prices crashed to very low levels in the late 1990s. The decline in world prices coincided with increase in the domestic support prices for wheat and rice, which encouraged increased production

As a result of the upward revision of import tariffs and introduction of export subsidies on agricultural commodities, the level of trade protection increased for several major commodities in the late 1990s. Nominal protection coefficients (NPCs) represent the ratio of the domestic price to world price (the price of an exportable or importable commodity at the border). Estimates of NPCs for rice and wheat indicate that trade protection for them increased rapidly in the late 1990s (Gulati et al 2003) (see Table 4).

Table 4: Nominal Protection Rate for Selected Major Commodities in India Year Wheat* Rice* Sugar* Cotton* 1991 1.17 0.86 1.10 0.67 1995 0.97 0.82 0.84 0.98 2002 1.37 1.35 1.77 0.56

*Exportable Source: Gulati and others 2003.

Table 5 given below gives the trends of prices, production, exports and imports of the four major agricultural crops, which have been chosen for the study. Prices, the main economic indicator, which influences the production, exports and imports, have shown a more or less continuous rising trend between 199495 and 200304. The years have been selected to compare the situation between pre and postWTO period. While the rise in prices is steadier in case of wheat and rice, there have been some ups and downs in case of cotton and sugar. Nevertheless, there has not been any significant negative impact on prices as a result of agricultural trade liberalisation.

The production trend is also on the similar lines with some fluctuations in between but those are because of bad monsoons and not due to trade liberalisation (see figures 14). However, in case of cotton and sugar the fluctuation is more prominent but overall showing a positive trend. Again, the mains reason is bad monsoons as cotton in particular is produced largely in those parts of India, which have been facing droughts for the last few years.

In case of exports and imports, there is no consistent trend. We can clearly see the impact of our trade policy and the global situation. The imports of rice, wheat and sugar are very low in recent years because of high tariffs, which India is maintaining on the imports of these products. The only exception is cotton on which India has reduced its tariff considerably and world cotton market is highly distorted because of the huge subsidies given by USA and some EU countries to their farmers and exporters. As regards exports, rice has shown positive trend because India has niche


market of basmati rice in some regions/countries. The exports of wheat and sugar picked up in later years. Cotton exports have decreased in the postWTO period.

Table 5: Trends in Prices, Production, Export and Import of Major Agriculture Crops

Rice Wheat Cotton Sugar Year WPI Prod. Imp. Exp. WPI Prod. Imp. Exp. WPI Prod. Imp. Exp. WPI Prod. Imp. Exp.

199495 111 81.81 3 384.0 109 65.77 0 0.08 154 11.89 161.0 45.0 119 275.5 727.0 20.0 199899 146 86.1 0 1492.57 152 71.3 266.0 0.32 167 12.3 22.0 49.17 154 288.7 127.0 5.81 199900 171 89.7 7.0 721 175 76.4 179.0 00.0 147 11.5 289.0 18 156 299.3 256.0 9.0 200001 168 85.0 4.0 644 177 69.7 1.8 97.0 157 9.5 259.0 49 153 296.0 7.0 112 200102 167 93.3 2 666 175 72.8 1.4 278.9 149 10.0 431.0 9.0 146 297.2 6.8 374 200203 166 72.7 NA 1205 176 65.1 NA 363.6 142 8.7 256.0 10.0 135 281.6 6.8 375 200304 169 86.4 NA 799.7 181 72.7 NA 453.2 181 13.5 NA NA 139 244.8 9.2 258.3

Notes: 1. For the WPI (Wholesale Price Index) base year is 199394. 2. The value of production of rice and wheat is given in million tonnes 3. In case of sugar the production value is of sugarcane in million tonnes and data of exports and imports is of sugar. 4. For cotton the production value in measured in million bales of 170 kgs each. 5. The value of exports and imports is given in US$million. 6. The data of the year 200304 is estimated (third advanced estimates).

Source: Economic Survey 200304, Ministry of Finance, Government of India; Ministry of Agriculture, Government of India; and other sources.

Figure 1: Trend of Rice Production


Figure 2: Trend of Wheat Production

Figure 3: Trend of Cotton Production


Figure 4: Trend of Sugarcane Production

V. Sustainability Conditions in India

V.1 Economic Impact

The agricultural sector growth rate in India plays a crucial role in overall annual GDP growth. Even after more than fifty years of planed economic development and continued emphasis on rapid industrialisation, agriculture still accounts for over a quarter of total GDP in India. Its significance is even more in terms of employment generation and livelihood. Three quarters of the population is rural and 70 percent of rural households depend on agriculture for their livelihoods.

In view of these facts, it is necessary for agricultural sector to contribute significantly in total real income of India and simultaneously generate productive employment opportunities. For the agricultural sector to meet their high growth targets it is equally important to have a continuous rise in capital formation, which has become almost stagnant over the last two decades. These three issues have been discussed below.

Real Income: Though India has become selfreliant in terms of meeting its foodgrains requirements but because of the heavy dependence of Indian agricultural sector on monsoons the farm sector growth rate does fluctuate a lot. This fluctuation in the growth rate of foodgrains productions in India has a direct bearing on the annual GDP growth. Table 6 given below shows the link between agricultural sector growth and the growth rate in the total GDP. The period from 199697 to 200304 coincidently also coincides with the implementation of the WTO AoA.


Table 6: Growth rates of GDP and Agriculture Production (Percent) Year GDP* GDP in Agriculture & Allied

Sectors* Physical Production of

Agriculture*** 199697 7.8 9.6 9.3 199798 4.8 2.4 5.9 199899 6.5 6.2 7.6 199900 6.1 0.3 0.6 200001 4.4 0.1 6.3 200102 5.8 6.5 7.6 200203 4.0 5.2 15.6 200304** 8.1 9.1 19.3

*At factor cost at 199394 prices **Advance estimates ***As determined by index of agricultural production (Base: triennium ending 198182) Source: Economic Survey 200304, Government of India

Gross Fixed Capital Formation (GFCF): Capital formation is one of the most crucial factors for increasing production. This is particularly more important for Indian agriculture where we are faced with the task of increasing production to keep pace with the ever rising population against the odds of the vagaries of monsoon. A strong capital base is required to make sustainable use of natural resources, for adoption of advanced technology and development of infrastructure for facilitating all agricultural activities. In other words capital formation is necessary in order to make agriculture a profitable commercial activity at par with other industries in the arena of global economy.

According to the Report of the Committee on Capital Formation in Agriculture (2003), set up by the government of India in 2001, agricultural development cannot be ensured by confining attention to the activities with in the boundaries of agricultural fields. It should encompass activities fully or partially meant for agriculture such as production of fertilizers and pesticides, development of agriculture markets, rural roads and communications; augmentation of facilities for agricultural credit for small and marginal farmers, agricultural education, research and development of agricultural technology which are the main source of increasing production under the limited availability of natural resources. Therefore, for monitoring agricultural growth it is necessary to have a broader measure of agricultural capital formation that includes capital formation in all these activities, which can be called capital formation for agriculture in comparison with capital formation in agriculture.

The Report (2003) finds that there has been a continuous decline in the share of agriculture sector’s capital formation in GDP. This is great cause of concern for India. The broad trends in both GFCF in agriculture and for agriculture are similar during the period 198081 to 200102. As percent to GDP, GFCF in agriculture has declined from 3.4% in 1980 81 to 1.6% in 200102. The corresponding share of GFCF for agriculture has also halved during this period. The deceleration has been more pronounced in the 1980s as compared to the 1990s. These can be seen from Table 7 below:

Table 7: GFCF in and for Agriculture at 199394 Prices (Rs. Crore)

GFCF Percent Share in GDP of GFCF

Year GDP in Agriculture

For Agriculture in Agriculture for Agriculture

(1) (2) (3) (4) (5) (6) 198081 401128 13721 17279 3.4 4.3 198586 513990 13061 17656 2.5 3.4 199091 692871 15805 21560 2.3 3.1 199596 899563 16824 25283 1.9 2.8 200001 1198685 18364 27946 1.5 2.3 200102 1265429 19880 28830 1.6 2.3

Note: 1 crore = 10 million Source: Report of the Committee on Capital Formation in Agriculture, Submitted in March 2003, Ministry of Agriculture, Government of India

The Report (2003) also finds that the share of GFCF in public sector in agriculture has declined in relation to GDP. The same is true of public sector GFCF for agriculture. There has been, therefore a longterm deceleration in the share of capital formation in agriculture in GDP at both aggregate and public sector level. In fact the shares of GFCF in


agriculture and for agriculture in GDP have declined much more sharply in the public sector, as would be evident from the Tables 7 & 8.

Table 8: GFCF in and for Agriculture at 199394 Prices (Public Sector) (Rs. crore)

Note: 1 crore = 10 million Source: Report of the Committee on Capital Formation in Agriculture, Submitted in March 2003, Ministry of Agriculture, Government of India

GFCF in agriculture now accounts for less than 10% of total GFCF. The ratio seems to have declined very sharply during the 1980’s. In the last few years there has been some improvement in the share of agriculture in total GFCF, however, in spite of this it is still well below what it was in the early 1980’s. The same is true of GFCF for agriculture.

Currently, GFCF for agriculture at 199394 prices account for about 12% of aggregate capital formation. As against this, the share of agriculture in GDP is currently about 24% clearly there is a strong case to increase the share of agriculture in total capital formation in the economy. Even in the case of Public Sector, the share of agriculture in total Public Sector capital formation has declined over the years.

As agriculture is getting diversified, there is a need to not only augment but also restructure the pattern of investment in agriculture. Historically, the Public Sector has taken the lead in directing the growth and pattern of agriculture investment. Keeping in view of the changed global scenario, the Committee recommends that

• Immediate steps should be taken to improve capital formation for agriculture in both Public and Private Sectors. Otherwise, it may be difficult to sustain the agriculture growth and rural purchasing power.

• Currently, irrigation accounts for the bulk of public investment in agriculture (above 90%). The new strategy of agriculture growth and diversification of agriculture from traditional crop cultivation to horticulture etc. would require more investments on cold storage, rural roads, communication, marketing network and facilities, warehouses etc.

• Simultaneously efforts should be made to revitalize agriculture through introduction of biotechnology and other innovations. This would require substantial increase in investment on research & development for agriculture.

Employment: Agriculture accounts for just under 60% of total employment and as a result growth and development in this sector have significant impact on the overall employment situation in the economy. However, at the same time it must be recognised that agriculture is not a sector where Indian policy makers are looking for a large increase in total employment generation. On the contrary, agriculture has traditionally served as a residual employer, and is therefore characterised by considerable underemployment, disguised unemployment, seasonal variation in employment and relatively low real wages. The longerterm employment strategy should therefore aim at absorbing as much of the expansion in the labour force as possible in the nonagricultural sector, thus reducing the pressure of labour on land and thereby tightening the labour market, so that incomes per head in farming and real wages of agricultural labour rise significantly.

The relationship between growth of GDP and growth of employment is usually characterised by a summary parameter such as the elasticity of employment with respect to GDP, which can be calculated either for employment in the economy as a whole or for employment in individual sectors. Table 9 presents Planning Commission of India’s estimates of employment elasticities for the agricultural sector, and also for the economy as a whole, based on data on employment growth and GDP growth for three different periods spanning the past two decades.

GFCF Percent Share in GDP of GFCF

Year GDP in Agriculture

for Agriculture

in Agriculture

for Agriculture

198081 401128 7358 9855 1.8 2.5 198586 513990 6005 9224 1.2 1.8 199091 692871 4871 8706 0.7 1.3 199596 899563 5318 9631 0.6 1.1 199900 1148442 4637 9902 0.4 0.9


From the data given below in Table 9, it is evident that during the period 199394 to 199900, the initial years of implementation of WTO AoA, employment elasticity in agriculture sector reduced to zero. It means increase in agricultural output during this period did not result in any increase in employment. The data given in Table 10 confirms this result. We see that during the period 199394 to 199900, employment in agricultural sector has actually gone down in absolute numbers, showing a negative growth of –0.34 percent.

Table 9: Elasticity of Employment to GDP in Agricultural Sector and All Sectors Period Estimated Elasticities in Agriculture* All Sectors

197778 to 1983 0.45 0.53 1983 to 199394** 0.50 0.41 199394 to 199900 0.00 0.15 Projected

As used in 9 th Plan projections 0.50 0.38 Projected for the future 0.10 0.22***

*Estimated elasticities for agriculture have been calculated on the basis of 3 year moving average of GDP at 198081 prices for the period 197778 to 1983 and 1983 to 199394. For the period 199394 to 199900 the GDP series with base 199394 have been used but a threeyear average is not used since data are not available for 199293 or 200001. **This period combines two distinct periods for which data are separately available i.e. 1983 to 198788 and 198788 to 199394. However, 198788 was a drought year when employment was abnormally low and this distorts elasticities in both periods. The combined period 1983 to 199394 has been used to avoid this distortion. ***Implicit elasticity based on 6.5% GDP growth. Source: Report of the task force on employment opportunities, 2001, Planning Commission, Government of India.

Table 10: Growth of Employment in Agriculture and Total Employed workers (million) Annual growth rate (%)

Sectors 1983 199394 199900 198394 199400 Agriculture 207.23 242.46 237.56 1.51 0.34 Total Employment 302.76 374.45 397.00 2.04 0.98 Source: Report of the task force on employment opportunities, 2001, Planning Commission, Government of India.

V.2 Social Impact

The true benefits of trade liberalisation in agriculture cannot be realised unless it leaves a positive mark on social sectors. In Indian case it is more important as majority of poor are dependent on agriculture for their subsistence. Therefore, it is very crucial to see the impact of agricultural sector liberalisation on social indicators such as poverty, health & education, and equity.

Poverty: Ever since the Uruguay Round AoA kick started trade liberalisation in agriculture in 1995, there has been a considerable concern in India about its implications for more than 600mn people who are dependent on farming for their livelihood. This is particularly true for products like rice, wheat, cotton and sugar, which are the lifeline of not only majority of rural people but products like Cotton and sugar provide employment to a significant proportion of urban population as well.

As of 199900, India's poverty continues to be predominantly rural although rural poverty declined faster than urban poverty over the last twentyfive years. Moreover, the decline in national poverty seems to have been driven mostly by the decline in rural poverty — not surprising given that 74 percent of India's population lives in rural areas. The decline in poverty is remarkable during the period 199394 and 199900 when the rural poverty went down by almost 10 percentage points in comparison to the 7 percent fall in combined (rural and urban) poverty ratio (see Table 11).


Table 11: Estimates of Incidence of Poverty in India

Year Poverty ratio (percent) No. of poor (million) Rural Urban Combined Rural Urban Combined

197778 53.1 45.2 51.3 264.3 64.6 328.9 1983 45.7 40.8 44.5 252.0 70.9 322.9

198788 39.1 38.2 38.9 231.9 75.2 307.1 199394 37.3 32.4 36.0 244.0 76.3 320.3 199900 27.1 23.6 26.1 193.2 67.1 260.3 2007* 21.1 15.1 19.3 170.5 49.6 220.1

*Poverty projection for 2007 Source: Tenth FiveYear Plan, Planning Commission, Government of India

This period 199394 to 199900 roughly coincides with the early years of implementation of WTO AoA. But how much this fall in poverty ratio in this period can be attributed to trade liberalisation undertaken by India to fulfil its obligations under AoA, is a matter of debate and further research. As far as India’s commitments under AoA is concerned it did not have to bring any major change in its existing policies except the removal of quantitative restrictions on imports. In the previous section we have seen that out of three pillars of AoA, India is not required to undertake any cut in its domestic support and export subsidies. While the exiting domestic support level is well below the permissible limit the export subsidies are not provide in India.

Health and Education: At present over 250 million Indians live in absolute poverty with majority of them in rural areas. According to the year 2002 report of Human Development in South Asia about 225 million Indians are chronically malnourished (see Table 12). This crisis of food insecurity in India is largely related to poor access rather than nonavailability of food as shown in table given below that per capita dietary energy supply, has been rising in India. The per capita dietary energy supply increased from 2370 Kcal per day in 199092 to 2430 Kcal per day in 1997 99. However, severe inequality in land and income distribution prevents the poor from reaping the benefits of increased food availability. The total number of undernourished increased from 215 million to 225 million during this period.

Table 12: Per Capita Availability of Dietary Energy Supply and the No. of Undernourished People in India

Year No. of Undernourished (Mn) Per Capita Dietary Energy Supply (Kcal/person/day)

199092 215 2370 199799 225 2430 Source: The State of Food Security in the World, 2001, Food and Agriculture Organisation, Rome

As evident from the table, neither the economic liberalisation of 1991 nor the little policy changes brought as a result of WTO AoA brought any positive change in the prevailing situation. Hunger and food insecurity are still widely prevalent and more so in rural areas. They are largely responsible for poor health indicators of India. Table 13 shows the trend of selected health indicators during the last decade. Although they are progressing in positive direction but the situation is alarming. The high infant mortality rate and maternal mortality rate are really a cause of concern.


Table 13: Selected Health Indicators Parameter 1991 Current

Level Crude Birth Rate (Per 1000 Population) 29.5 25.0 (2002*) Crude Death Rate (Per 1000 Population) 9.8 8.1 (2002*) Total Fertility Rate (Per woman) 3.6 3.2 (1999) Maternal Mortality Rate (per 100,000 live births) NFHS 437 (199293) 407 (1998) Infant Mortality Rate (Per 1000 live births) 80 64 (2002*) Child (04 years) Mortality Rate Per 1000 children 26.5 19.5 (2000) Couple Protection Rate (Percent) 44.1 48.2 (199899)

NFHS Life Expectancy at Birth Male 59.7 (199195) 63.9 (200106) Female 60.9 (199195) 66.9 (200106) .Note: The dates in the brackets indicate years for which latest information is available. NFHS: National Family Health Survey; *Provisional Source: Ministry of Health and Family Welfare, Government of India.

As regards education, in the five decades after independence, the increase in literacy rate during the decade 19912001 has been the highest, i.e., from 5221 to 64.84 percent, which is an increase of 12.6 percentage points (see Table 14). For the first time, the country witnessed a faster growth in female literacy compared to that of males. As a result there has been a narrowing of the gender gap in literacy, which was 25 percent in 1991 and to 22 percent in 2001. There is also, for the first time, a converging trend in the ruralurban literacy gap has been observed. According to the Economic Survey 200304, between 1991 and 2001 rural literacy increased by 7 percent, thereby reducing the urbanrural gap from 28.4 percent in 1991 to 20.9 percent in 2001.

Table 14: Literacy Rates in India (19512001) Census Year Persons Males Females Gender Gap

1951 18.33 27.16 8.86 18.30 1961 28.30 40.40 15.35 25.05 1971 34.45 45.96 21.97 23.98 1981 43.57 56.38 29.76 26.62 1991 52.21 64.13 39.29 24.84 2001 64.84 75.85 54.16 21.69

Source: Census of India

V.3 Environmental Impact

Agriculture is the most dominant landusing activity. With the increase in population and the rise in demand for foodgrains, agriculture encroaches further into forests and fragile areas, resulting in destruction of ecosystem and adverse impact on all forms of life. Undoubtedly, in case of India the population pressure has been causing serious threat to the sustainable use of land, water, and other natural resources. In India, over the last three decades, there has been a severe squeeze on the available land resources. In order to increase productivity to meet the food requirements of teeming millions there has been a sharp increase in the use of chemical fertilisers, pesticides, insecticides and High Yielding Varieties of seeds. Here we are analysing the impact of agricultural sector development on biodiversity and land degradation.

Biodiversity: Being a tropical country, India is characterised by a complex mosaic of distinct agroecosystems, differentiated by their climatic, soil, geological, vegetational, crop growing and other features. With the advent of Green Revolution in the mid1960s, a handful of laboratorygenerated varieties of seeds have been promoted over vast areas, particularly in the plains of Northern India. Given certain inputs such as irrigation and chemical fertilisers and pesticides, these varieties of seeds produce high yields. The extensive use of various agricultural inputs, thereafter, resulted in homogenising of growing conditions. Where there was earlier a complex mosaic of diverse microhabitats, now there are immense stretches of uniform agricultural landscape. Intercropping is replaced by monocropping resulting in replacement of a wide variety of species by a handful of profitable ones. Further, the genetic diversity


within the same crop species is replaced by a narrow genetic range of financially lucrative varieties. The net effect of these and other practices has been a massive displacement of indigenous crop diversity.

At present, there is no available figure for the overall loss of crop diversity in India and for the world as well. Some idea can be gauged by the fact that a handful of HYVs are now grown over 70 percent of paddy land and 90 percent of the wheat land of the country. Thousands of varieties of cereals (rice, wheat etc.), cotton and other crops are no longer in use on farms.

The 1990s have seen a major shift in India's economic policy, away from goals of selfsufficiency and public sector towards an 'open' economy and privatisation. In the field of agriculture, there has been an aggressive thrust towards commercial farming, especially to feed an insatiable export market. Cash cropping, already a threat to the smallscale biodiverse farm, has been given a major boost. New trends include floriculture, industrial aquaculture, and other forms of intensive farming, which leave little scope for biologically diverse production systems.

The parallel move towards more hightechnology agriculture makes the country as a whole also more insecure, as it increases its dependence on biotechnologies controlled by industrial countries and multinational corporations. The entry of Cargill, Cieba Geigy, Monsanto, McGain and other globally powerful companies into India's seed and agroproducts sector is a major step towards this crippling dependence, and a direct reversal of policies, which had all this while tried to take us towards selfreliance.

Apart from the ecological risks, one aspect, which has been less focused on, is the fact that most such biotechnologies are likely to remain beyond the reach of the small farmers. This is also adversely impacting on the livelihoods of the small seed manufacturer, who along with farmers themselves still serve the majority of the seed needs of Indian agriculture. These developments can only deal a further blow to farmer selfsufficiency. This process of homogenisation of agriculture, and increasing dependence on alien agencies and technologies, is likely to be greatly intensified in the coming years.

Furthermore, the provisions in the WTO TRIPs (TradeRelated Intellectual Property Rights) agreement, especially those seeking to harmonise IPR regimes across the globe and to enforce patentability of life forms, are forcing changes in the Indian Patent Act and related legislation. This could have severe implications for biodiversity and farmers' rights. IPRs are expensive, and corporations would try to push their protected seeds over as wide an area as possible to recover costs and make profits. Further displacement of traditional diversity and homogenisation would result. Additionally, innovations by farmers, which result in expanding diversity, may be hindered if IPR regimes favour the formal sector breeder at the cost of the farmer.

Land Degradation: Land degradation in India has been caused by both – poverty and development. The poverty environment nexus postulates that due to lack of alternative incomegenerating options poor are dependent on biomass based resources, which lead to accelerated depletion of such resources. However, there is a counterargument suggesting that, given the very fact that the poor depend on biomass based resources for their sheer survival, they would not overexploit such resources (Chadha and others, 2004).

The development led degradation of land has been caused by overcultivation of crop land, deforestation, overgrazing, excessive use of chemical fertilisers and pesticides, waterlogging and salinisation of irrigated land, industrial pollution and its associated consequences. Overgrazing, deforestation, and overcultivation of cropland can be induced both due to povertyrelated reasons and developmental reasons. However, waterlogging/salinisation and industrial pollution are linked primarily to developmental reasons.

In case on India, soil erosion is the most serious cause of concern as India is under increasing pressure to raise the farm productivity in order to meet the food requirements of over 1 billion people. Table 15 below summarises the soil degradation situation in India during mid1990s.

Table 15: Situation of Soil Degradation in India Classification of Indian Soil Degradation Area (Mha) Percent Water Erosion Loss of top soil 132.5 40.3 Terrain deformation 16.4 5 Wind Erosion Loss of top soil 6.2 4.1 Terrain deformation/overblowing 4.6 1.9


Chemical Deterioration

Loss of nutrients 3.7 1.1 Salinisation 10.1 3.1 Physical Deterioration

Waterlogging 11.6 3.5 Land not fit for agriculture 18.2 5.5 Soils with little or no degradation 90.5 27.5 Soils under natural condition 32.2 9.8 Total 328.7 100.0

Source: Sehgal, J., and I. P. Abrol. “Soil Degradation in India: Status and Impact”, Oxford & IBH Publishing Co., 1994, New Delhi.

VI. Significance of Impact

In the previous section we analysed the sustainability conditions in India during the implementation of the Uruguay Round AoA, i.e., from 1995 to 2004. The analysis was more focused on the early years of implementation period because of the lack of availability of data for later years. As per the WTO AoA the implementation is supposed to be completed by the end of 2004. The situation, however, changed owing to the poor progress of Doha round of trade negotiations and nonfulfilment of commitments by developed countries. The developed countries had to implement their part of obligations by the end of 2000.

In the meanwhile a new development took place in July 2004 at Geneva when 147 WTO members reached upon a framework agreement called “July Package” which brought the bewildered Doha round back on track and extended the deadline of the completion of Doha round to 2005. Nevertheless, for the purpose of this study we will consider the impact of partial trade liberalisation, taking the current situation as baseline scenario (reflecting the situation that would prevail without a new WTO agreement on agriculture). The partial liberalisation scenario will be examined for assessing sustainability impact in each of the three aspects, viz, economic, social and environmental.

The three components of the partial liberalisation scenario are: (a) Tariff reductions – As per the Derbez text developed countries will be expected to reduce tariffs by 36 percent. Developing countries will be expected to reduce tariffs by 24 percent (subject to a maximum postliberalisation tariff of 40 percent). Least developed countries (LDCs) have no reduction commitments. (b) Reduction of export support – The scenario for this pillar assumes that developed countries eliminate all forms of export support, developing countries eliminate 50 percent of export support, and LDCs have no commitments. (c) Domestic support – The trade measure in the scenario for this measure will be reductions of 60 percent in tradedistorting domestic support for developed countries, 40 percent reductions for developing countries, and no reductions for LDCs.

VI.1 Economic Impact Assessment

As repeated several times, out of the three pillars of the AoA, India’s commitments lies only in case of tariff reductions. Till now much of Indian agricultural policy, and fear of market oriented reform, is based on the perception that reducing import barriers will increase domestic price volatility and threaten livelihood of millions of small and poor farm producers. Therefore, it is primarily because of this reason India has been maintaining high average tariff rates on its farm imports.

India has never been a major foodgrains exporter as all along its prime concern was how to protect its millions of small and marginal farmers. In WTO agriculture negotiations unlike Cairns group India stance has remained defensive. India preferred to seek concessions in order to protect its domestic farm producers rather than seeking greater market access. However, whichever formula is chosen for tariff cuts, India will have to reduce her existing average bound tariff rates on agricultural products.

As a result of these possible tariff reductions, the actual picture is not easy to predict because of various government interventions and distortions that may influence both input and output prices. However, in this section we try to analyse how the future trade liberalisation in agricultural sector would impact on major crops like rice, wheat, sugarcane and cotton and in turn on the overall agricultural growth.


Rice: One of the important developments of the last one decade in Indian farm export landscape is the emergence of rice as an important export crop. Although the export trend of rice is not consistent but it shows much promise. The Arkansas Global Rice Model 2 , for instance, predicts that, in 2010, India would be one of the major net exporters of medium and longgrain rice along with Thailand, Vietnam, US and Pakistan. This reinforces the existing trade patterns (Gulati & Naraynan, 2003).

At present, rice sector in both developed and developing countries attracts a high level of government intervention. While developed country importers such as Japan and Korea insulate their rice markets through heavy border protection, exporters such as the US and EU resort to export support to make their rice more competitive in the world market. A developing country like India is cautious in liberalising rice trade for the sake of food security. Exports of common rice from India were banned until 1994. India also maintains high bound and applied tariff rates of 80 percent.

The high degree of intervention in rice sector worldwide has led to great diversity in rice price levels across countries and has created a huge distortion in world trade of rice. In fact, it is argued that rice markets are so distorted that countries compete less on productivity gains or efficiency and more on policy levels that make their exports competitive (Tabor et al 2002). Now the question arises, how would the liberalisation of rice trade impact on the competitiveness of different countries and particularly India in this case?

If we go by the value of nominal protection coefficients (NPCs), India, having NPCs of less than one, is likely to be competitive (see table). Therefore, it is expected that India would emerge as one of the important net exporters if further trade liberalisation takes place in rice sector, while the richer countries such as Japan, Korea and the EU would be net importers (Gulati & Naraynan, 2003).

Sugarcane: India is a competitive country in the international sugar market. But, it has not been able to secure a reasonable share in world sugar trade. The EU and other countries, in spite of their higher costs of production, have been exporting sugar at much lower prices because of higher support given to the sugar industry in their countries by the respective governments. In India the export price of white sugar, which was 409 per tonne in January 1996 has come down by almost 50 percent to 210 per tonne in January 2003. This has also affected the India domestic prices of sugar (Gawli, 2003).

The studies done by LMC International of UK and ABARE of Australia find that if the international sugar market becomes fully free and fair the following likely situations would emerge:

• The overall prices will rise by 38 percent. Prices in Japan will increase by 60 percent, in Western Europe by 40 percent, in Eastern Europe by 25 percent and in China, Philippines and Ukraine prices will come down by 10 percent.

• Europe, the US, Japan and Indonesia will have to increase imports by 15 million tonnes. • The international sugar industry will shift from inefficient regions to efficient regions.

In the emergence of such scenario, India will be one of the major beneficiaries of a free and fair international sugar market. The present direction of India’s sugar policy is also based on the assumption that the global sugar industry is becoming free and fair and that all types of government support and market intervention are being dismantled.

Wheat: In case of wheat, the results of a study done by Naik (1999), which uses Domestic Resource Cost (DRC) 3 analysis to evaluate its international competitiveness, find that wheat production in the major wheat producing states in India is internationally competitive. This includes Punjab, Haryana and Rajasthan, which are competitive in all years (199596 to 199899), showing DRC less than 1. Thus, wheat production in India is likely to remain internationally competitive even after further trade liberalisation.

Cotton: As regards cotton, the sector is in deep distress, thanks to the combined effects of draught, increasing cost of cultivation, declining subsidies and removal of import restrictions. At present imports are conducted under the Open General License (OGL) system, which are free and unrestricted by time or quantity, with a nominal import duty of 10 percent. In India, there have been no subsidies for cotton production since 2003. At the same time, it must be emphasised that the prices of cotton in the world markets are highly distorted as a result of production subsidies in some of the developed countries. The US, for example, has an annual cotton farm subsidy programme amounting to $3billion,

2 A framework that provides short and longrun projections of the international rice economy and analysis of market and trade polices 3 A coefficient of less than one indicates that production is internationally competitive.


which is separate from its export subsidies. These are direct payments to producers and not related to yields or prices. US production costs are $1.70 per kg but its cotton is sold at $1.18 per kg (Cariappa and Cariappa, 2004).

In Europe, Greece, Spain and Turkey supported their farmers with subsidies of $718mn, $239mn and $57mn respectively in 200203. In china import is not free and is based on a quota system that is regulated according to needs and requirements. Further, the imports are time restricted to protect domestic markets (Cariappa and Cariappa, 2004).

The likely elimination of unfair farm subsidies might help in mitigating the distress of Indian cotton farmers.

Thus, in aggregate, the net economic impact of future trade liberalisation of world agricultural trade is likely to be beneficial for India, though may not as significant as needed in the short run. However, there might be some sectors, which would require greater protection such as oilseeds, cotton, etc.

VI.2 Social Impact Assessment

Based on the experience of economic and trade liberalisation undertaken since early 1990s, the benefits seem to have gone more in favour of large farmers than the small ones. The regional disparity has also increased further during 1990s. Agricultural trade liberalisation in order to have a positive social impact must bring institutional changes and ensure the growth and development of those crops and regions that can have direct impact on generating employment and in turn reducing poverty.

Out of the four crops under study, rice trade liberalisation has potential to have significant impact on poverty, closely followed by sugarcane, cotton and wheat. Except wheat, all the other three crops have high average labour use (man days per ha) in production. While sugarcane uses an average labour use of 190 mandays per ha, rice and cotton have an average labour use of 105 and 100 mandays per ha respectively. Wheat has very low average labour use of only 55 mandays per ha (Government of India, 2000 and Subramanian et al 2000).

In case of rice, empirical evidence shows that countries that are competitive stand to gain substantially from trade liberalisation. Deaton (1989), for instance, observed that an increase in rice prices as a result of trade liberalisation in Thailand would benefit all rural households. More recently, Minor and Goletti (1999) predicted, using a spatial equilibrium multimarket model, that the elimination of rice export quota in Vietnam would raise prices by 14 to 22 percent on average, and can be expected to reduce both the incidence and depth of poverty. According to Gulati and Naraynan (2003), a similar positive linkage between the rice prices and wages exists in India. In India the rice trade liberalisation can bring greater benefits, as the larger share of rice production comes from regions, which are extremely poor such as Uttar Pradesh, Bihar, West Bengal, Orissa, Andhra Pradesh etc.

Another factor, which can cause positive impact on employment generation and poverty eradication, is crop diversification resulting from the trade liberalisation. Joshi and others (2004) argues that area shift from cereals to vegetables would generate substantial employment opportunities in rural areas. Rough estimates suggest that 1 ha shift in area from wheat to potato would generate 145 additional mandays. Similarly, 1 ha area shift from coarse cereals (sorghum and pearl millet) to onion would generate 70 mandays more employment opportunities in rural areas. Generating additional employment in rural areas has welfare and equity implications.

Overall, the social impact of trade liberalisation is likely to be a mixed one. Trade liberalisation can result in high agricultural growth rate but it does not ensure growth with equity. There are possibilities that it may lead to further widening of gap between small and big farmers and developed and underdeveloped regions. This may happen because of rise in cost of production because of mechanisation, which our small farmers cannot afford. The backward regions like Bihar, Assam and Uttar Pradesh may suffer because of insufficient investment in agricultural sector.

VI.3 Environmental Impact Assessment

It is not easy to analyse the environmental impacts of future agricultural trade liberalisation in Indian case, as there is no direct relationship between trade liberalisation and environmental degradation. However, the continuing loss of topsoil as a result of land degradation is almost certain to cause adverse impact on farm production. Theoretically, we may argue that trade liberalisation increases world prices and demand, which creates incentives to improve yields through better land management.

In case of India the agricultural trade liberalisation can bring both opportunities and risks for the environment. The sudden increase in demand through the opening up of world agricultural market may force Indian farmers resort to


excessive use of chemical fertilisers, pesticides, and insecticides for increasing production through high yields. This will result in further degradation of environment. However, the opening up of the international trade under WTO is opening vistas that appear to favour organic farming. The burgeoning European and US green markets provide enormous scope for Indian exporters. The market for bio food is still rather limited but it is expanding rapidly at the rate of almost 20 to 25% per year. Further, consumers appear to be prepared to pay 2025% higher price for health food.

Over 40% of Indian agricultural lands have remained untouched by any kind of chemical fertilizer or pesticide during the last 35 years of green revolution era. India thus has large areas that are genuinely free of chemical pollution and are ideally suited for use of organic farming. India can play a dominant role if it can marshal its virgin lands to produce food grains, fruits, etc. for the rapidly expanding domestic and global market for organic food. India is best known as an exporter of organic tea but also has great export potential for many other products such as rice, cotton, wheat and fruits & vegetables. The agricultural trade liberalisation can help in exploiting these potentials.

SIA Matrix of Results Impacts of TradeRelated Agriculture Measures in The WTO

Significant Impacts Impact On Baseline Scenario Liberalisation Scenario

A B C A B C India 0 0 0 +1 +1 +1

Notes: A = Economic Impacts B = Social Impacts C = Environmental Impacts Scoring: 0 = nonsignificant impact compared with the base situation 1 = lesser significant impact 2 = greater significant impact + = positive impact + = positive and negative impacts likely to be experienced /+ = negative over an initial (specified) period of time but expected to become positive in the longer term

VII. Intra and Intersectoral Linkages

The Indian agricultural sector in postliberalisation phase has witnessed crop substitution in favour of high value commodities such as fruits, vegetables, livestock and fisheries. According to Joshi and others (2003) the agricultural sector in India now ranks as the most diversified in the South Asia. Using the Simpson Index 4 for measuring the degree of diversification, they estimated that in the year 19992000 India had a crop diversity index of 0.66, closely following Maldives (0.77) and Sri Lanka (0.75). This increased diversification has been strongly influenced by price policy, increased export opportunities, infrastructure development, urbanisation and technological improvements. Further, the increased diversification came primarily as a result of crop substitution rather than increased cropping intensity.

Within India, the Southern and Western regions posted the highest degree of crop diversification as measured by the Simpson Index. Notably, during the 1990s, the Southern region also recorded faster agricultural growth rates than the national average. On the ground this growth rate translated to the rapid shift away from food grain crops toward oilseeds, pulses, maize, sugarcane, fruits, vegetables, and other crops. In contrast, the Northern region continues to specialise in foodgrains, particularly rice and wheat, well encouraged by favourable government price support policies.

Increasing agricultural diversification is opening new export avenues and labour opportunities. Agricultural diversification contributed to changing significantly the composition of Indian agricultural exports, expanding from traditional exports of tea, spices, and coffee to horticulture, fisheries and livestock products. Agricultural diversification is also helping to generate additional employment opportunities in rural areas, especially since the labour requirement of noncereal crops is substantially higher than cereal crops.

Indian agriculture heavily depends upon the vagaries on monsoons. But this increase in agricultural diversification is mitigating the impact of weather related shocks in some regions. For instance in Andhra Pradesh, the agricultural and

4 The index provides a clear dispersion of commodities in a geographical region. The index ranges between 0 and 1. If there exists complete specialisation, the index moves towards 0.


allied sector’s reasonable growth rate in the recent past was bolstered very much by the rapid growth in the livestock and fisheries sector.

As regards intersectoral linkages, the rural nonfarm sector and agrobased industry are slowly gaining importance as a source of supplementary rural activities and income. According to a survey of 16 states conducted in 199394, the non farm sector on average accounted for onethird of rural household incomes (Lanjouw and Shariff 2000). Given the increasing pressure of population on agriculture and rise in disguised unemployment, the rapid growth of rural nonfarm sectors is very crucial.

The expansion and growth of agrobased industries hold an added significance in generating high value employment in rural areas. The agrobased industries have been an important component of the industrial sector in India. Between 199495 and 200001, the share of agrobased industry in total industrial units increased from 65 percent to 82 percent. In absolute number the agrobased industrial units increased by 4.5 million units. Out of this the foodprocessing category increased by 1.3 million, the second largest after textiles. However, its share in total manufacturing value added decreased from 36 percent to 32 percent over the same time period (World Bank 2004).

VIII. Policy Preparedness to Face WTO Challenges

At present, India is not a major exporter of farm products. The share of agriculture in its total exports has continuously declined over the last two decades. In 1980, the sector had approximately 30 percent share in total country exports, which came down to 18 percent in early 1990s and declined further to 14 percent currently. India, however, is considered to be one of the major potential farm exporters as the WTO AoA was expected to bring about significant increases in trade in agriculture and to specially benefit the developing countries. The withdrawal of subsidies by the developed countries is expected to raise prices of agricultural commodities and make developing countries’ exports competitive.

On the other hand, the opening of all barriers to agricultural trade is likely to pose some critical challenges. The first daunting challenge for a country like India will be to find institutional mechanisms for protecting their millions of small and marginal farmers who constitute an overwhelming majority of cultivators. Another likely challenge emanates from the fear that excessive imports could adversely affect local production, thereby, seriously jeopardising the livelihood of the very large workforce engaged in agriculture.

Keeping in view of the above mentioned threats, the future negotiations on AoA in the WTO must endeavour to make Special & Differential Treatment (SDT) for developing countries, both in countries’ new commitments and in any relevant new or revised rules and disciplines. The new S&DT should be effective in practice and should enable developing countries meet their needs, in particular in food security and rural development.

The domestic policy changes must follow the developments, which are taking place at WTO. Since the philosophy behind trade liberalisation is the maximisation of global welfare through efficiency gains, mapping out comparative advantages across countries for different commodities in a dynamic setting is necessary as a basis for meaningful negotiations in the WTO. The Developed countries are very well equipped with technical and legal expertise, even though these capabilities are used for advancing their case towards perpetuation of domestic support to agriculture and restriction of market access, that are quite untenable. On the other hand, the capabilities of developing countries, including India, are poor in this respect despite their approach and line of action on matters relating to agricultural trade being justifiable on theoretical as well as practical grounds. Therefore, there is a need to give a high priority to the development of these skills in the country (Rao 2001).

On the domestic front, a major effort is required for raising the farm sector productivity by stepping up public investment, by accelerating the evolution and adoption of costreducing technologies, and by removing restrictions on agricultural trade, marketing processing within the country. All this requires to be achieved through major reforms in governance and institutions, particularly at the state level. The investible resources with the government have to be raised (Rao 2001).

In order to protect the interests of small holders, there is a need to undertake some important institutional reforms like the consolidation of land holdings, and giving tenancy rights to existing occupancy tenants. Further, cooperative farming and innovative institutions like integrated cooperatives such as the mother dairy (a milk cooperative), contract farming, etc. should be encouraged to involve the small farmers in the process of production and diversification.

In September 2000, the Government of India appointed a Task Force on Agriculture (TFA) to assess the impact of WTO commitments on Indian agriculture and to suggest steps to safeguard the interests of the sector, while exploiting


the opportunities presented by this treaty. The TFA in its final report submitted in August 2001 came out with some very interesting findings. It highlighted the practical difficulties (Box 1) in the form of structural defects and deficiencies of the Indian economy, which are hampering the prospects of farm exports. The TFA also identified few virgin areas where India can reap advantages in international market (Box 2).

Source: Report of the Task Force on Agriculture, Ministry of Agriculture, Government of India, August 2001.

Source: Report of the Task Force on Agriculture, Ministry of Agriculture, Government of India, August 2001.

Box 1: Practical difficulties The prospects of agricultural exports are rendered bleak because of certain structural defects and deficiencies of the Indian economy and of the agricultural environment:

§ A serious practical difficulty arises out of the infrastructural weakness. The farmgate prices in India mark a substantial comparative advantage. But, by the time the produce is packaged and transported to port of embarkation most of the advantage gets eroded.

§ The land reforms legislation including tenancy laws and ceiling Acts do not permit cultivation specifically targeted for exports. There is little varietal uniformity and lesser standardization of technology packages. If an enterprising person with modern knowhow wishes to enter the field he is discouraged by the fact that even a marginal consolidation of fragmented pieces of land is not permitted for more than three years under the land legislation.

§ Indian agriculture is all a smallscale affair, quite innocent of largescale modern organisational structure. Largescale corporations handle 85 to 90% of the international trade. India is probably the solitary exception where exports are handled by minienterprises.

§ Dependence on erratic monsoons is a perpetual threat that jeopardizes regularity of supply and standardisation of quality; thus is a very serious handicap in export business.

§ Most agricultural inputs are more expensive in India than elsewhere. Fertilisers, agricultural machinery, pesticides, petroproducts cost much more in India than abroad. The comparative advantage of Indian produce at the farmgate is largely due to the cheap rural labour.

§ The uncertainty in government policies regarding exports and imports, absence of futures, poor banking infrastructure and the sheer crudeness of the agricultural marketing mechanism result in wide fluctuations in prices. Attempts at contracts farming have run into trouble as farmers who are anxious to supply their produce for processing and export in years of lean prices turn reluctant when the prices are high and soaring.

Box 2: Prospects for Expanding Exports There are a few virgin fields, which show great promise for exports from India:

§ About 40% of agricultural land in India has not been touched by any chemicals pesticides or fertilisers. There is a growing demand, particularly in the European countries, for certified biofood. India could almost lionise this market.

§ A number of Indian herbals and medicinal plants are attracting the inquisitive attention of pharmaceutical giants abroad. Some of these latter have established bases in India with a view to collecting specific plants growing in forests, mountainsides and wilderness. Collecting these plants or undertaking their cultivation offers considerable promise.

§ Rural labour, particularly the female labourers have demonstrated a very high degree of dexterity in crosspollination operations. This should permit India to make a big inroad into the seed multiplication market.


References

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Tanzania Case Study 5

INTRODUCTION

Background to the study

Multilateral liberalisation of trade in agricultural commodities offers all countries (developed and developing) potential gains from trade. Increased market access, as other countries reduce their barriers to imports, would allow many developing countries to increase their exports, to developed countries and globally. Import liberalisation also offers benefits: consumers gain from access to a wider variety of cheaper goods, and competition from imports encourages domestic producers to become more efficient. A less restricted and less distorted global trade regime encourages increased efficiency in the allocation of resources, both within and across countries. The gains are not evenly distributed and some countries, and some producers within countries (especially those who lose protection and are constrained in their ability to increase efficiency), will incur losses. Multilateral trade liberalisation in agriculture will affect patterns and intensity of production, within and across countries, and will therefore have social and environmental impacts, both positive and negative. The purpose of the SIA is to identify the probable distribution of gains and losses associated with the variety of economic, social and environmental impacts. The study will recommend mitigating and enhancement measures that can promote benefits, minimise losses and compensate losers.

A further consideration in the liberalisation of agriculture is the social and environmental effects of changes in patterns and intensity of agricultural production, especially but not exclusively in developing countries. Allowance has to be made for food aid, for countries’ particular needs in strengthening their agriculture, and for general and targeted assistance from developed countries (such as European countries’ preferential trade with their former colonies). The special and differential treatment (SDT) provisions of the Agreement on Agriculture provide additional means of achieving these aims, which are considered further within the Doha agenda. In addition to the food security and market access concerns of both developed and developing countries, the liberalisation of agricultural trade is affected by a number of other issues:

• Countries generally aim to apply the same standards of food safety to imports as they do to their domestic produce, and may do so under the separate WTO Agreement on Sanitary and Phytosanitary measures.

• They may wish to promote the development of their own agricultural sector, especially to take account of particular social groups or environmental concerns. This is allowed under WTO rules, using a number of mechanisms which are considered not to distort trade (referred to as “Green Box” measures). Such support is also permitted for direct payments made under productionlimiting programs (the “Blue Box”), or where the scale is small compared with the total value of the supported products.

• Agriculture is seen to have a wider (multifunctional) role than food production, including environmental conservation and animal welfare. Permissible support mechanisms are sought for these also, generally as part of the Green or Blue Box provisions.

There are three basic components to negotiations on liberalisation of trade in agriculture – reduction of tariffs and non tariff barriers (NTBs), reduction of export support (especially subsidies) and removing the trade distortions associated with domestic support measures. Although the SIA considers each of these separately (to identify distinct effects), the aim is to assess their combined effects, specifically the effects of liberalising imports and expanding exports in particular sectors of agriculture in particular types of countries. The SIA focuses on the impacts of those reforms that are most directly related to trade. Although general impacts on the EU and other developed countries will be addressed, more detailed analysis and country case studies will be confined to developing and least developed countries. In the context of agriculture, where subsidies for domestic farmers are significant and pervasive in many developed countries (especially in the EU and US), reforms to domestic support will have significant impacts on farmers, agribusiness and consumers in those countries. Although such impacts are not ignored, the economic, social and environmental impacts on developed countries will not be addressed in detail.

Exporting countries (actual or potential) expect to benefit from enhanced market access. However, the extent of benefits will vary for different countries and enhancing measures may be required to ensure that benefits are realised. Cheaper imports benefit consumers of final and intermediate goods. There will be losses and adjustment costs in countries opening up to increased competition from imports, and these costs are likely to be greater the higher the degree of initial

5 Prepared by: Ntengua S.Y. Mdoe and Elibariki E. Msuya, Department Agricultural Economics and Agribusiness, Sokoine University of Agriculture, P.O. Box 3007, Morogoro, Tanzania. February 2004.


protection and the poorer the country. As poorer countries typically have inflexible economies and their agricultural producers face multiple constraints (e.g. limited access to inputs, irrigation, markets, technology, etc), they will face difficulties in meeting the costs and actually making the required adjustments. One cannot presume that in all cases liberalisation will have a beneficial economic impact (the costs and/or constraints on adjustment may be too great in some countries, or for certain producers). Even where the economic impacts are positive, it cannot be assumed that the environmental and social impacts are always positive or insignificant. Where adverse impacts are likely, mitigating measures will be discussed, distinguishing both shortrun and long run issues.

The study covers the range of agricultural commodities, drawing distinctions between food and cash crops, temperate and tropical products, and crops and livestock (noting that measures relating to the latter can impact on animal feeds). As it is not feasible or practical to try and address the full range of agricultural products in any detail, the analysis concentrates on specific products. The products are selected to represent broad categories of agricultural commodities: food grains (wheat and rice), livestock (beef), cash crops (cotton, sugar) and horticulture (green vegetables). The products are also selected to ensure that a wide range of issues relevant to the negotiations can be addressed. For example, most of the products are affected by all three elements of reform (tariffs, export and domestic support), all are important exports for some developing countries, some are important imports for developing countries, and some are especially important for the least developed countries. The commodity impact analysis concentrates on the products in question, at both country and global levels. Where appropriate, especially in the country studies and to address specific social or environmental impacts (e.g. animal welfare), other products will be considered.

The overall sustainability impact on any particular country will depend on the composition of its agricultural trade, the structure of the agricultural sector (including economic and social contexts) and the nature of production (encompassing how agriculture relates to the environment). For any country, the beneficial (adverse) impact for one product may be offset by adverse (beneficial) impacts on other products. It is not feasible to consider all countries, and the study considers six representative groups of countries, two developed and four developing. The EU and other developed are the two groups of developed countries. The four developing country ‘types’ are chosen to represent major exporters, countries with high levels of protection, least developed countries (LDCs) and lowincome countries (whose agriculture sector is similar to that of LDCs, but who cannot avail of LDC status).

The domestic support policies of most developed countries, especially the EU and US, have had a significant effect in distorting world trade in many agricultural commodities. By restricting imports and subsidising exports, these policies depress world prices, which constrain the ability of developing countries to export and thus denies them market share. Furthermore, the subsidised exports undermine the competitiveness of local producers in importing countries. This could create food security problems in importing (developing) countries, although this is unlikely as in many cases the subsidised imports do not compete directly with local produce. In countries that are net food importers, consumers benefit from the subsidy.

In the European Union, WTO negotiations and the heavy financial burden of the Common Agricultural Policy (CAP) have constituted strong pressure to liberalise trade in agriculture. The CAP already accounts for about half the EU budget, although farming represents less than five per cent of total employment and less than 1.5 per cent of EU GDP (Serger, 2001). This understates the true importance of agriculture, as agribusiness (especially food) probably accounts for a fifth of GDP, and many of the subsidies actually go to business rather than farmers (this is even more relevant to the US). This has resulted in the situation where the CAP fails to meet the needs of most farmers, is a burden on consumers and distorts world trade, resulting in strong impetus for change (see Agricultural Policies in OECD Countries: Monitoring and Evaluation 2003, Paris: OECD). Proposed reforms include Agenda 2000, which sets new rules for market intervention and reduces price support, especially for cereals (EC, 2000). A similar distinction, between domestic support and trade per se, arises for other developed countries with high protection and domestic support (e.g. US, Japan, Norway and Switzerland).

Consequently, negotiations on liberalising trade in agriculture have been complicated by the need to address reform of domestic support in addition to trade policies. Had it only been tariffs and nontariff barriers at stake (as for most other sectors, where export subsidies are prohibited), liberalisation of trade in agriculture could have proceeded faster. For the purposes of this study it is essential to distinguish the issues of domestic support and trade. Developed countries are not required to eliminate support for their domestic agriculture sectors. The issue is how they provide support, and specifically that they do so in a way that does not distort world trade. In our analysis we will use projections of the effect on world markets of removing the tradedistortions associated with domestic support. Typically, these will be represented as estimated effects on world prices, from which one can infer potential effects on exporting and importing countries. The effect of elimination of export subsidies will also be analysed through the estimated effect on world prices. We will represent tariff and NTB liberalisation as affecting domestic prices (i.e. lower tariffs reduce import prices).


It follows that we do not need to review the modalities that are being discussed in negotiations on agriculture in the WTO in great detail, as our scenarios will be relatively simple. The direct trade reforms are the reductions in tariffs and nontariff barriers that these countries implement, as it is these that influence the price in the local market of agricultural imports (given world prices). Reforms to export and domestic support in developed countries will affect domestic and world prices, and these price effects will induce changes in patterns of net trade. The effect on the world price is an appropriate summary indicator of the effect on relative incentives that will determine the impact on developing countries. The detail of the reforms will also have implications for the developed countries. We will not undertake any global modelling or simulations in this study, but will simply take estimates of world price effects from studies that are available.

This case study is about the impact of the trade reforms Tanzania. Tanzania has been selected for a detailed case study of least developed countries (LDCs). This case study covers three food grains (maize, rice and wheat), one livestock product (beef), two cash crops (cotton and sugar) and one group of horticultural crops (green vegetables). Maize was added to the original list of six products because of its importance as the most preferred staple food crop across the country.

Since the overall sustainability impact will depend on the structure of the agricultural sector, nature of production and composition of its agricultural trade, the remaining sections of this chapter provide background information on the Tanzania’s agricultural sector including it structure and its importance in the economy.

The structure of Tanzanian agriculture

Agriculture in Tanzania comprises crop and livestock production. Crop production systems can be classified into the following four categories:

(i) smallholder farming with some annual crops (cotton, tobacco, maize and beans) or perennial crops (coffee, tea, cashewnut, banana);

(ii) smallholder farming based on pastoralism, with some annual food crop production, usually sorghum and millets, mainly in low rainfall areas;

(iii) medium to large scale commercial farming, often as monoculture, particularly of export crops(coffee, tea, sisal), but also including some large scale annual food crop production such as maize and wheat; and

(iv) Irrigated farming, particularly for rice (paddy) production, ranging from smallholder to large scale farming.

In smallholder farming systems, different cultural practices are found ranging from sole cropping of cotton in western Tanzania and tobacco in southern highland, mixed cropping of coffee, banana and vegetables in northern Tanzania, and an almost agroforestry interface of cashewnuts, coconuts, cassava and cereals in southern Tanzania. Other prevalent cropping systems include cereal and grape (vines) in Dodoma and maize, sunflower and legume mixed cropping in the southern highlands of Tanzania.

With regard to livestock, four livestock production systems are commonly distinguished in Tanzania viz.: pastoralism, agropastoralism, commercial ranching, smallscale dairy and largescale dairy. Cattle are the dominant species, accounting for about 75% of the 16 million livestock units in the country. High concentrations are found in nine regions of Arusha, Manyara, Dodoma, Tabora, Shinyanga, Mwanza, Singida, Rukwa and Mara. Nearly 50% of the cattle herd is on agropastoral system of farming mainly in the humid plateau lands of Mara, Iringa, Mbeya and more than 40% are on pastoral system in the semiarid to subhumid rangelands of Arusha, Manyara, Dodoma, Singida and Shinyanga. Most of the cattle raised in the pastoral and agropastoral production systems are of the traditional (indigenous) short horn zebu type, which accounts for about 98% of the cattle found in the country. Improved cattle are found in ranches, smallscale dairy and largescale dairy production systems. Ranching, and smallscale and largescale dairy constitute 2% of the total cattle herd in the country. Commercial ranching is almost entirely operated by Government through the National Ranching Company (NARCO) and constitute about 0.8% of national cattle herd. The small ruminants are found in almost all parts of Tanzania. They account for about 22% of the national meat supplies, significantly contributing to the local red meat consumption in rural areas. Goats are found in large numbers and therefore more important in meat supply than sheep. Many rural families own goats and they assist the communities in food security and poverty alleviation. Livestock normally graze in rangelands under almost communal land tenure.

Agriculture in the Tanzanian economy


The agriculture sector plays an important role in the Tanzanian economy and possesses the potential to advance the country’s objectives of growth and poverty reduction. It contributes significantly in terms of aggregate growth, exports, employment and linkages with other sectors. The sector contributes the most to GDP (over 50% of the GDP) and supports livelihoods of over 80% of Tanzanians living in the rural areas. Since over 80% of the population in Tanzania live in rural areas and agriculture is the mainstay of their living, any strategies to address poverty and food security must involve actions to improve agricultural and livestock production and farm incomes to ensure availability and access to food.

Importance of Trade in Agriculture

Table 1 shows the value of agricultural exports by commodity from 1997 to 2003. Prior to 2000, agricultural products contributed over half of Tanzania’s export earnings. However, the share of agriculture exports declined from about 59% in 2000 to about 33% in 2003. This situation can be explained by the fact that traditional export products started loosing ground with the revival of the mining industry, hence the increase in share of mineral exports. On average, production of traditional export products themselves performed poorly during the second half of 1990s. The share of traditional export crops started to decline since 1998 when it was more than 60% to about 19% of Tanzania’s export earnings in 2003. Besides mineral exports, the increase in nontraditional exports including those from the agricultural sector (For example horticultural products, fruits, live animals, fish) also reduced the share of traditional export crops. Within the agricultural sector, the share of traditional export crops declined from about 85% in 1997 to about 58% of the value of agricultural exports.

Table 1: Value of Agricultural Exports by Commodity 1997 2001, million US dollars

Year Commodity 1997 1998 1999 2000 2001 2002 2003 Traditional Agricultural Products

435.3 356.3 301.2 292.8 231.1 206.1 218.5

Nontraditional Agricultural Products

73.4 81.6 85.9 97.7 108.5 127.7 149.9

Total Agriculture 508.7 437.9 387.1 390.5 339.6 333.8 368.4 Petroleum Products 7.1 0.1 0.4 1.2 0.0 0.0 0.0 Minerals 51.1 26.4 73.3 177.4 302.2 383.8 540.2 Manufactured Goods 111.3 35.7 30.1 43.1 56.2 65.9 99.9 Other Exports 74.3 88.5 52.5 51.1 78.0 119.1 121.2 Grand total 752.5 588.6 543.4 663.3 776.0 902.6 1,129.7 Source: Bank of Tanzania (2003).

Apart from agricultural exports, Tanzania imports various agricultural products especially food items. The value of imports of food items increased from 97 million US dollars in 1997 to more than twice as much in 1999 and then declined to about 169 million US dollars in 2001 (Table 2). In 2003, the value of food imports accounted for almost 30% and 8% of the value of imported consumer goods and total value of all imported goods, respectively.

In general, the share of food imports depends on the domestic food production, which to a large extent depends on the rainfall pattern.

Table 2: Value of Agricultural Imports by Commodity Category 1997 2001, million US dollars

Year Commodity Category 1997 1998 1999 2000 2001 2002 2003 Capital Goods* 563.6 764.9 693.2 638.2 739.7 721.2 848.9 Intermediate goods**

382.9 303.4 319.6 319.4 440.2 423.0 677.5

Food Products *** 97.1 180.9 230.7 183.0 169.4 147.3 183.0 Other Consumer goods****

276.0 339.5 329.2 393.8 364.8 369.3 435.9

Total Consumer Goods

373.1 520.4 559.9 576.8 534.2 516.6 618.9

Grand Total 1,319.6 1,588.7 1,572.7 1,534.4 1,714.1 1,660.8 2,145.3 Note: * Include transport equipment, building and construction


** Include oil, fertilizers and industrial raw materials *** Include various crop and livestock products to bridge the gap between domestic production and demand **** Include clothes and other nonfood consumer goods

Source: Bank of Tanzania (2003).

STUDIES ON THE IMPACT OF LIBERALIZATION OF TRADE IN AGRICULTURE IN TANZANIA

There have been many studies in Tanzania that review and estimate the potential economic effects of alternative scenarios for liberalising trade in agriculture which include export reforms, tariffs reforms, removal of government direct interventions in food market and domestic support arrangements. To review and estimate the impact of the reforms, different studies used different approaches from, case studies, with and without scenarios, before and after scenarios CGE model, Global Trade Analysis Project model, and empirical analysis. The different approaches are all acceptable and there is no single method that can give a better result of impact in trade liberalization in developing countries. Some studies used more than one approach.

A study by McKay et al. (1997), examined the Tanzania supply response of agricultural output with the aim of proving the claim that trade liberalization which introduce price incentives and efficient marketing will encourage producers to respond. They found out that, longrun elasticity of food crop output to relative prices was almost unity; both food and aggregate shortrun response was estimated at about 0.35. They also found out that agricultural supply response is high so that the potential for agricultural sector response to liberalization of agricultural prices and marketing may be significant. The study concludes that, liberalization of agricultural markets, where it increases the effective prices paid to farmers, can be effective in promoting production, although complementary interventions, to improve infrastructure, marketing, access to inputs and credit, improved production technology etc, are probably necessary.

Gabagambi (1998) in his study on production and marketing of paddy and cotton in Ulanga district of Tanzania following market liberalization found that competition in paddy marketing has improved pricing efficiency. On the other hand, he found lack of competition in cotton marketing as very few traders were buying cotton in the district. Analysis of returns to inputs carried out by Gabagambi indicates that the returns were low for both crops and he attributes this to unnecessarily high production and marketing costs due to poor infrastructure and lack of competition in input supply.

A case study by Kakwemeire (1999) on cotton marketing in Kahama district found that liberalization has had positive impact on prices received by producers and cotton production, but incomes of smallholder cotton producers have not increased substantially. He indicated that pricing of seed cotton is not fully liberalized. An indicative price is set jointly between cotton buyers and board officials. This is intended to be a guide to buyers for setting their prices. Buyers may vary the price, but are not allowed to pay below the minimum price agreed upon by the joint meeting. An implication of this price setting procedure is that farmers who are not cooperative society members are not represented and one could not rule out the possibility of collusion between buyers with regard to price setting. The study also found that, the various requirements and fees which cotton buyers are subjected to, are effectively increasing the marketing transaction costs which in turn contribute to depressing the prices offered to farmers. In their study on competition and coordination in the cotton market system in Southern and Eastern Africa, a system overview report for Tanzania, Maro and Poulton (2002) report that international price changes have been fully transmitted to producers after market liberation leading into higher share of world price received by producers than before liberalization. They further report that the dominant influence on cotton production levels has not been the nature of cotton organization but rather the price of cotton on the international markets. This finding is supported by Larsen’s study on the Tanzania Cotton sector. Larsen (2003) reports that one of the predicted positive impacts of liberalization of higher share of export market price for lint cotton being passed through to farmers has been attained due to greater competition at the farm gate level and this has generally resulted into increases in national cotton production.

A recent report by the World Bank (2004) on institutional mapping of coffee and cotton as part of a study on reform of the Tanzania cotton, coffee, cashew and tea boards, indicate that liberalization has increased both coffee and cotton producers’ share of the export prices. Marketing efficiencies have improved and both green coffee and cotton lint reached the international market early and benefited from premium prices. The report indicates further that processing facilities for coffee and cotton with improved technologies were built. However, the report argues that liberalization that permitted vertical integration of coffee exporters conflicted with the requirement that all coffee should go through board managed auction. Also the report argues that intense competition for both primary processed coffee and seed cotton following liberalization has led to more or less total breakdown of quality control at farm level due decline in use of pesticides to control diseases and private buyers’ inability to enforce quality control through agents who buy from growers on their behalf.


Ponte (2001) in his study on coffee markets in East Africa including Tanzania, reports that domestic trade and processing have largely been liberalized, although regulatory requirements are still quite demanding at all levels of the marketing chain. As a result of liberalization, and in order to establish market share, Multi National Corporation (MNC) exporters have vertically integrated into processing, domestic trade and in some cases even estate production. Tanzania still runs a mandatory export auction, but the majority of coffee going through the auction is simply reacquired by the same company that bought it domestically. Thus, there is little or no competitive bidding for this socalled ‘captive’ coffee. For the same sector, Temu (1999) in a study on coffee marketing in Tanzania after liberalization found that the industry has responded much more successfully since liberalization. The market has become much more competitive and significant developments have taken place. Producer prices are higher than before and marketing margins have decreased mainly due to better processing technology and competition between traders. There has been improvement in both physical and human capital in the sector. The success is mainly due to development of organizations and institutions that solved some of the “immediate” structural problems that existed prior to liberalization. However, the study argues that, there is still untapped potential for further decrease in marketing costs through better coordination in assembling coffee from farmers.

A recent report by BACAS (2004) on institutional mapping of sugar, which is part of a a bigger study on reform of the Tanzania Cotton, Coffee, Cashew and Tea Boards: Options and implications for other crop boards, indicates that the benefits of market liberalization in the sugar sector were as expected as sugar producers are receiving a higher share of export prices. The report further indicates that liberalization in the sugar sector has led into dramatic increase in the number of domestic outgrowers of sugarcane, producers and traders of primary processed sugar. Consequently, sugar production, export and domestic consumption have increased. The report argues that replacement of the Sugar Development Corporation (SUDECO) by the Sugar Board of Tanzania (SBT) has been a move towards the right direction to improve performance of production, trade and consumption of sugar in Tanzania but concerns still remain with regard to uncompetitive behavior of private importers of sugar, SBT’s monopoly tendency to exports and breakdown of input supply systems that were maintained earlier under single channel marketing system.

A study by Rweyemamu (2001) on the cashew sector in Tanzania concluded that the output marketing system suggests that liberalization measures to date have led to strong private sector activity in cashew purchase and export. Liberalization appears to be one of the key factors responsible for the revival of the cashew industry. Nominal producer prices increased and as a result, production of the crop also increased. However, although the private sector is responsible for buying the vast majority of nuts from farmers, the partially liberalized industry still suffers from significant weaknesses that impair the production and marketing system. The output market is only partially competitive raising concern that farmers may be receiving disadvantageous prices for nuts. Market failures are caused by a combination of factors including high information costs/lack of market information (for both farmers and traders) and scarcity of capital at the lower levels of the marketing chain. The consequences of these shortcomings include both suboptimal cashew production (efficiency impacts) and an undue share of benefits from cashew production (equity impacts).

In the Tobacco sub sector, marketing has shifted from the cooperative/board monopoly to a more competitive system incorporating big international players and their agents. A case study by Simon (1998) on the effects of liberalized agricultural markets on smallholder agriculture found that the advent of liberalization led to acute conflicts between local cooperative societies and private companies constituting the trade. Interlocking contracts between farmers and traders also proved unenforceable with farmers avoided repaying their debts by selling to other buyers. He concluded that liberalization of tobacco marketing led to an initial surge in production as the new market entrants competed with each other. When the rapidly escalating local taxes on tobacco farmers and traders were factored in, margins on tobacco cultivation are eroded rapidly. The institutional basis for routine functioning markets is not yet in place.

There are different views regarding the impact of liberalization of grain marketing in Tanzania. Amani et al. (1992) and Putterman (1995) argue that the response of producers in the food crop sector has increased production of grain in the country and decreased grain imports. This argument is rejected by Ponte (1998). He argues that there is no evidence of improved efficiency in grain production since production at the farm level did not increase as much as it is published in government statistics.

Nyange, et al. (2003), used a case of Njombe and Rungwe districts to study the impact of macroeconomic reforms policies in Tanzania, which targeted the agricultural sector because is the largest economic sector and has greatest potential in ensuring food security and poverty alleviation. The reform policies were to remove government direct intervention in the agricultural sector so as to unleash production potential and trigger a positive supply response. The study highlights policy reforms’ impact into national and household level. At national level, the reforms resulted into a modest growth of the economy and agricultural sector, such as increased GDP growth rate from 3% before reforms to 6.2% in 2002/3, reduction in inflation from 30% in 1995 to 4.5 in 2002/3, foreign exchange reserve increased from


equivalent of 6 weeks imports (1995) to 30 weeks imports in 2002/3. At household level, the study showed no significant decrease in poverty particularly in rural areas, household Budget Surveys (1991/92 and 2001/2) indicated that poverty had declined only by 3 percent (i.e. from 39% to 36%), in rural areas poverty fell by 2% (from 41% to 39%), only Dar es Salaam recorded a significant fall in poverty from 28% to 17%.

A review study by Mdoe and Rweyemamu (2003) used before and after policy scenarios to analyze the impacts of market liberalization policy on both commercial and smallholder sub sectors and identify the role of the government in assisting the smallholders during the transition to a diversified and working market economy. The study showed that there haven’t been efficient operations within the liberalized markets. Citing different studies, Mdoe and Rweyemamu argue that there was gross inefficiency in the productionmarketing systems such that most of the farmers have not captured the full potential benefits of their production regimes despite operating under a liberalized market scenario.

Shapouri and Trueblood (1999) used food gaps scenarios in assessing effects of global trade liberalization on food security of 67 lowincome, fooddeficit countries including Tanzania. The first scenario focused on the impact of rising food prices, and the second scenario studied the impact of full agricultural trade liberalization on foreign exchange earnings. They found that, the impacts are positive but relatively small in both scenarios. Several factors explain this relatively modest result, including low production response, small food import or export shares, and low initial export growth rates. They concluded that, although international agriculture market liberalization is an important factor affecting food security, reform is not sufficient to alter the situation significantly. They added that, agricultural market liberalization could improve another important dimension of food security in lowincome countries — the disparity in purchasing power within countries.

Wobst (2002) in a study on the impact of alternative domestic and global trade liberalization scenarios on five economies of Malawi, Mozambique, Tanzania, Zambia, and Zimbabwe used a computable general equilibrium model that employs standardized 12sector social accounting matrices. He found that in cases of large variance in the initial tariff structure, a uniform tariff cut causes higher efficiency gains in production, foreign trade, and national welfare and requires less sectoral adjustment than a tariff harmonization with uniform tariff rate at constant revenue from tariff collection. In addition, he also found out complementary domestic measures that improve the costefficiency of the marketing system, support foreign trade policies (here a devaluation of the exchange rate) and either dampen their negative consequences or even compensate for them. From the results he concluded that common policy measures have different impacts depending on the underlying economic structures and that there is no ‘one size fits all’ strategy that would per se satisfy the needs of a particular class of developing countries. Therefore, he recommends exercising caution when dealing with trade liberalisation policies that aim at structural adjustment.

Computable general equilibrium (CGE) model based on a social accounting matrix was used by Grepperud et al. (1999) to analyse the economyenvironmental interlinkages for Tanzania, with the aim of using the model to stimulate growth and crop production. The model results showed that both policy reforms have expansive effects and that there are significant sectoral complementarities between agriculture and nonagriculture in Tanzania. Fertilizer subsidies promote cash crop production and a more land intensive production pattern in agriculture, while maize trade liberalization stimulates food crops and a more land extensive agriculture. Fertilizer subsidies are found to imply far more expansive effects than trade liberalization does. Only minor differences were identified between the two policy reforms as concerning their impact on the balance of trade, distribution and the environment.

In their study on Economic Liberalization and Livestock Sub Sector in Tanzania, Mdoe et al. (2001) analysed the effects of reform policies under Economic Recovery Program in livestock subsector. The study found out that the ERP measures have had both positive and negative impact on income and welfare of those involved in livestock business. New market opportunities for livestock were provided by the reforms but the opportunities varied according to livestock type and location. They also found out that the market forces brought higher input prices and expenditures on livestock production, which led farmers to reduce or abandon the use of expensive livestock inputs. The study concluded that the effects of reform policies were compromised with some internal factors such as, poor rural roads and the country being a net importer of most of the processed livestock products.

A study by Kanaan (2000) on Tanzanias’ experience with trade liberalization showed that trade liberalization had induced pronounced shift in income from the public sector and areas of the private sector that could easily be tapped for revenue by the government toward farmers, small enterprises, and the informal sector. In addition to that, it caused imports and customs duties to grow rapidly while shrinking the domestic tax base. The results of the study also showed that trade reforms allowed the country to become better integrated with regional common markets. The study concluded that, trade reforms played a key role in the revival of the export sector and the recovery and rationalization of imports, and laid the foundations for sustainable growth.

http://www.imf.org/external/pubs/ft/fandd/2000/06/kanaan.htm


A synthesis report by ESRF (2003) on Trade Policies And Agricultural Trade In The SADC Region: Challenges and Implications asserts that recent trends and pattern of trade in Tanzania’s trade statistics show a significant contribution of nontraditional exports and dominance of South Africa as one of new trade partner for Tanzania. It is found that the growth of Tanzania’s agricultural exports to other SADC counties is constrained more by domestic (supplyside) factors than international trade barriers. Noting however that the trade policy environment has significantly improved, and a comprehensive trade policy exists for Tanzania.

The SADC researchers used three approaches involving both desk and fieldwork. Firstly, each country took an inventory of the existing agricultural trade policies in their countries; the level, composition and trendprofile of intra SADC trade in agricultural products. This addressed the questions of what SADC members were trading with each other, the importance of agricultural trade and what the nature of this exchange implies for the success or failure of efforts in promoting SADC intratrade in agriculture. Secondly, each country level study conducted survey interviews of both agricultural trading enterprises and institutions. Surveybased methods provided the inventory of what the member countries are experiencing with regional trade such as tariff, nontariff, and technical barriers, geography and logistical problems, administrative problems, transport, communications, financial and other constraints, which work against trade. Thirdly, the studies undertook empirical analysis by estimating various competitiveness indices and gravity models using various data sets. Gravity models were employed to analyze trade flows between SADC member countries. In some countries, indices of Revealed Comparative Advantage (RCA) were computed to show the range of agricultural products SADC members could export competitively. The indices provide some indication of comparative advantage. A Regional Orientation Index (ROI) indicated whether regional trade is growing in relative importance. This provided information about the effect of regional arrangements on the direction of trade. Other indices of the intra agricultural trade provided useful insights into the extent of intraagricultural trade taking place and its implication for regional initiatives as well as complementarities of potential partner’s imports and exports. These include Diversification and Hirschman Indices.

Estimates of trade indices show that despite slow growth in Tanzania’s exports, the competitiveness of Tanzania’s commodity in the regional market is improving albeit the increasing competition, and the rate of protection is declining. This is partly a result of the trade liberalization and regional integration processes. Most products with high comparative advantage are not necessarily more regionally oriented. This finding is also supported by the Gravity model results, which revealed that Tanzania is trading below its potential with SADC countries particularly Botswana, Namibia and Mozambique.

Merlinda (1996) reported that the nature of welfare changes is significantly affected by the structure of trade and domestic distortions present in the economy. The termsoftrade changes indicate that while many countries are adversely affected due to increases in world prices, the termsoftrade losses are small relative to total GDP. Only in a few countries are the estimated welfare changes constitute over one percent of GDP. The distortion effects appear to be significantly larger than the termsoftrade effects in several countries. In some cases, the distortion effect works in opposition to the termsoftrade effects and large enough to reverse the sign of the overall welfare change. This implies that removal of policy distortions would convert the small termsoftrade loss to potential gains. However, many least developed netfood importing countries did not use the Round to support domestic efforts at trade policy reform. As shown in other studies that most of the gains from multilateral liberalization would come from countries’ own liberalization efforts, these countries lost the opportunity for gains.

In studying the impact of Doha agricultural trade agreements between country groups of developed and developing countries, Conforti and Salvatici (2003), used simulation of liberalization scenarios based on the model of the Global Trade Analysis Project (GTAP). The sscenarios were run on a 2013 baseline looking on the interaction between the two groups and took into account a number of events that affected and will further affect world agricultural markets. The results confirmed countries’ notion that liberalization is positively related to the overall potential economic benefits that should arise from the increased role played by comparative advantages in shaping market prices and returns to primary factor. However, the results showed that the gains are not as much to developing countries whose possibilities to benefit from incentives toward relocating resources inside and outside agriculture are limited by the extent and the diversification of the economy; and whose terms of trade may deteriorate with more global market liberalization. The authors concluded that it is difficulty for the poorer and the less diversified economies to capture the opportunities arising from a more liberal trade environment because of limited possibilities to switch toward competitive activities.


REFORMS AND GOVERNMENT SUPPORT TO THE SELECTED PRODUCTS

• This section provides an overview of reforms and government support to each of the seven crops studied. Besides the overview on reforms and government support, the section highlights the importance of the crops in the economy and level of existing trade for each crop.

Cotton

Cotton is one of the major traditional cash crops in Tanzania. It is grown throughout the country, primarily by smallholders on farms of about 0.5 to 10 hectares. Although cotton is grown throughout the country, there are two major cotton growing zones namely Western Cotton Growing Area (WCGA) and Eastern Cotton Growing Area (ECGA). More than 90% of the cotton is produced in WCGA, which comprises Mwanza, Shinyanga, Mara, Tabora, Singida, Kagera and Kigoma regions. The remainder (about 10%) is produced in ECGA, which include Morogoro, Iringa, Tanga, Kilimanjaro and Arusha regions.

Tanzania cotton production is currently less than 100,000 tons or around 0.3% of the world output. Production has declined from 250,000 tons in 1996/1997 cropping season to about 90,000 tons in 200/01 cropping season. Cotton yields over the past five cropping seasons have ranged from 85 to 175 kg. per hectare, one of the lowest yields in African cotton producing countries.

Cotton provides income to nearly 500,000 rural households engaged in cotton production as well those employed in the ginning factories and textile industry. It is one of the major sources of export earnings to Tanzania.

Cotton Trade

Almost 85% of Tanzania’s cotton is exported with the remainder being absorbed by the domestic market. The volume of cotton exports declined from 61,150 tons in 1992/93 cropping season to 33,320 tons in 2002/03 cropping season while value of the exports declined from 78.37 million UDS in 1992/93 to 28.63 million USD in 2002/03. In 2002/03 cotton exports accounted for about 4% of total Tanzania exports.

The domestic market for cotton comprises the local textile industry, which has been performing poorly. In the past, most of the textile mills were owned by the government. In recent years, however, there have been efforts to revive them through privatisation. The revival was facilitated by imposition of duty on import of kangas and 15% reduction on electricity tariffs. Most of the textile mills are producing for the domestic market except for two smallscale mills in Arusha, which are taking advantage of Afican Growth and Opportunity Act (AGOA) to export their products.

Reforms and Government support in the cotton sector

Prior to 1990, marketing and ginning of seed cotton was in the hands of primary cooperative societies and regional cooperative Unions. The Tanzania Cotton Marketing Board (TCMB) bought lint from the Unions for sale to exporters on a tender system, and to local textile mills. Reforms in cotton began with exposing the sector to market forces. In 1990, price controls on seed cotton were relaxed. Ownership of seed cotton was transferred to unions, as the board began providing fee based marketing services. The government began to announce only indicative prices rather than setting seed cotton price in 1991/92 cropping season. In 1994/95, Cotton Act allowed competition in cotton marketing and ginning, which eliminated the monopoly by the board and unions. During the 1994/95 marketing season, some 22 private companies started trading in cotton and 8 new ginneries were established in western Tanzania. However, in the Eastern Cotton Growing Area where production was low there were no private buyers and the Tanzania Cotton Lint and Seed Board (TCL&SB) acted as the buyer of last resort.

The reforms in the cotton sector led to deficiencies relating to maintenance of cotton quality and input supply. As the number of private companies increased and competed for limited output especially in the Western Cotton Growing Area, grading of cotton at farm gate was abandoned. All cotton was traded as high grade. Input use also declined. With increase in cost of pesticides, procurement of pesticides by cooperatives fell drastically between 1993/94 and 1998/99. Moreover, varieties developed for lake and southern zones were mixed due to uncontrolled movement of seeds and varieties that growers can use in their farming systems.

In late 1990, a cotton development strategy was developed for enhancing the Tanzania Cotton Lint and Seed Board role in supporting the cotton sector. The strategy for increasing cotton production include development and transfer of new cost effective production technologies, improving cotton procurement, distribution and delivery of cotton inputs through contract farming and other schemes, introduction of stronger cotton extension services, and favourable legal framework


for promoting commercial cotton farming. There is also a Cotton Act of 2001 whose thrust is on improving quality by requiring grading and trade in only graded material, controlling pests and diseases through strong quarantine measures, maintaining genetic purity through control over seeds and varieties that growers can use and ensuring fair trading measures.

In 1999/2000 cropping season, the cotton board established Cotton Development Fund (CDF) through 3% levy on exports to finance purchase of cottonseed, chemicals and cotton research and development.

Sugar

Sugar is of great importance to Tanzania as food as well as a potential source of employment. At present the sugar industry is one of the largest agroprocessing industries in the country. It contributes approximately 35% to the gross output of the food manufacturing sector and some 7 to 10% to total manufacturing value added. The industry is also a major employer with a labour force of about 30,000 direct and over 80,000 indirect (secondary) employments. In addition to employment creation, the sector contributes in earning foreign exchange for the country. The industry also contributes to the Government revenue in a form of tax amounting to 24 % of turnover.

Sugarcane, which is said to be a cheaper source of sugar than beets, is the main source of sugar produced in Tanzania. The scale of sugarcane production ranges from small to largescale production. Largescale sugar production is undertaken by various sugar companies, which are both cane planters and millers owning sugarcane estates as well as sugar mills. These are Tanganyika Planting Company (TPC) in Kilimanjaro region, Kilombero Sugar Company (KSC) which include Msolwa Estate (K I) and Ruembe Sugar Estate (K II), and Mtibwa Sugar Estate (MSE), both are in Morogoro region, and Kagera Sugar Limited (KSL) in Kagera region. At Kilombero Sugar Company and Mtibwa Sugar Estate, there are out growers attached to the sugar mills in these companies. They are a diverse group of cane growers with acreage sizes ranging from less than one hectare to over 100 hectares (MDB, 2003). Largescale production of sugar cane is concentrated mainly in three regions: Morogoro, Kagera and Kilimanjaro. Table 3 shows the contribution of outgrowers to the total cane crushed from 1999/00 to 2003/04 cropping season.

Besides large scale production and out growers, there are four categories of small scale producers operating throughout the country: (i) owners and operators of mini plants of capacity 100 TCD capable of producing 1000 2000 tons of sugar; (ii) owners and operators of miniature sugar plants (village level sugar plants) with the capacity to produce 100 – 600 kg of sugar per day; (iii) household level sugar producers who crush sugarcane using manual cane crushers; and (iv) producers of jaggery.

Table 3: Contribution of sugarcane outgrowers to the total cane crushed, 1999/00 to 2003/04

Outgrowers’ contribution Year Total cane crushed Tonnage As % of total cane crushed

1999/00 1,255,484 324,315 25.83 2000/01 1,333,474 245,272 18.39 2001/02 1,522,860 394,979 25.9 2002/03 1,833,719 422,035 23.02 2003/004 2,020,972.97 617,779 30.56 Average 1,593,299.99 400,875 25.00

Sugar Trade

The importance of sugar as an export crop is very negligible. Most of the sugar produced in the country is for home consumption and only a small proportion is exported through ACP EU to EU Protocol, ACPU EU Special Preferential Sugar scheme (SPS) and LDCEU (Everything But Arms) EBA initiative. Although Tanzania exports some of its sugar, it also imports sugar (Table 4). It is clear from Table 4 that Tanzania is a net importer of sugar.

Table 4: Refined sugar exports and imports, 19982002

Refined sugar exports Refined sugar imports Year Quantity in tons Value in US$ Quantity in tons Value in US$


1998 16,823 16,718,000 30,610 16,501,000 1999 13,541 10,893,000 103,810 48,200,000 2000 13,280 6,272,000 127,002 46,544,000 2001 30,758 13,533,000 74,843 26,140,000 2002 22,698 9,037,000 58,659 19,399,000 Source: FAO

Reforms and government support to the sugar sector

Reforms in the sugar industry included liberalization of domestic price setting and institutional reforms. The main institutional reforms were the privatization of the sugar estates and factories, partialderegulation of the sugar marketing and increasing the role of outgrowers. Most of the sugar estates have now been privatized and the government has very few shares. A Parliament Act of 2001 established the Sugar Board of Tanzania (SBT). The functions of the board can be categorized into licensing, quality control and market regulation in the sugar sector. The SBT has power to register all sugarcane outgrowers directly or indirectly through agents. Approval of varieties of sugarcane to be grown for commercial purposes is the responsibility of the Ministry of Agriculture. The Act which established the board restricts importation of sugarcane. No person is allowed to import, breed or modify (by genetic engineering) sugarcane or seed, cuttings and seedlings without written authority of the Board. The SBT has established a fund known as the Sugar Industry Development Fund for the development of the sugar industry. All levies paid by sugar manufacturers are deposited into this fund. The fund is used to finance sugar industry development activities including sugar marketing promotion, training and research. The Board has very limited role and responsibility in the provision of inputs and extension services to sugarcane growers.

Rice

Rice is a highly preferred food in urban areas and institutions such as hospitals, schools and hotels because of its simplicity to prepare for a large number of consumers. It constitutes about 17% of the cereal consumption in the country with other staples such as maize and wheat constituting about 78% and 3% respectively.

Rice is grown almost throughout the country, mainly produced by smallscale farmers. Largescale commercial rice production is limited to few private individuals who bought farms formally under the National Agricultural and Food Corporation (NAFCO). Shinyanga, Mwanza, Morogoro, Mbeya and Tabora are the leading regions in rice production, which together account for about 7080% of rice production in the country. Production of rice has been fluctuating over time. It increased from 622,500 tons in 1995/96 to 849,000 tons in 1997/98, declined to 323,700 tons in 2000/01 and increased to 1,283,700 tons in 2002/03.

Rice Trade

Most of the rice produced is consumed locally and very little is exported to neighbouring countries in the Region. Like maize, Tanzania exported substantial amount of cereal grains including rice to Zambia and Malawi in 2002/03, which were both hit by drought. This rice was from Mbeya region, which borders the two countries and therefore cheaper to transport the rice to these countries than to other urban areas within Tanzania. Despite this cross boarder trade, rice has in most cases been in short supply in Tanzania especially in urban areas, compelling the government to import rice to bridge the gap between local supply and demand. Overall, Tanzania is a net importer of rice despite the vast land suitable for rice production. Table 5 shows imports of rice from 1998 to 2002.

Table 5: Broken rice imports, 19982002

Year Quantity in tons Value in US$ 1998 16,983 5,983,000 1999 26,519 8,415,000 2000 82,283 23,056,000 2001 83,386 17,025,000 2002 56,705 8,755,000 Source: FAO

Reforms and government support in the rice sector

Like maize, reforms in the rice sector began with government withdrawal from controlling rice and paddy prices and reducing the monopoly of the National Milling Corporation (NMC) in rice marketing. During the 1988/89 cropping


season private traders were allowed to compete with Cooperatives and NMC in purchase of paddy directly from farmers. Government control over producer and consumers prices for rice ended in 1989/90. In 1990/91 the government began to announce indicative prices as a guide to farmers in negotiating with traders. This ended during the 1992/93 cropping season and thereafter rice prices depended on market conditions (demand and supply situation).

Wheat

Wheat ranks third after maize and rice as one of the preferred staple grain in Tanzania. It accounts for 1% of the total calorie intake in the country. Most of the wheat is consumed in urban areas. It is estimated that about 80% of wheat is consumed in urban areas. The demand for wheat is likely to increase with increase in urban population and changing consumption habits among urban dwellers in Tanzania.

Production of wheat is carried out in two distinct production systems. Large scale mechanized production system in the northern highlands and smallscale production in the southern highlands of Tanzania. In the smallscale production system, wheat is intercropped with other crops and is characterized by low level of technology and hence low yields per hectare. The northern highlands account for more than 70% of the total wheat production in the country. Total wheat production has been fluctuating over time. Production increased from 65,800 tons in 1991/92 to 111,500 tons in 1997/98, declined to a record low of 32,700 tons in 1999/00, increased to 72,000 tons in the following season and thereafter declined to about 45,000 tons in the 2002/03 cropping season.

Wheat Trade

Tanzania does not export wheat. Almost all wheat produced in the country is traded locally. However, the country imports wheat to bridge the gap between domestic production and demand. Table 6 shows wheat imports from 1998 to 2002.

Table 6: Wheat imports, 19982002

Year Quantity in tons Value in US$ 1998 237,860 55,943,000 1999 83,444 28,777,000 2000 298,947 56,523,000 2001 381,805 67,273,000 2002 390,069 58,411,000

Source: FAO

Reforms and government support to the wheat sector

Like maize and rice, reforms in the wheat sector began with government withdrawal from controlling prices of wheat and reducing the monopoly of the National Milling Corporation (NMC) in wheat marketing by allowing private traders to compete with NMC in purchasing wheat from farmers.

Maize

Maize is the major and most preferred staple food crop in Tanzania. Other preferred staples are rice and wheat. Maize constitutes a more than 75% of the cereal consumption in the country. While most of the rice and wheat are highly preferred and mostly consumed in urban areas, maize is preferred and consumed in both rural and urban areas of Tanzania. It is a major staple for the Tanzania’s population.

Maize is largely produced in smallholder farms almost throughout the country although production and demand levels vary among regions thus creating surplus regions. Although maize is produced in all 20 regions of mainland Tanzania, only 6 regions are reported to have a regular surplus (MDB, 1997). The maize surplus regions, in descending order are Iringa, Mbeya, Rukwa, Ruvuma, Arusha and Singida. Four of the six regions are in the southern highlands of Tanzania, which account for a larger share of the maize produced in the country. Mbeya and Iringa are the largest producers and account for almost a quarter of the country’s maize production.

Annual maize production has generally been fluctuating. Production increased from 1,831,200 tons in 1996/97 to 2,684,600 tons in 1997/98, declined to 2,009,100 tons in 1999/2000, increased to 4,377,900 tons in 2001/02 and then


declined to 3,415,600 tons in 2002/03 cropping season. The fluctuating trend n maize production is largely due to rainfall fluctuation as most maize is rainfed.

Maize trade

Most of the maize produced in the country is consumed locally. During good years, however, Tanzania exports maize to neighbouring countries. In recent years, for example, Tanzania exported some maize to Zambia and Malawi, which were both hit by drought. These exports increased from 16,871 tons in 2000 to 152,310 tons in 2002. Most of this maize came from the southern highlands regions of Iringa, Mbeya, Ruvuma and Rukwa. These regions are not only major maize producing regions in Tanzania but they are also close to Zambia and Malawi.

Although Tanzania is almost self sufficient in Maize, it has been importing maize in the form of food aid and commercial imports to alleviate shortages caused by natural calamities such as drought and floods. Table 7 shows maize imports from 1998 to 2002.

Table 7: Maize imports, 19982002

Year Quantity in tons Value in US$ 1998 269,615 92,504,000 1999 35,585 24,536,000 2000 49,453 11,707,000 2001 31,045 8,781,000 2002 63,373 11,953,000

Source: FAO

As pointed out above, only 6 out of the 20 regions in mainland Tanzania are maize surplus region. Therefore efficient interregional trade of maize is important in linking producers in surplus areas with consumers in deficit areas. Efficient trade will occur if maize markets in surplus and deficit regions are integrated. However, several factors affect the degree of market integration between regional markets in Tanzania. The most important factor is transfer costs whose major component is transportation cost. Other transfer costs are handling (loading and unloading), insurance, storage, etc. Transportation cost depends on distance, topography (e.g. plain versus mountainous road) and road quality through depreciation. These factors affect market integration indirectly through their contribution to transportation cost. Factors other than transfer cost that influence market integration are flow of market information determined by telecommunication infrastructure, degree of competition in the markets as well as government policies and institutions.

Associated with market integration is the degree of price transmission, which may have an effect on the speed of traders’ response to move maize to deficit regions. Maize trade in Tanzania is characterized by a large number of small and medium traders who operate from both maize surplus and deficit markets in rural and urban areas. Most of them do not own transport. They rely on hiring trucks and rail wagons. High transportation cost between regions is a disincentive for these traders to engage in maize trade. Given the great size of Tanzania and relatively costly transport due to long distances and quality of roads from DaresSalaam (Table 8), some regional markets are poorly integrated with the DaresSalaam, which is a major focal point for maize price formation in Tanzania 6 . A study by Nyange (2000) found Arusha, Morogoro, Iringa and Njombe maize markets to be integrated with DaresSalaam. He associated this integration with good quality transportation infrastructure. On the other hand, the study found that ArushaMwanza, MbeyaKasulu and MbeyaMwanza which are poorly linked with neither paved roads nor railways to be segmented while MbeyaDaresSalaam and TaboraDaresSalaam were found to be segmented due to long distances between them.

High transport costs from Daressalaam will not only affect transmission of local prices from one region to another but also protect some regional markets from movements in world maize price. The impact of changes in world market price is discussed in section 4.3.

6 Daressalaam is considered a major focal point for maize price formation for several reasons. Firstly, DaresSalaam is the largest urban centre in the country with a population of about 5 million people (URT, 2002 Population Census). Secondly, the city relies entirely on maize from other regions or through imports especially during nationwide maize deficit. Thirdly, DaresSalaam is the largest import and export cite for agricultural products. Fourthly, the city has the highest per capita income, which denotes an effective demand. Lastly, major livestock feed industries and some breweries located in DaresSalaam add to the total demand for maize.


Table 8: Road distance and condition and railway link between DaresSalaam and some maize producing areas in Tanzania.

Market channel Road distance (Km)

Road condition p = paved, pp = partly

paved, np = not paved

Railway link l = linked or near, nl =not linked

DaressalaamMorogoro 193 p L DaresSalam – Iringa 503 p nl DaresSalaam – Njombe 722 p l, near DaresSalaamMbeya 893 P l DaresSalaam – Songea (Ruvuma) 1001 P nl DaresSalaam – Sumbawanga (Rukwa) 1228 pp nl DaresSalaam –Arusha 639 P l DaresSalaam – Singida 743 pp nl DaresSalaam – Tabora 1078 pp l DaresSalaam – Mwanza 1441 pp l

Reforms and government support in the maize sector

Reforms in the food crop sectors began with government withdrawal from controlling prices of cereal grains and reducing the monopoly of the National Milling Corporation (NMC) in cereal grain marketing including maize. During the 1988/89 cropping season, private traders were allowed to compete with Cooperatives and NMC in purchase of maize directly from farmers. Government control over maize producer and consumer prices ended in 1989/90. In 1990/91, the government began to announce indicative maize prices as a guide to farmers in negotiating with traders. This ended during the 1992/93 cropping season and thereafter maize and other grain prices depended on market conditions (demand and supply situation). Subsidy on inputs particularly fertilizer subsidy was officially removed in 1994/95. Also controls on importation and distribution of inputs of most crops including inputs for maize production were removed. However, the fertilizer subsidy was reintroduced some two years ago for farmers in the major maize producing regions in the southern highlands of Tanzania.

Beef

Tanzania is richly endowed with various species of livestock. According to the 1994/95 livestock census Tanzania has 15.6 million cattle, 10.7 million goats, 3,5 million sheep and 27 million chickens. Despite the large livestock population, it has little contribution to the national economy. The Livestock Subsector’s contribution to the country’s Gross Domestic Product (GDP) is about 6% and its contribution to the Agricultural GDP is about 13%, of which about 40% is from beef, 30% from milk and the remaining 30% comes from poultry and small ruminants. The sector has therefore a great role to play in rural communities providing a relatively secure form of income, savings, investment and food security. Furthermore, the animals are a source of manure, hides and skins, and draught power for cultivation and transport.

Beef production mainly comes from the traditional sector that is dominated by the Tanzania Short Horn Zebu (TSZ) in which the agropastoral system contributes 80% and the pastoral system 14%. The remaining proportion of 6% comes from commercial ranches.

Beef Trade

Most of the beef produced in Tanzania is mainly for the domestic market although part of the annual cattle offtake is exported as live animals to neighbouring countries and the Middle East. To facilitate trade of live animals with neighbouring countries, the government has established border markets where livestock trade between our country and neighbouring countries is conducted legally. These were established in order to arrest unofficial livestock trade, which has been taking place across borders. Ten border livestock markets have been established in the country of which four


are along Tanzanian/Kenya boarder, two along Tanzania/Uganda, one along Tanzania/Zambia/Democratic Republic of Congo (DRC), one along Tanzania/Burundi and two along Tanzania /Rwanda boarder.

Tanzania is currently not exporting any beef. However, corned beef was one of the Tanzania’s exports in the past. Tanzania, which used to export corned beef to Europe lost its European Union (EU) sanitary certificate in 1974. Since then exports of corned beef declined and ceased completely in 1993 when Tanganyika Packers Limited (TPL) was closed 7 . Inability to meet health and hygienic standards of importing countries appears to be the major barrier to export trade in beef and other livestock products. Concerns about food safety standards in developed countries have been increasing since 1990s following the period of eroding consumer confidence in the safety of food produced and traded in Europe provoked by food scares such as the BSE crisis and the dioxin contamination scandals. Standards applied to beef exports include Sanitary and Phytosanitary Standard (SPS), Hazard Analysis and Critical Control Point (HACCP) and traceability.

These standards act as the main trade barrier facing Tanzania beef exports. For Tanzania to access the international markets for beef, it has to prove that it has done an active effort to assure the safety of the product not only when the product is in the possession of the exporting organization but also at various points in the supply chains. This implies a high degree of monitoring and keeping records of the products and the conditions under which they have been produced and traded. Compliance to the standards, therefore, give rise to a number of production and transaction costs which include fixed costs of adjusting production facilities, costs of coordinating the flow of beef through the supply chain as well as the costs of conformity assessment. Controlling these costs in Tanzania is a bit difficult because of two major reasons. First, the cattle subsector is dominated by smallholder producers. About 98% of the subsector belongs to the traditional small scale producer with little or no commercial orientation. There are only 15 commercial ranches in the country owned by the National Ranching Company (NARC)). Private sector participation in commercial livestock production is almost negligible although the government is now encouraging private investment in ranching. Second, domestic quality standards for beef are different from those of the developed countries. When exporters of beef in Tanzania have to meet the standards set in developed countries, they have to operate under standards, which are much higher than the ones commonly enforced in Tanzania.

Reforms and Government Support in the Beef Sector

Prior to liberalization, the government was providing support to the beef sector including provision of dip services, veterinary drugs and extension services. Following liberalization, most of the services have been privatized and government role is largely to provide support to the private sector through provision of technical and extension services, coordination and policy guidelines at the district level. There are also efforts to improve health and hygienic standards in order to revive beef exports to Europe and other developed countries. These efforts include establishment of animal disease free zones, improvement of livestock marketing services and promotion of commercial beef production in the country through the Tanzania Livestock Marketing Project (TLMP) and National Ranching Company (NARCO).

The Tanzania Livestock Marketing Project (TLMP), a project established in 1993, envisages improvement of the marketing of livestock and meat by the improvement of livestock marketing services and infrastructure, and construction of modern slaughterhouses. The National Ranching Company (NARCO) is charged with the responsibility of promoting commercial beef production in the country. In the on going restructuring of the company, it is expected that, each of its farms will be left with an area of approximately 20,000 ha that will act as a model for running of commercial beef ranching in the country. The rest of the land will be apportioned into 4,000 ha units and allocated to individual ranchers for commercial beef production.

Green Vegetables

Green vegetables play an important role in human nutrition, preventing diseases and contributing to the health of the people as they are a source of minerals and vitamins. Tanzania is endowed with good climatic conditions for the production of green vegetables for the domestic market as well as for export. The agroecological characteristics of the country favour the production of different types of green vegetables almost throughout the year. Regions with climate suitable for green vegetables are Arusha, Coast, DaresSalaam, Dodoma, Iringa, Kilimanjaro, Mbeya, Morogoro and Tanga. At present production of vegetables in Tanzania is estimated at 1,035,000 tons. Despite the fact that Tanzania has a high potential for green vegetable production, the contribution of green vegetables to the national economy in terms of export earnings is very low.

7 Tanganyika Packers Limited (TPL) was a private company, which used to slaughter 200,000 animals per year from 1950 to 1974. In 1974, the company was nationalised and TPL lost its UK sanitary certificate and Marketing agreement with BBLL causing production and exports of corned beef to decline.


Green vegetable trade

Horticultural products are one of Tanzania’s nontraditional exports. The value of exports of horticultural products has been increasing in recent past. It has increased from about USD 116.8 million in 2002 to USD 136.2 million in 2003. However, a significant share of these exports is cut flower exports from Northern Tanzania (Arusha and Kilimanjaro regions). Green vegetables account for very small proportion of the horticultural exports. Most of the green vegetables produced in the country are consumed locally. Some of the vegetables are grown around urban areas to serve urban market and some of these urban areas like Arusha, Moshi and DaresSalaam are close Kilimanjaro and DaresSalaam international airports. Moreover, areas like Arusha and Kilimanjaro are close to Kenya where there is lively export trade in green vegetables. Yet export trade in green vegetables in Tanzania is limited compared to Kenya.

The few green vegetable exports are through Kenya. Like beef, green vegetables are relatively perishable and they are prone to food safety standards. Standards applicable to green vegetables and other horticultural products like fruits include Sanitary and Phythosanitary Standards (SPS) especially min. pesticide residues (MPRs). Therefore, Tanzania’s access to export markets for green vegetables will depend on the capacity of green vegetable growers to meet the costs of complying to these standards. The major reason why Tanzania is a negligible exporter of green vegetables is due to inability to comply with standards and quality requirements of importing countries. Consequently most of the green vegetables produced in Tanzania are sold in the domestic market especially in urban areas. However, more than 50% of the production is lost before reaching the market due to the perishable nature of vegetables coupled with poor transportation system, poor handling and preservation methods as well as lack of processing facilities.

Reforms and government support in green vegetable and horticultural sector as a whole

Priority in terms of reforms and government support in the agricultural sector has been given to the production of traditional export crops such as coffee, tea and cotton and staple food crops such as maize, beans, rice and sorghum. The marketing of green vegetables and horticultural crops as a whole has never been intervened by the government. Even before market liberalization, trade in green vegetables and other horticultural produce has been conducted by the private sector in a free market where supply and demand regulate prices.

POTENTIAL IMPACT OF WTO NEGOTIATIONS FOR THE SELECTED CROPS

The overall SIA study examines three scenarios: tariff reduction, reductions in export support and reductions in domestic support, which are used to generate effects of trade measures on world prices for reductions in export and domestic support, and on import prices for tariff reductions. Since Tanzania is a least developed country, export subsidies and reduced domestic support do not apply in the case Tanzania. Therefore the analysis in this section consists of examining the effects of assumed increases in the world price of the seven products selected for this case study.

Cotton

The review presented in Chapter two provides adequate empirical evidence that cotton growers in Tanzania respond to price incentives. Cotton supply has been found to be price responsive with shortrun supply elasticity of close to unity. Therefore a 10% increase in the world cotton price is expected to induce farmers to increase cotton production. The studies indicate that international price changes have been more fully transmitted to farmers after market liberalization than before market liberalization. This has in general resulted into a higher share of the export market price for lint cotton being passed through to farmers. An increase in the producers’ share of the export price from about 40% to about 50% is reported.

Economic impact

Assuming 50% share of the world cotton price, the price of seed cotton received by farmers would increase by about 5% if the world cotton price increases by 10%. This would likely increase cotton production by 5% if we assume a short run supply response of close to unity. However, due to constraints faced by smallholder cotton growers including inadequate pesticide supply, inadequate finance and poor infrastructure, the potential impact of increase in world cotton prices on cotton production will not be fully realized. Therefore production of seed cotton and exports of link cotton will probably increase by less than 5% if world price of lint cotton is increased by 10%.


The rise of price of cotton received by farmers and increase in cotton production have the potential of increasing farmers’ income from cotton and consequently expenditure on consumer goods and services such as health and education for children. Kakwemeire’s case study on the effect of crop marketing liberalization on cotton production and farmers’ income in Kahama district, in the Western Cotton Growing Area, provide empirical evidence of increase in farmers’ income from cotton production as well as their expenditure on consumer goods with increase in prices following liberalization, but the impact was considered to be less significant.

Increase in cotton production and trade also have a potential positive impact on self employment for those engaged in production and trading of seed cotton. However, rise in seed cotton price will likely have a long run negative impact on wage employment in local textile industries since cotton as a raw material will become more expensive and compel local textile industries to operate under capacity.

Impact on food security

In the Western Cotton Growing Area, cotton competes with maize for land and labour resources. Moreover, the two crops are planted during the same period. In the medium and longterm, there is likelihood of reducing maize farm sizes in favour of cotton if the increase in seed cotton price makes cotton price relatively higher than the price of maize. This would likely have a negative impact on own farm maize production and hence household food security 8 . In the Eastern Cotton Growing Area, cotton competes largely with paddy and maize for land and family labour. Similarly, if a 5% increase in seed cotton price makes cotton price relatively higher than maize and paddy price, farmers are likely to reduce maize and paddy land as well as labour in favour of cotton. The consequence will be decline in maize and paddy output and hence household food security.

Social impact

Apart from increased welfare through increased spending on consumer goods and services such as health and education resulting from increase in cotton income, increased cotton production has the potential of accelerating tree cutting and clearing of bushes in land used for livestock grazing. This may trigger conflicts between cotton growers and livestock keepers as it will reduce land available for grazing. Conflicts between cultivators and livestock keepers have been reported in agropastoral areas of Morogoro region.

Environmental Impact

Environmental impact may arise due increased use of pesticides and cutting of trees and clearing of bushes to expand cotton production with increase in price of seed cotton. Currently most farmers use pesticides at less the recommended rate and recommended spray regimes per season. The major reason for not using the recommended rates and recommended spray regimes is the prohibitive cost of pesticides 9 . Increase in cotton income as a result of rise in price of cotton relative to pesticide price would increase farmers’ purchasing power and intensify use of pesticides. Increased use of pesticides may have a negative environmental impact not only through pollution of rivers and streams by pesticide residues but also disturbing biodiversity.

While pollution of rivers and streams and impact on biodiversity are likely to occur in both cotton growing areas, environmental degradation through cutting down tress and bush clearing is likely to occur in the Eastern Cotton Growing Areas where most farmers practice shifting cultivation.

Sugar

The studies on sugar reviewed in Chapter two provide evidence that sugarcane growers and sugar producers responded to price incentives. However, there are constraints that prevent farmers from getting the full advantage of liberalization in the sugar industry. These include low sugarcane productivity levels, small capacity of sugar processing factories, inadequate finance and poor feeder roads. The studies indicate that farmers receive only about 46% of the world market price of sugar. If world sugar price increases by 15% import parity price of sugar price in DaresSalaam would increase by 15%. Since the world price is not fully transmitted to farmer, sugarcane price is likely to increase by about 7%.

8 Food security means more than household own food production. It is defined as access to food for all people at all times to ensure a healthy life. This can be achieved through own farm production and/or purchase. However, rural people in Tanzania consider themselves to be food secure if they produce adequate food to last the household for the whole year because dependency on food purchases in rural areas is constrained by several factors including inefficient food markets and poor road infrastructure. 9 Normally a minimum of four spray regimes per cropping season are recommended. The optimum number of spray regimes per cropping season is six.


Economic impact

In the short run, increase in sugar and sugar cane price will increase sugar output as there will be an incentive for sugarcane growers and processors to harvest and process more sugarcane. In the medium and long term, production of sugarcane and sugar output will increase through improved crop husbandry and increased crop acreage. Assuming a long run elasticity for sugar supply of close to unity, production of sugar is likely to increase by about 6%. On the other hand, increase in domestic sugar price will impact negatively on sugar consumption but the impact on consumption will be less significant than impact on production since demand for sugar in Tanzania is inelastic.

Increase in both sugar price and production will increase incomes of both out growers and estates involved in sugarcane growing and processing. Besides growers’ incomes, there will be impact on employment. Employment in sugar estates and out growers’ farms is expected to increase with expansion of sugarcane production and possible expansion of processing factories due to increased investment in processing facilities in the long run.


Impact of rise in world sugar price on food security will be negative. In almost all sugarcane growing areas, sugarcane competes with paddy for both land and labour. Paddy production is more labour intensive than sugarcane production. Thus returns to labour in sugarcane production are generally higher than returns to labour in paddy production. For example, during the 1999/2000 cropping season, returns to labour in Sugarcane production in Kilombero valley in Morogoro region were almost 8 times the returns to labour in paddy production (Mdoe, 2000). Other things remaining unchanged, increase in sugarcane price would likely provide an incentive of expanding sugarcane production at the expense of paddy production. Smallholder paddy growers around sugar estates are likely to shift from paddy to sugarcane production. This will have negative impact on paddy production and hence declining food security since paddy is a staple and preferred cereal especially in urban areas.

Social impact

Producers of sugar and sugarcane have the potential of gaining from higher sugar and sugarcane prices through increased income. Increased income will increase access to health and education services. On the other hand, consumers would lose by paying higher sugar prices.


Negative environmental impact is expected with the expansion of sugarcane production stimulated by increase in world sugar price. Impact on environment is expected to result from intensive use of chemicals and irrigation. BACAS (2004) reports intensive use of herbicides and fertilizers in sugarcane farms and estates in Morogoro region. Herbicides are used to reduce rate of weeding. Commonly used herbicides are GESAPAX, 500 F W and 2 4 Damine. Fertilizers are applied to improve soil fertility but the recommended type and the dose to be applied vary with the type of soil. In sugarcane production, fertilizers used include Urea, Sulphate of Ammonia (SA), NPK, TSP and DAP. Intensive use of both herbicides and fertilizers may impact negatively on the biodiversity. The sugarcane harvesting method also has the potential of impacting negatively on biodiversity and the impact is likely to increase with expansion in sugarcane production stimulated by rise in world sugar price. Sugar fields are usually burned before harvesting to reduce trashes and facilitate cane crushing. This does not only pollute the environment but also impact negatively on environment through biodiversity destruction.

Irrigation is mostly practiced by largescale estates. Smallscale out growers depend largely on rainfed farming. Price incentives with not only encourage expansion of estates but also intensity of irrigation to increase yields. This will have negative impact on the river systems and biodiversity. Another impact on river systems is pollution of water with herbicide and fertilizer residues as largescale sugar estates intensify use of fertilizers and herbicides coupled with irrigation. This is likely to reduce quality of water for domestic uses.

Rice

Although Tanzania produces rice, it is generally a net importer of rice. Before liberalization, the government has been trying to induce increases in domestic rice production though price incentives. Different short run supply elasticity estimates for paddy in Tanzania have been reported. Mbonde (1992) reported a supply elasticity estimate of 0.22 while Danielson (2002) reported elasticity estimates of about 0.13. McKay et al. (2002) reported short run elasticities for


aggregate food crops of 0.35 and long run elasticities of almost unity. All these elasticity estimates suggest that paddy producers respond positively to price incentives.

If a 515% increase in world rice price will on average increase domestic price of rice by about 8%, paddy price may likely increase by about 1016%, assuming paddy producers receive about 50% share of the world rice price.

Economic impact

In the short run, rise in paddy price will induce paddy trade as producers and traders with stocks of paddy will increase paddy sales. Production of paddy will increase by less than 5% in the short run and almost by 20% in the long run while imports are likely to fall drastically to the level that they would be cancelled, so Tanzania would likely become self sufficient in rice in the long run. Increase in producer price for paddy and household paddy output will increase incomes of paddy producers and spending on nonfarm consumer goods and services such as health and education.

Apart from increased income for producers there will be increase in selfemployment through involvement in paddy and rice trade and wage employment in largescale commercial rice farms. However, the impact on wage employment will be less significant due to limited number of largescale rice farms.

While producers are likely to gain when world rice price increases, consumers are likely to pay higher prices for imported rice. Consumption of rice is likely to decline by almost 10% if rice price rises by an average of 8%, assuming a price elasticity of demand for rice in urban areas of –0.958 as reported by Nyange (2000). If the import parity price for rice is relatively higher than prices of other cereals and starchy food items, there is likelihood for consumers to switch to relatively cheaper food products especially maize, which is the most preferred staple food in Tanzania. Estimates of cross price elasticities for food commodities in urban areas by Nyange (2000) suggest that a 10% increase in the price of rice would increase consumption of rice by 1.6%. Geographically, however, the impact on consumers will be small as only consumers in DaresSalaam and nearby regions with low transport costs from DaresSalaam will be affected. Local rice prices in areas far away from DaresSalaam are likely to be way below the import parity price for rice.

Social Impact

In the short run, rise in parity price for rice as a result of increase in world rice price will negatively affect consumers especially poor urban consumers in DaresSalaam and nearby areas where rice is not insulated from world market by high transportation costs. Eating habits of urban consumers where a typical diet consists of maize meal (ugali) for lunch and rice for dinner is likely to be affected and consumers may be forced to eat maize meal twice a day (lunch and dinner).

In paddy producing areas where the import parity price for rice will be an issue, there is likelihood of disputes related to land for irrigation due to increase in it demand. Increase in rice price has been found to increase demand for irrigated paddy land and movement of people to irrigated paddy growing areas, whose effects are manifested as increased pressure on land and water resources. In some rice irrigation schemes such as Kikafu Chini in Kilimanjaro, intensification of land use has increased and the rental value of land has more than doubled (FAO 1993). Also disputes related to land have been found to increase due to increased demand for irrigated land. Apart from utilizing irrigation water for paddy production, farmers have taken advantage of using the water for growing high value crops such as vegetables throughout the year. Consequently the quality of life of people in the rice irrigation scheme has improved as manifested by better houses (BACAS, 1998). These impacts are likely to happen in other rice growing areas with rise in the price of rice and paddy.


Increase in paddy production will increase food security at the household level in paddy producing areas and at the national level.


Significant negative impacts are likely to occur in irrigated paddy growing areas than in rainfed paddy growing areas. For example, in the irrigated paddy area of Kikafu Chini in Kilimanjaro region, BACAS (1998) reported environmental problems associated the spread of water borne diseases, soil erosion, and water pollution.

The major water related disease prevailing at Kikafu Chini is malaria, which is spread by mosquitoes. Another study carried out by Mosha et al. (1994) at the Lower Moshi irrigation scheme in Kilimanjaro has shown high prevalence of malaria and bilharzia parasites.


Soil erosion was found to be a serious problem at Kikafu Chini irrigation scheme. Soil erosion leads to increased siltation of irrigation canals, damage to irrigation structures, gullying, loss of fertile land and subsequent yield losses. A related problem to erosion is siltation. Sediments carried by water in streams and rivers may reduce water quality and cause undesirable deposition and sedimentation in other parts of the stream. Pollution hazards were found to be minimal in Kikafu Chini irrigation scheme since few farmers used chemicals. However, significant pollution hazards from intensive use of herbicides in largescale irrigated paddy farms is expected to occur. Use of herbicides to control weeds to reduce labour requirements is a common practice especially in large scale paddy production.

Environmental degradation through cutting down trees and clearing bushes to expand rice production as rice price increases is likely to occur in rainfed paddy growing areas where farmers practice shifting cultivation.

Wheat

Until recently wheat in Tanzania was mainly produced in largescale government parastatal farms. The interest of the farms was to produce wheat at any cost in order to reduce wheat imports. Their survival depended on government subsidy rather than profit made from wheat production. Therefore, wheat production was not responsive to prices of wheat. Wheat supply response studies done before privatisation of largescale wheat farms in early 1990s found insignificant response of wheat production to price changes (Mbonde, 1992). Since all wheat farms have been privatised, it is expected that private producers will respond to price incentives.

Almost all the wheat produced in Tanzania is consumed locally especially in urban areas but the country imports wheat to bridge the gap between domestic production and demand.

If the rise in world price of wheat increases import parity price by 10% and assuming a 50% producers share of the world market price, the price received by wheat producers is likely to rise by about almost 20%.

Economic impact

Assuming a short run wheat supply response of about 0.35 and a long run supply response of close to unity for food crops (Danielson, 2002), wheat production will increase by about 7% and about 20% in the short and longrun respectively if producer price increases by 20%. Wheat imports are likely to fall by almost 20%. Incomes of smallscale wheat producers will increase as a result of selling more wheat at a higher price. The impact on smallholder income is likely to be significant since there is low use of purchased inputs in smallholder wheat production (Mdoe, 2000).

In largescale farms, which produce most of the wheat consumed in Tanzania, there is potential for increase in wage employment due to expansion of wheat production but the impact on employment will be less significant because most of the wheat production operations are highly mechanized.

For consumers, consumption of wheat is likely to decline by about 10% if import parity for wheat increases by 10% as a result of increase in world wheat price, assuming a price elasticity of demand of –0.923 (Nyange, 2000) for cereals other than maize and rice in urban areas. With the increase in wheat price, there is likelihood of consumers switching to relatively cheap products. Since wheat is largely used for making bread and no other cereal is suitable for making good bread without mixing it with wheat and bread is a preferred food item for breakfast in urban areas, two things are likely to happen if wheat price is higher relative to other cereals. First, some consumers in urban areas are likely to switch from purely wheat bread to bread mixed with other relatively cheaper cereals such as millet and sorghum. Second, poor consumers can completely switch consumption from wheat bread to other food items for breakfast such as cassava, yams and potatoes.

Impact on Food Security

There is potential negative impact on food security if wheat price increases relative to competing crops in smallholder farming systems in highland areas. In major maize growing areas in the southern highlands, wheat competes with maize, which is the most preferred staple food for most Tanzanians. An increase in price of wheat is likely to induce smallholder farmers to expand wheat production at the expense of maize because wheat production is less input intensive than maize production. Reduction in maize production will reduce food security especially in the producing areas where wheat is not a preferred staple food. Findings by Nkwera (1994) in his case study on economic analysis of grain marketable surplus in Tanzania: The case of maize and wheat in Njombe indicate that wheat constitutes a very small share in the food basket of smallholder farmers in Njombe district.


Social impact

Smallholder wheat producers have the potential of gaining from higher world wheat prices through increased incomes from wheat sales and increased expenditure on nonfood consumer goods and services such as health. On the other hand, consumers who are mainly urban dwellers have the potential of losing from increased prices of imported wheat. Another potential social impact is increased conflicts between largescale wheat farms and Maasai pastoralists grazing their cattle around the farms. Such conflicts have been reported by Bernard (1993) in Arusha where most of the large scale wheat farms are located and the conflicts are likely to increase with expansion of largescale wheat production induced by higher world wheat prices.


Largescale wheat production is characterized by intensive use of chemicals especially herbicides to control weeds. Two categories of herbicides are used. The first category involves preemergence herbicides with residual effect which are applied immediately after planting while the second category involves post emergence herbicides which include systemic/contact herbicides used to control grassy and broad leaf weeds (Bernard, 1993). Increase in wheat production in largescale farms due to increase in wheat price is likely to intensify use of herbicides. Since wheat is grown in highland areas, the herbicides will not only impact on biodiversity in the wheat growing areas but also the potential of polluting river systems during rains.

Maize

There is ample evidence from literature that smallholder maize producers respond positively to price incentives. Danielson (2002) reports short run supply elasticity for maize of 0.113 while McKay et al. (1999) report shortrun supply elasticity of 0.35 for aggregate food including maize. The elasticity estimates are higher than the shortrun own absolute price elasticity of 0.06 reported by Mbonde (1992) although his estimate of relative price elasticity of supply for maize was 0.64. The higher value of relative price elasticity than the absolute value implies that maize production is more responsive to changes in the relative price of maize (maizecash crops price ratio) than to changes in it own absolute price.

If worldwide liberalization of agricultural trade raises maize prices by 10%, the import parity price for maize will increase by slightly less than 10%. The following are the potential impacts of an increase in international price of maize:

Economic impact

The impact of the rise in the international price of maize more detailed analysis than the impact on rice and wheat. For much of Tanzania, the ruling price of maize will be set by local costs of production plus the costs of delivery to the region in question. Local production costs are probably of the order of TShs. 95,000 (US$86) a tonne at the farm gate, to which another TShs. 25,000 (US$23) a tonne may be added for transport and storage costs. In the coastal areas around the major port of DaresSalaam, it is possible that import parity prices apply, since the coast is one of the most distant destinations for supplies from the main production areas in Mbeya, the Southern Highlands and Kilimanjaro Arusha. Import parity price would be around TShs. 130,000 (US$118) per tonne. Thus if world prices of maize rise, this has no effect on most Tanzanian maize markets because no export response is triggered, since export parity prices at farm gate would be too low.

But what happens on the coast, where the single main points of consumption, DaresSalaam, lies? If we estimate that one fifth of the Tanzania maize market is coastal, then the rise in the import parity price would likely to see maize consumption fall by around 2%. To some extent the consumers cutting back maize consumption would likely look for cheaper foods such as cassava and sweet potato to substitute for maize. Although rice and wheat are more by urban consumers than cassava and sweet potatoes, they could not switch to wheat or rice, since these are even more costly than maize.

However, when wheat and rice consumers cut back their consumption of these grains by a combined total of almost 10%, it is most likely that they will switch consumption to the cheaper alternative of maize. It is thus likely that there will some upward pressure on domestic maize prices, sufficient to cause growers to expand domestic production by just


4%. It is, however, highly unlikely that this would be sufficient to drive domestic prices anywhere near the import parity level.


In response to the increase in domestic maize price, there would likely be expansion of maize production in the coastal areas in the long run at the expense of cassava production. This may likely have a negative impact on food security in the coastal rural areas. These areas are considered to have a high potential for cassava production and cassava is considered to be a food security crop in Tanzania because it is less prone to drought than maize.

Impact on Environment

Intensification of maize production around DaresSalaam city through increased use of fertilizers and pesticides will likely to have negative impact on the environment. Intensive use of fertilizers and pesticides will not only affect the biodiversity but also the likelihood of polluting rivers and reducing water quality.

Beef

So far Tanzania does not export beef except a few live animals to neighbouring countries and the Middle East. However, there are limited imports of beef by supermarkets especially in large urban areas such as DaresSalaam and Arusha. Therefore, increase in world beef price by 10% will increase price of imported beef in urban areas of Tanzania. Consumers of imported beef will lose by paying higher imported beef prices.

Economic impact

Rise in export price is likely to provide an incentive to cattle keepers especially commercial ranches to produce beef for export if the 10% increase in world beef price can meet the costs of complying with quality standards of the importing countries. The increase in world beef price will not only stimulate domestic production of quality beef for export but also quality beef to meet the demand of the segment of consumers currently buying imported beef. There is also a potential gain in terms of increased income from sale of cattle by traditional cattle keepers as commercial ranches are likely to buy increased numbers of cattle for fattening and beef production. In the medium to longterm, investment in beef processing facilities are likely to increase and this has a potential positive impact on employment.

In the consumption side, consumption of imported beef is likely to decline by 9% if world beef price rises by say 10%, assuming price elasticity of demand for meat in urban areas of –0.914 reported by Nyange (2000). Consumers of the imported beef are likely to switch to other relatively cheap imported meat products. Otherwise they may switch to locally produced beef, which they generally consider of low quality.


Unlike traditional pastoralists and agropastoralist, expansion of commercial ranching will increase area under fodder crops. Moreover, use of grains as animal feed will increase. While increase in land under cattle fodder will reduce land for staple food production, grains fed to cattle will reduce food available for human consumption. Consequently the availability from domestic sources of food grains for the purpose of direct consumption by ordinary Tanzanians will decrease.

Social impact

Consumers of imported beef have the potential of losing from increase in imported beef if world prices increase by 10%. Another potential social impact, which is likely to occur is increased conflicts between cattle keepers and crop growers. Increase in commercial ranching will have impact on land ownership. Tanzania is about to start the implementation of a recently adopted land reform (the Land Act and Village Land Act of 2001), which includes significant changes to the way land can be acquired, held and transferred. The reform will facilitate the development of markets in land and private ownership of land is encouraged. Development of commercial ranching will transform land, which is currently owned by the community into private ownership. This could result into pastoral and agro pastoral people in villages near the ranches losing land used for grazing. Decline in public grazing land has the potential of increasing conflicts between livestock keepers and crop cultivators as well as the commercial ranches.


Green Vegetables

As pointed out earlier, there is very little export trade for green vegetables. Green vegetable trade is impeded by green vegetable growers inability to meet standards of importing countries. If export markets lower tariffs the following are likely to happen:

Economic impact

Domestic prices of green vegetables are likely to increase. If the rise in price is large enough to enable producers meet costs of complying with standards of export market, production of vegetables for export is likely to increase. This will particularly encourage expansion of green vegetable farming in and around urban areas where the vegetable can easily be transported to export markets.

Social impact

In the short run, consumers in urban areas especially the urban poor are likely to lose by paying higher prices for green vegetables. In the longrun consumers are likely to gain by paying low prices as a result of increased supply with expansion of green vegetable production in areas around towns and cities.

Another social impact is likely to be competition for water between domestic uses and green vegetable production as producers would like to maintain constant supply of green vegetables throughout the year.


In urban areas like DaresSalaam, Moshi and Arusha where livestock keeping is also practiced, there is likelihood of reducing problems of disposing animal dung, as most of it is likely to be utilized in green vegetable production. The impact to the environment in urban areas is likely to be positive.

SUMMARY, CONCLUSIONS AND RECOMMENDATIONS

More than 80% of Tanzanians live in rural areas: most of them are engaged in agriculture as their main occupation. Farming contributes more than 50% of GDP, while agricultural exports represented one third of the value of exports in 2003. Most of the land is cultivated in small parcels by households using at most rudimentary tools and few purchased inputs. Largescale commercial farming and ranching operations are few and far between.

Tanzania is a large country with much variation in its geography so that it can produce a wide range of crops and animal products. However, the large size of the country, combined with relatively sparse road and rail networks, means that transport costs are high.

Since Tanzania liberalised its economy, starting in the 1980s and with increased vigour in the 1990s, there have been several studies of the impact of overall, and specific trade, liberalisation on agriculture and on particular farm enterprises. By and large these show some favourable impacts in that farmers have usually seen both their share of the world price, and the absolute price for their produce rise. In most cases, farmers have responded by increasing their production.

Their ability to do this, however, has been limited by rising costs of inputs, plus limited supply of these in the more remote areas where private dealers are reluctant to operate, decreased availability of formal credit, privatisation of previously free government services, and in some cases the imposition of new taxes and levies on profitable crops. Inability to meet international standards for hygiene and quality has prohibited exports of beef and impeded those of green vegetables. It is thus a working hypothesis that obstacles in the supply chain may play a greater role in affecting farmer decisions than price levels in the national market.

As a leastdeveloped country, Tanzania is largely exempted from the provisions of the Agreement on Agriculture(AoA). In any case, even if it were not an LDC, export subsidies do not exist, and domestic support to agriculture is minimal so that obligations would apply only to tariffs on imports. Hence in this, the analysis consists of examining the effects of assumed increases in the world prices of key products produced and consumed in Tanzania, consequent on the rest of the world complying with the provisions of the AoA.

The results are summarised in Table 9 below:


Table 9: Impacts of increased world prices in selected products on Tanzania

Product Impacts Economic Food security & Social Environmental

Cotton 10% rise in world price, transmits to 5% grower prices. Increased cotton production, attenuated by problems in access to inputs and finance

Expanded cotton area may mean less maize planted in west, and maize and paddy in the east. If land is cleared, it may remove livestock grazing and trigger conflicts with cattle keepers. May be job losses in textile mills from higher cotton prices.

The environment could suffer from cutting trees to clear land, and from increased use of pesticides.

Sugar 15% increase in world sugar prices drives up local prices of sugar by 15%, and grower prices up by 7%. Production rises by 6%, with consequent gains to jobs in processing.

Domestic price rise scarcely affects consumption due to inelastic demand. Land likely to be switched from rice to sugar, with loss of rice production.

Environmental harm due to increased use of herbicides, fertiliser and irrigation.

Rice A 515% increase in world rice price will increase domestic price of rice by about 8%, with growers getting about a 1016% increase. Expanded production, jobs on land Rice imports likely to fall drastically and Tanzania would likely become self sufficient in rice in the longrun. Rice consumption likely to decline by 10%. Possible switching of consumers to relatively cheap food items, probably maize or cassava

Improved food security at household and national levels. Consumers lose by paying higher rice prices. Eating habits of urban consumers especially the urban poor likely to be affected.

Negative impacts on the environment from water borne disease where irrigation is used, erosion, some pollution

Wheat Production likely to increase by 7% in short run and 20% in long run. Wheat imports likely to fall by almost 20%.

Significant increase in smallholder producers incomes Insignificant increase in wage employment in largescale wheat farm. Wheat consumption likely to decline by 10% with possible switching to relatively cheaper related products.

Loss of maize fields due to expanded wheat farms. Expanded wheat fields may lead to conflicts with herders. Consumers lose by paying higher wheat prices. Eating habits of poor urban consumers affected less or no bread for breakfast.

Concerns over more use of herbicides negative impact on biodiversity, pollution and reduction of water quality..

Maize A 10% increase in world maize price will increase import parity price for maize by 10%. In the short run, consumption of maize declines by almost 2%. Switching to relatively cheap products of cassava and sweet potatoes by consumers in coastal

Consumers in DaresSalaam city and nearby urban areas lose. Switching to maize production at expense of cassava land likely to put food security at stake.

Urban environment likely to be affected by increased use of fertilizers and pesticides in areas around city and towns.


areas is likely. In the long run, production likely to rise by 4%

Beef Increase in beef price may stimulate commercial production of beef for export. Incomes of traditional cattle keepers likely to rise through sale of cattle for fattening. Employment in beef processing plants likely to increase. Consumption of imported beef likely to decline by 9% with possible switching to relatively cheap imported meat products

Rise in prices may hurt consumers of imported beef. Food security hit by expanded area to grazing, and of use of grains as animal feeds. Concerns over access to land given the recent land act of 2001 that encourages private ownership of land.

Green vegetables

Domestic prices of green vegetables likely to increase. Green vegetable production around urban areas for export likely to increase

Urban poor consumers likely to lose by paying higher prices in short run. In longrun, consumers likely to gain by paying low prices.

Positive environmental impact through utilization of animal dung for vegetable production.

Overall, the analysis of the impact of increased world prices on the selected seven crops show that the increase prices will transmit to growers of most of the crops (except maize) by more than the world price rise, and encourage increased production by almost twice the price rise, given a longrun supple elasticity of unity for most products. In some cases, however, failings in the supply of inputs, finance and marketing may limit producer response. But we can expect farmers and farm labourers to gain.

For maize, the ruling price of maize in most parts of Tanzania will be set by local costs of production plus the costs of delivery to the region in question. Local production costs are probably of the order of TShs. 95,000 (US$ 86) a tonne at the farm gate, to which another TShs. 25,000 (US$23) a tonne may be added for transport and storage costs. In the coastal areas around the major port of DaresSalaam, it is possible that import parity prices apply, since the coast is one of the most distant destinations for supplies from the main production areas in Mbeya, the Southern Highlands and KilimanjaroArusha. Import parity price would be around TShs. 130, 000 (US$ 118) per tonne. Thus if world prices of maize rise, this has no effect on most Tanzanian maize markets because no export response is triggered, since export parity prices at farm gate would be too low.

Imports of both rice and wheat fall but the fall in rice imports more than cancels out average imports, implying that Tanzania would probably become self sufficient in rice production in the long run.

Domestic net consumers of foodstuffs will lose by the rises in the prices of rice, wheat, beef and sugar; and in some cases by loss of domestic maize production as land is switched to other crops. For maize, if we estimate that one fifth of the Tanzania maize market is coastal, then the rise in the import parity price would likely to see maize consumption fall by around 2%. To some extent the consumers cutting back maize consumption would likely look for cheaper foods such as cassava and sweet potato to substitute for maize. Although rice and wheat are more by urban consumers than cassava and sweet potatoes, they could not switch to wheat or rice, since these are even more costly than maize.

However, when wheat and rice consumers cut back their consumption of these grains by a combined total of almost 10%, it is most likely that they will switch consumption to the cheaper alternative of maize. It is thus likely that there will some upward pressure on domestic maize prices, sufficient to cause growers to expand domestic production by just 4%. It is, however, highly unlikely that this would be sufficient to drive domestic prices anywhere near the import parity level.

Social conflicts between herders and cultivators may be exacerbated where the incentives are to expand production by increasing the land area used. This applies throughout much of lowland Tanzania, above all in the north of the country, where pastoralists and crop farmers live sidebyside using different parts of the ecosystem.

The environment could suffer from removal of trees and bush to create new crop fields, and from increased use of crop chemicals that potentially pollute watercourses and reduce biodiversity by poisoning some plant and animal species.


All this said, much depends on the ability of those in the supply chain from farmers grouped in associations to traders to processors and multinational corporations to resolve the current problems of inputs and finance; and on complementary measures by government, through investments in roads and other physical infrastructure, and public measures to remedy market failures. The more success there is in these two fields, the more likely the trade liberalisation effects are to be benign and significant.

REFERENCES

Amani, H.K.R. (1992). Agricultural market reforms in Tanzania: Evolution, performance and future policy issues. In: Market Reforms and Parastatal Restructuring in Tanzania, Bagachwa, M.S.D and N.Y. Mbele 9Eds.). Economic Research Bureau, University of DaresSalaam.

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Agriculture, The Case of Brazil

C. Azzoni, J. Guilhoto, E. Haddad and F. Silveira 10

1. Introduction

This report presents the results of the study “Sustainability Impact Assessment of WTO Negotiations, Agriculture: The Case of Brazil”, prepared by Fipe – Fundação Instituto de Pesquisas Econômicas, to ODI – Overseas Development Institute.

The objective of this study was to assess the likely impacts of a scenario of trade reform in the agriculture sector, as anticipated under WTO negotiations. To do this, a SAMbased model originally developed for OECD by researchers at FIPE was used. The results contain structural information from the SAM provided to OECD, as well as associated model results. However, the model specification and scenario analysis differ from those adopted by OECD. Hence, the corresponding results also differ.

The document is organized following the outline jointly agreed by the research teams of both institutions. According to that, the report presents two sections, in addition to this introduction. Section 1 presents a brief overview of the model used in the simulations, while Section 2 presents results of the simulation focusing on the economic, social and environmental impacts of a scenario of trade reform based on the guidelines provided by ODI.

2. Overview of the Model

2.1. Sectoral Disaggregation

The inputoutput matrices released by the Brazilian Statistical Institute (IBGE) only take into consideration agriculture as a whole and 7 food processing industries, out of a total of 42 sectors. Using information from the national accounts, agricultural census, sectoral prices, and yearly agricultural and sectoral surveys, agriculture was broken down into 9 activities and 17 products 11 , while foodprocessing industries were disaggregated into 11 activities and 13 products. Two nonfood items, alcohol (treated separately from the chemical sector) and textiles receive special consideration, for their attachment to agricultural activities. Three important agricultural inputs are included, namely, tractors, fertilizers, and other chemicals (defensives). Two relevant sectors for the distributive chain of agricultural products, trade and transportation, are also highlighted. The remaining activities of the economy are aggregated into three sectors: services and government, resource oriented industries (forestry and mining), and other manufacturing. Table 1A presents information on the sectoral (activity) aggregation in the model; Table 1B presents information on the number of activities and products, as well as product destination.

Table 1A. Sectoral Aggregation Sugar cane Soybean Corn Fruits Other crops Poultry and egg production Cattle ranching and farming Hog and pig farming Other animal production Coffee industries Alcohol Sugar

10 Research Team at Fipe, Brazil. Draft provided to ODI, December 2004. 11 For example, the activity “other crops” includes coffee, rice, wheat, beans, cassava, cotton, and others; the activity “fruits” includes orange, and other fruits and vegetables.


Vegetal oil processing Vegetal products processing Poultry industries Beef industries Other meat industries Dairy industries Animal feed Other food products Beverage Textiles Agricultural machinery industries Fertilizers Other chemical elements Resource oriented industries Other industries Trade Transport Services and government

Table 1B. General Information on Activities and Products Included in the SAM

Production destination (%) Consumption

Activities Products

Share in Production (%)

Intermediate Use Households Government Exports Sum

Raw agricultural products 9 17 6.6 71.4 25.6 0 3 100 Processed food products 11 13 8.2 29.2 57.2 0 13.6 100 Alcohol 1 1 0.9 76.1 22.5 0 1.4 100 Textiles 1 1 5.2 90.4 3.3 0 6.3 100 Agricultural inputs 3 3 0.5 99.3 0 0 0.7 100 Trade 1 1 0.6 53.3 37.9 0 8.9 100 Transportation 1 1 3.4 52.4 40.9 0 6.7 100 Services and government 1 1 35.6 21.2 44.7 32.6 1.6 100 Resource oriented industries 1 1 1.7 77.6 5.8 0 16.6 100 Other manufacturing 1 1 37.3 66.1 24.7 0 9.2 100 Sum 30 40 100 42.9 34.6 17.1 5.4 100

Table 1C presents more details on the importance of sectors. It can be seen that non agriculturerelated sectors account for only 74.62% of total national production, in spite of the fact that Brazil is a major world producer of several products. In this table, trade and transportation activities are included in the group of agriculturerelated activities. This is of course an overestimation, indicating that the share of agriculturerelated sectors would be even smaller 12 . Agricultural activities per se account for only 6.6%, and food processing industries for 8.2%. Each of these is less important, quantitatively, than distribution activities (with a share of 8.7% in total production). This reflects the fact that the Brazilian economy is large and diversified, and that urban activities are by far more important.

12 The share of agribusiness activities in Brazilian GDP in 2003 was 30.81%, reflecting the growth in these activities after 1999, clearly well above other sectors in the Brazilian economy. For more details, see (http://www.cepea.esalq.usp.br/pib/other/pib_agronegocio_1994_03.xls).


Table 1C. Output Share, by Product, 1999

Production Value (US$ 1,000) %

Production Value (US$ 1,000) %

Raw agricultural products 6.61% Processed food products 8.19% Coffee 3,776,279 0.40% Coffee products 6,749,905 0.71% Sugar Cane 3,042,287 0.32% Sugar 4,388,781 0.46% Rice 2,281,101 0.24% Rice products 1,665,388 0.18% Wheat 277,731 0.03% Wheat flour 2,258,098 0.24% Soybean 4,302,112 0.45% Vegetable oil mills 9,275,711 0.98% Corn 2,811,213 0.30% Other vegetables 11,270,475 1.19% Beans 1,003,527 0.11% Poultry products 4,759,649 0.50% Cassava 1,292,612 0.14% Beef products 5,716,668 0.60% Orange 838,206 0.09% Other meat products 5,614,827 0.59% Other Fruits and vegetables 2,428,879 0.26% Dairy products 6,261,652 0.66% Cotton 539,715 0.06% Animal feed 4,356,302 0.46% Other Crops 12,317,972 1.30% Other food products 8,660,971 0.91% Poultry and egg production 3,336,100 0.35% Beverage 6,763,839 0.71% Cattle ranching and farming 7,090,160 0.75% Other agriculturerelated 1.06% Hog and pig farming 2,063,300 0.22% Alcohol 4,739,058 0.50% Milk farming 3,691,624 0.39% Textiles 5,347,674 0.56% Other animal production 11,587,790 1.22% Other sectors 74.62% Agricultural inputs 0.85% Resource oriented products 16,056,473 1.69% Tractors 1,097,795 0.12% Other manufacturing 354,002,945 37.31% Fertilizers 4,497,500 0.47% Services and government 337,849,289 35.61% Agricultural defensives 2,439,861 0.26% All products 948,712,411 100% Distribution activities 8.67% Trade 49,618,898 5.23% Transportation 32,640,042 3.44%

Table 1D presents the importance of imports and exports for each product. Imports are very important for wheat, considering the insufficiency of local production in 1999. Tractors come second, with imports accounting for 38.4% of production value, although almost the same share is also exported; other inputs are also important, but to a lesser extent. In the raw agricultural products group, the most important importers are rice and corn. In the food processing area, rice products, dairy and beverages dominate. The very large imports are resource oriented products and other manufacturing products. On the export side, the highest percentage of production value exported belongs to tractors, followed by sugar, coffee products and soybeans. The foodprocessing group is the most important in terms of export value, with an average of 13.7% of total value exported. Raw agricultural products are less of an export item, except for soybeans, for most of Brazilian agriculturerelated exports are processed food (even if in the early stages of processing). Imports of fertilizers and defensives are also important for Brazilian agriculture.

Table 1D. Imports and Exports, by Products, 1999

Imports Exports

Value US$ Share

Share of Production Value Value US$ Share

Share of Production Value

Coffee Sugar Cane Rice 1 05.803.40 0.20% 4.60% 13.78 Wheat 9 26.698.82 1.50% 333.70% 306.16 0.10% Soybean 8 0.631.62 0.10% 1.90% 1.339.475.16 2.60% 31.10%


Corn 8 6.735.31 0.10% 3.10% 6.563.02 0.20% Beans 1 9.740.48 2.00% 1.221.12 0.10% Cassava 2 5.725.84 2.00% 227.41 Orange 1 6.309.41 1.90% 21.537.40 2.60% Other Fruits and vegetables 4 5.161.30 0.10% 1.90% 1 52.198.98 0.30% 6.30% Cotton 9 2.46 230.71 Other Crops 2 41.688.99 0.40% 2.00% 73.451.46 0.10% 0.60% Poultry and egg production 1 7.579.61 0.50% 1 0.411.22 0.30% Cattle ranching and farming 1 4.764.24 0.20% 924.48 Hog and pig farming 3 .627.84 0.20% 104.53 Milk farming Other animal production 2 20.792.92 0.30% 1.90% 96.976.45 0.20% 0.80%

1 .805.352.22 2.80% 2.90% 1 .703.641.87 3.30% 2.70% Coffee products 1 .258.57 2.167.680.92 4.20% 32.10% Sugar 1 .611.38 1.561.108.75 3.00% 35.60% Rice products 1 58.488.26 0.20% 9.50% 1 0.058.50 0.60% Wheat flour 4 6.236.55 0.10% 2.00% 688.59 Vegetable oil mills 2 55.360.10 0.40% 2.80% 2.067.267.01 4.00% 22.30% Other vegetables 3 59.193.78 0.60% 3.20% 1 .948.410.45 3.80% 17.30% Poultry products 5 60.56 0.00% 727.865.10 1.40% 15.30% Beef products 6 9.701.29 0.10% 1.20% 503.371.97 1.00% 8.80% Other meat products 6 9.218.46 0.10% 1.20% 3 24.984.90 0.60% 5.80% Dairy products 4 50.463.57 0.70% 7.20% 5.880.18 0.10% Animal feed 1 98.677.88 0.30% 4.60% 404.950.91 0.80% 9.30% Other food products 3 51.870.06 0.60% 4.10% 5 48.255.22 1.10% 6.30% Beverage 3 38.380.42 0.50% 5.00% 108.549.52 0.20% 1.60%

2 .301.020.89 3.60% 3.00% 1

0.379.072.04 20.10% 13.70% Textiles 4 72.398.69 0.70% 8.80% 329.774.71 0.60% 6.20% Alcohol 4 .257.51 0.10% 71.784.44 0.10% 1.50%

4 76.656.20 0.80% 3.90% 4 01.559.15 1% 3.30% Tractors 4 21.574.05 0.70% 38.40% 415.951.10 0.80% 37.90% Fertilizers 8 16.027.76 1.30% 18.10% 3 2.888.27 0.10% 0.70% Agricultural defensives 4 29.016.59 0.70% 17.60% 17.178.81 0.70%

1 .666.618.40 2.60% 20.70% 4 66.018.17 0.90% 5.80% Trade 3 77.781.34 0.60% 0.80% 4.162.171.59 8.10% 8.40%

2.174.683.49 4.20% 6.70% Transportation 3 77.781.34 0.60% 0.10% 6 .336.855.09 12.30% 1.70% Resource oriented products 3 .295.838.06 5.20% 20.50% 2.713.451.53 5.30% 16.90%

Other industrial procuts 4 3.412.602.93 68.40% 12.30% 2

4.616.735.89 47.70% 7.00% Services and government 1 0.178.166.37 16.00% 3.00% 5.019.717.51 9.70% 1.50%

5 6.886.607.37 89.60% 13.50% 32.349.904.93 62.60% 7.70% Total 63.514.036.42 99.80% 7.60% 51.637.051.26 100.00% 6.10%

Table 1E expands on information of Table 1B, showing the destination of production for every product. Most agricultural raw products go to intermediate use, 71.4% on average, but some sectors sell mainly to household consumption, such as other animal production (78.4%), other crops (39.2%), other fruits and vegetables (26.2%), milk farming (23%), poultry and eggs (15.4%), and orange (15.1). The processed food group allocates only 29% of production to intermediate use, with most products being allocated to household consumption, and some to exports. The most important in this respect are rice (85.5%), other food products (81.3%), poultry (78.7%), dairy products (75.8%). Alcohol and textiles are mainly for intermediate use, but alcohol is also used for household consumption (even as automobile fuel). Within the system, the service sector (that includes government), allocates its production to all destinations, with a larger share to households.


Table 1E. Destination of Output, by Product, 1999

Consumption Intermediate use Household Government Export Sum

Coffe 100 0 0 0 100 Sugar 99.9 0.1 0 0 100 Rice 100 0 0 0.00 100 Whea 100 0 0 0.10 100 Soybea 70 0 0 30.10 100 Corn 98 1.9 0 0.20 100 Bean 88 12.4 0 0.10 100 Cassav 92 8 0 0.00 100 Orang 82 15.1 0 2.70 100 Other Fruits and 68 26.2 0 5.80 100 Cotto 100 0 0 0.00 100 Other 60 39.2 0 0.60 100 Poultry and egg 84 15.4 0 0.30 100 Cattle ranching and 100 0 0 0.00 100 Hog and pig 100 0 0 0.00 100 Milk 77 23 0 0.00 100 Other animal 21 78.4 0 1.00 100 Coffee 27 33.7 0 39.00 100 Suga 43 22.4 0 34.90 100 Rice 14 85.5 0 0.60 100 Wheat 89.3 10.7 0 0.00 100 Vegetable oil 47 30.4 0 22.80 100 Other 13 70.1 0 17.40 100 Poultry 6 78.7 0 15.50 100 Beef 21 70.1 0 8.90 100 Other meat 25 69.7 0 5.70 100 Dairy 24 75.8 0 0.10 100 Animal 65.1 24.6 0 10.30 100 Other food 12.6 81.3 0 6.00 100 Beverag 42.6 55.8 0 1.60 100 Alcoho 76.1 22.5 0 1.40 100 Textile 90.4 3.3 0 6.30 100 Tractor 33.4 0 0 66.60 100 Fertilizer 99.3 0 0 0.70 100 Agricultural 99.3 0 0 0.70 100 Trad 53.3 37.9 0 8.90 100 Transpo 52.4 40.9 0 6.70 100 Resource oriented 77.6 5.8 0 16.60 100 Other industrial 66.1 24.7 0 9.20 100 Services and 21.2 44.7 32.6 1.60 100

2.2. Farm Household Typology

In the model used in this study, there are ten different household groups (Table 2A). Agricultural households are split into two groups: family and commercial. The first is subdivided into four groups, according to income levels. A sixth type of agricultural household is included, namely, agricultural wage earners. The nonrural households are subdivided into four groups, according to income quartiles.


Table 2A. Household Groups Agric Fam 1 Agric Fam 2 Agric Fam 3 Agric Fam 4 Business Agric Agric Employees Urban Households 1 Urban Households 2 Urban Households 3 Urban Households 4

One of the main sources for the study of rural households is FAO/Incra (2000). Based on the last agricultural census (1995/96), this study proposed a classification of family agriculture in Brazil using farm level data. Another important data source is the survey “Pesquisa Padrão de Vida PPV” (Living Standard Survey), developed by IBGE in partnership with the World Bank, also referring to 1995/96. This study is comprehensive, containing information on both income sources and consumption expenditures, but is based on a small sample of urban and rural households (just under 5,000). Other important data source is the yearly PNAD – “Pesquina Nacional por Amostra de Domicílios” (National Survey of a Sample of Households), by IBGE, presenting data on income sources for both urban and rural households, although for the latter coverage is limited. Finally, information on consumption structures came from PPV and from “Pesquisas de Orçamentos Familiares” (Household Expenditure Surveys) of 1987/88, and 1995/96, covering 11 metropolitan areas in the country.

Some information needed to develop the study is defined at the farm (establishment) level, and others are defined at the household level, such as income sources, and consumption structures; thus it was necessary to rearrange and consolidate the available data sources covering these different dimensions in order to get consistent results. Table 2B presents information on rural and urban earnings. The poorest family farm group A accounts for 35% of persons in the family farm segment, and earns 60% of the poorest urban group (G), indicating the lower income levels in the rural area. The richest family farm group (D), representing only 17% of the family farm segment, earns on average more than the third of the urban income group (I). Commercial farmers and the upperlevel family farmers (groups D and E) receive less than half the income of the richest urban inhabitants (group J). Within the family farm segment, inequality is high, with income doubling from group A to B, and B to C, and almost tripling from C to D. Although pension payments are more valuable for urban families, they are very important for family farms C and D, for they are closer in value to the labor income in rural activities.

Table 2B. Sources of Income(R$/month), by Household Group


2.2.1. Some characteristics of family and commercial farms

The average size of family farms is 26 hectares, and of commercial farms is 433 hectares. Around 87% of family farms present area below 50 hectares. Family farms account for only 4% of total hired labor. The same situation is observed for loans obtained, with commercial farms accounting for 73.8% of the total amount of money lent to agriculture. Provision of electricity is present for 64.5% of commercial farms, but only 36.6% of family farms; technical assistance is used by 43.5% of commercial farms, but only 16.7% of family farms. In terms of technology, the same divide between the two groups is present, with 56.5% of commercial farms using fertilizers and inputs for soil correction, and 33.2% using some sort of soil conservation; the proportions for family farms are 36.7%, and 17.3%, respectively. In terms of income per farm, the average for commercial farms is R$ 19,085 per year, while for family farms it is only R$ 2,717. Table 2C shows that monetary income accounts for 86% of total income for commercial farms, compared to 66% for family farms, indicating the importance of selfconsumption for the latter. For family farms only, it is observed that 46% have total income below R$ 98 per year, and negative monetary income 13 . Of those, 63% are located in the Northeastern region. At the other extreme, 10% of family farms present yearly income of R$ 16,000, and are concentrated in the South/Southeast region of the country. For the poorer farmers in the Northeast, monetary income accounts for only 24% of total income, and 73% for the same group in the South.

Table 2C. Income, by Household Type

Table 2D shows the contribution of family farms to the regional value of production. In terms of area, family farming accounts for 30.5% of the country’s farming area, and it is more important for the poorer Northeastern and Northern regions, but also for the richer South. The regional importance of family agriculture varies across products, and its importance for different products varies across regions. For example, manioc is basically a family farm crop, but its share in production value is smaller in the MidWest and the Southeast, as compared to the other regions. Cattle ranching are mainly commercial in the MidWest, but the family share in the Northeast is much higher. Another example is soybeans, which are typically commercial everywhere, except in the South, where family farming accounts for over 50% of production value.

13 This is indicative of how poor those families are. A negative monetary income means that farms are not profitable in their commercial activities, and that families live mostly on nonmonetary income. Some nonrural income might be used to cover the deficit.


Table 2D. Share of Family Farming in Production Value

2.3. The Structure of the SAM

The structure of the SAM for the Brazilian model is presented in Figure 1. The construction of the Brazilian Social Accounting Matrix (SAM) uses as its basis the inputoutput system constructed for the Brazilian economy, as well as the Brazilian National Accounts, for the year of 1999. Figure 1 displays the main accounts in the SAM without the distinction between agricultural and nonagricultural accounts.

Figure 1. Main Accounts in the Brazilian SAM Capital Labor Land

A B C D E F G H I J K L M N O 1 B 1 H 1 2 A 2 F 2 H 2 J 2 N 2 O 2

Capital 3 A 3 Labor 4 A 4 Land 5 A 5 HH 6 D 6 G 6 H 6 Firms 7 C 7 E 7 H 7

Government 8 K 8 L 8 9 A 9 F 9 N 9 10 M 10 11 A 11 F 11 I 11 J 11 N 11 12 A 12 F 12 G 12 13 G 13 I 13 14 F14 G 14 H 14 M 14 15 G 15

Rest of the World Accumulation

Financial Dummy

SAM for the Brazilian Model

Imports Exports

Ind Taxes on Prods Other Taxes

Institutions

Domestic Activities Domestic Products

Factors

Acc. Fin. Dummy Exports Ind

Taxes Other Taxes ROW HH Firms Gov Imports Dom

Activts. Dom. Prods.

Factors


The matrices displayed in column A (A2, A3, A4, A5, A9, A11, and A12) come from the use matrix of the IO system constructed. While the matrix displayed in B1 is the make matrix of the IO system. Matrix C7 is the transpose of matrix A3, while matrix E7 is the transpose of matrix A5. Matrix D6 is constructed by allocating to each one of the elements of its main diagonal the result of the sum along the rows of matrix A4.

Matrix F2 is obtained by allocating the consumption of households as obtained in the IO system to the consumption of the 10 types of families, based on specific information. These were used for agricultural family types 1 to 6 and for urban families type 1 to 3, with the results for urban family type 4 obtained as a residual. Matrix F9 is obtained in a similar way as matrix F2. Matrix F11 is obtained by estimating the indirect taxes on the consumption of domestic and imported goods made by families, and than adjusting the system such that the total of indirect taxes is consistent with the results obtained in the IO system. Matrix F12 (other taxes) is obtained by allocating income taxes, property taxes, and social security taxes (paid by individuals), as displayed in the national accounts, to the ten household types considered in the model. Matrix F14 is obtained as a residual after estimation of total income of each household type, which is obtained by the sum o matrices D6, G6, and H6. Matrix G6 is obtained as a residual, by subtracting from the total income of the firms (sum of C7, E7, and H7) the expenditures on other taxes (G12), rest of the world (G13), accumulation (G14), and financial dummy (G15).

Matrix G12 is estimated based on income tax paid by firms, as presented in the national accounts. Matrix G13, also based in the national accounts, displays the payments made by firms to the rest of the world. Matrix G14 is obtained by allocating total firms savings, as displayed in the national accounts, to the firms considered in the SAM. Matrix G15 is obtained by allocating the Financial Dummy presented in the national accounts and in the IO use matrix to firms. Matrix H1 is obtained from the IO use matrix and refers to the subsidies paid by government to domestic activities. Matrix H2 is obtained form the IO use matrix and refers to the purchases of public goods made by government.

Matrix H6 refers to the transfers and interest paid by government to the households, as presented in the national accounts. Matrix H7 refers to the transfers and interest paid by the government to the firms, as presented in the national accounts. Matrix H14 is government net savings, as displayed in the national accounts. Matrix I11 shows the indirect taxes paid by imported products, while matrix I13 displays the total value of imports net of indirect taxes. These values come from the use matrix of the IO system.

Matrix J2 displays the value of the exports made by the Brazilian economy, while matrix J11 displays the indirect taxes on those exports. These values come from the use matrix of the IO system. Matrix K8 is the allocation of indirect taxes (sum of matrices A11, F11, I11, J11, and N11) to government. Matrix L8 shows the allocation of other taxes (sum of matrices A12, F12, and G12) to government.

Matrix M10 represents the payments of the rest of the world to exports, i.e., it shows the value of total exports made by the Brazilian economy, as obtained by the sum of matrices J2 and J11. Matrix M14 is the net external savings, as displayed in the national accounts. Matrix N2 is the consumption of national goods made by the gross fixed capital formation, as displayed in the use matrix of the IO system. Matrix N9 is consumption of imported goods made by the gross fixed capital formation, as displayed in the use matrix of the IO system. Matrix N11 presents the indirect taxes paid by the gross fixed capital formation for the consumption of the domestic and imported goods. Finally, Matrix O2 displays the allocation of domestic products to the financial dummy, as shown in the national accounts and the use matrix of the IO system.

2.4. Solving the Model

The goal of this subsection is to describe the various relationships embedded in the model. Its solution considers reactions of consumers to price and income changes, and reactions of producers to input price changes. It does not include, however, substitution effects between products and sectors. It is structured in five stages, as described below. The sum of the results calculated in these stages, partially considering the reactions of agents to price and quantity stimuli, comes close to a full general equilibrium model. In previous applications, it has been shown that the disaggregated results provided by the model estimated in this study are compatible, at the aggregate level, with the ones resulting from the fully specified CGE model.

2.4.1. Model solution mechanics

As a result of structural reforms in international trade, prices of commodities exported by the Brazilian economy are expected to change. It is expected that the international supply curve of protected commodities will shift upwards, leading to increases in international prices, as portrayed in Figure 2 below.


Figure 2. Expected Effects in the World Market

International Prices

Volume traded

World Supply

World Demand

Some countries will be negatively affected by the changes, some countries positively. It is expected that the demand for Brazilian exports will increase. The effects on domestic prices will depend on the elasticity of domestic supply. In the case of a flat domestic supply curve, there will be no increase in the domestic price of the commodity, and thus no reduction in domestic consumption, and total production will increase by the amount of exports. In the most probable case of some price transmission to the domestic market, the domestic price is expected to increase, leading to a reduction in the domestic consumption. Thus, the final increase in production will not be the full amount of exports, as before, but a smaller amount. It will be equal to the increased amount of exports, less the decreased amount of domestic consumption (assuming this domestic price increase will not affect the country’s competitiveness in the international market).

In order to estimate the impacts of this chain of events, the first stage of the model estimation simulates a situation in which the whole increase in export volume is used to shock the model, ignoring any price increases. No restriction is imposed on the supply of inputs either. In other words, this stage simulates an increase in exported quantities at the previous price level. The results of this stage indicate the upper bound effect on national production, admitting that the additional production does not cause any price effect on the domestic market. Additional exports will be added to the previous production, imposing direct, indirect and induced effects on the system.

The price transmission from international to domestic prices considered is the one obtained from the resulting scenarios from ODI. These estimates present expected international price changes as well as domestic price changes. This domestic price change for a product is supposed to spread to all prices in the economy through a Leontieftype price transmission mechanism. For example, an increase in the domestic price of soybeans will affect in the first place the prices of all sectors utilizing this product as an input, at fixed coefficients. In later stages, all prices will be affected in some way through the indirect effects generated by the original price increases.

The estimated domestic price changes will increase or decrease the production value of the specific product, depending on the priceelasticity of that product’s demand. For a product with priceinelastic demand, which is the case of almost all food products, a domestic price increase will result in increased production value and income for that activity. In order to keep total income constant in the system, this extra income is transferred from all other sectors in the economy, whose incomes will fall proportionately to their participation in total production. Considering these changed incomes and the price changes, nominal and real income changes are calculated. Using estimated incomeelasticities, the income changes will be transformed into production value changes, adding another element to the estimation. At this stage, still no factor supply restriction is imposed, that is, a flat supply curve is supposed.

So far two results have been obtained. The first indicates the maximum effect of increased exports without any restriction on the supply side of the economy. Price effects have been introduced in the second stage, indicating the negative impacts on economic activity of the estimated price increases. In the third stage these results are just summed up, to come up to the net results, still ignoring input supply restrictions.

Increased production of goods means increased use of inputs. If goods were produced with flat cost curves, there would be no effect on prices from the supply side; if production faces positive sloped cost curves, some supply reactions are to be expected. A way to consider this effect is to estimate product supply elasticities and include these factors in the


estimation of the impacts. However, data limitations made it impossible to do it this way. The alternative used was to estimate the expected increases in input prices as a consequence of increased production, and to spread these price increases to the economy with a Leontieftype price transmission mechanism. The same chain of income and price changes described in the second stage is estimated.

As a matter of fact, in the estimated model, as input prices rise, production costs go up in all sectors using these inputs, and the flat domestic supply curve moves upward. This shift in supply affects the quantity transactioned in the same way as the reactions of producers in the upward slopped supply curve, but the quantitative effects might be different. Thus, although the choice of this methodology to introduce domestic supply responses was determined by data restrictions alone, the input supply limitations introduced via the Leontieftype price transmission mechanism partially takes care of the problem. Off course, the two alternatives most probably will lead to different quantitative results, but the direction of change is the same.

Finally, the fifth stage just consolidates the upperbound effect of the first stage, the influence of price transmission, and the influence of input limitations, coming up with the net effects on the national economy. Figure 3 summarizes the mechanics of the model solution.

Figure 3. Model solution schematics

40 products

Land Labor Capital

10 household types (6 rural, 4 urban)

10 consumption structures (40 products)

Domestic purchases

International purchases

Change in International Demand

Income and price elasticities

Passthrough to domestic prices

International price changes

Leontief type price multipliers

Input supply

limitations

Cons. Price Index General Price Index

2.4.2. Input Supply Restrictions

According to the mechanism described above, input supply restrictions are incorporated in the fourth stage. Given the additional input requirements calculated in the third stage, input price changes are estimated, based on estimates of input supply limitations. The overall effect of these price changes is considered in the economy as a whole, diminishing the restrictionfree previous income estimates.

3. Policy Simulations

In this section, a trade reform scenario is simulated. Given the framework presented in Section 2, it is expected that trade liberalization will change the international prices of agricultural commodities, with effects different dimensions of the economy. For instance, impacts on rural and urban families in Brazil are expected to be different: as different types of rural and urban households are involved in the productive process in different ways, it is expected that the international price changes will affect them differently. Likewise, economic effects are expected to be different across sectors. The aim of this Section is to present the expected economic, social and environmental impacts.


3.1. Working Scenario

As presented in Section 2, the international and domestic changes in product prices are exogenous to this study. They were calculated independently by ODI. In summary, to delineate the working scenario, presented in Table 3, the following assumptions were made:

Ø The price scenario was made using the changes in world prices for Brazil given in the ODI scenario; Ø For the transmission of the world prices to domestic prices, the relation given by the GTAP model used in the

OECD project was adopted (Fipe, 2004), i.e.: a) 0.764 for soybean and corn; b) 0.809 for rice; c) 0.814 for cotton; and d) 1.000 for the other products;

Ø This high level of price transmission is also found in the study conducted by Brooks, J. and O. Melyukhina (2004). “Estimating the PassThrough of Agricultural Policy Reforms: an Application to Brazilian Commodity Markets”, paper presented at the OECD World Outlook Group Meeting, São Paulo, Brazil, 2425 May 2004;

Ø For the export changes due to the changes in prices, when available, the price elasticities of exports, given in the study made by Barros, G.S.C., M.R.P. Bacchi, and H.L. Burnquist (2002). “Estimação de Equações de Oferta de Exportação de Produtos Agropecuários para o Brasil (1992/2000)”, IPEA Discussion Paper 865, were used, i.e.: a) 2.881 for soybean that was also applied to corn and rice; b) 0.784 for cotton; c) 0.101 for coffee; d) 2.458 for sugar; e) 1.187 for vegetal oil; f) 0.187 for poultry; g) 1.411 for beef; and h) 3.338 for animal feed;

Ø When not available in the study by Barros, Bacchi and Burnquist (2002), the following price elasticities of exports were taken from the GTAP model used in the OECD project (Fipe 2004), i.e.: a) 0.00 for wheat, as Brazil is a net importer of this product; b) 1.426 for other vegetables and other food products; and c) 0.323 for other meat products.

Table 3. Working Scenario (in percentage changes)

Product Export prices Domestic prices Exports

Soybean 8.00 6.11 23.05 Corn 8.00 6.11 23.05 Cotton 10.00 8.14 7.84 Coffee products 10.00 10.00 1.01 Sugar 14.00 14.00 34.41 Rice products 10.00 8.09 28.81 Wheat flour 10.00 10.00 0.00 Vegetable oil mills 8.00 8.00 9.50 Other vegetables 8.00 8.00 11.41 Poultry products 10.00 10.00 1.87 Beef products 10.00 10.00 14.11 Other meat products 10.00 10.00 3.23 Animal feed 10.00 10.00 33.38 Other food products 10.00 10.00 14.26

3.2. Results

Aggregate results are presented in Table 3. As a consequence of the trade reform scenario for the agriculture sector, real aggregate GDP is expected to grow by 0.86%, real household income by 0.85%, and employment level by 0.91%. These are quite low values, reflecting the fact that Brazilian economy is highly diversified, with agricultural activities and food processing industries taking a small share of total activity. Besides that, exports are a small share of total production. For raw agricultural products, it represented only 3% of total production in 1999. Within this group, soybeans presented the largest export share, 31.1%, in spite of the importance of the Brazilian production in the international market. For processed food products as a group, the export share was 13.6%, with the largest shares belonging to sugar (35.6%), and coffee products (32.1%). The importance of the domestic market explains the low impacts of the simulated export increases, and also the fact that all types of families endup receiving the benefits of increased exports, as will be shown later on in this Section.


Table 4. Aggregate Results (in percentage changes) Real GDP 0.86 Real Households Income 0.85 CPI 1.45 GDP Deflator 1.05 Employment 0.91

Table 5 provides information on changes in production values at the product level. Overall, agricultural and agriculturalrelated activities (agribusiness) present a better performance.


Table 5. Effects on Sectoral Activity (in percentage change) Activity Production

Sugar cane 7.05 Soybean 10.35 Corn 3.71 Fruits 1.74 Other crops 2.07 Poultry and egg production 1.90 Cattle ranching and farming 2.02 Hog and pig farming 5.02 Other animal production 1.28 Coffee industries 2.63 Alcohol 0.86 Sugar 16.05 Vegetal oil processing 4.42 Vegetal products processing 3.59 Poultry industries 1.98 Beef industries 5.77 Other meat industries 3.68 Dairy industries 0.99 Animal feed 4.70 Other food products 7.28 Beverage 1.25 Textiles 0.54 Agricultural machinery industries 1.11 Fertilizers 4.55 Other chemical elements 1.25 Resource oriented industries 0.50 Other industries 0.49 Trade 0.78 Transport 0.76 Services and government 0.56 Total 1.06

The impacts can also be assessed considering their different effects across household types. The aggregate results presented before are detailed as they accrue to different households, and some synthetic indicators are used to consider the impacts on poverty and inequality.

Table 6 shows the expected changes in income received by households. It shows that agricultural employees and commercial farmers are the ones expected to have the largest positive impacts (+2.57% and +2.42%). In general, rural households will benefit more than urban households. The two poorest rural household types will receive the lowest positive impacts among rural households (+1.28%), but this is larger than the best case of urban households (+0.76%). The best case within agricultural farmers is a positive impact of +1.57% (type 4), still 0.85 percentage point below commercial farmers (business agric.).


Table 6. Impacts on Household Income Across Family Types Family Type Real Income CPI

Agric Fam 1 1.28 4.47 Agric Fam 2 1.28 4.14 Agric Fam 3 1.44 3.65 Agric Fam 4 1.57 1.77 Business Agric 2.42 1.80 Agric Employees 2.57 3.18 Urban Households 1 0.72 3.00 Urban Households 2 0.76 2.39 Urban Households 3 0.76 1.75 Urban Households 4 0.72 0.90 Total 0.85 1.45

The impacts of the changes simulated in the model are considered with the use of synthetic indicators of poverty and inequality. Income inequality is portrayed through Gini and Theil coefficients, which are calculated for the whole income distribution, and separately for urban, rural, and family agricultural households. As for poverty indicators, changes in the percentage of indigents and in the number of poor people are considered. For this, households from PNAD 2003 were allocated to the same ten categories employed in this study and the additional income coming from the simulations were summed to their previous incomes. 14 Since impacts are differentiated across household types, the aggregate income distribution changes, leading to new Gini and Theil coefficients.

Results are presented in Table 7, in which the first column presents the base case (benchmark), referring to the situation present in the SAM. The second column shows the impacts on income distribution of the run of the model. It can be seen that the price changes simulated in the standard run of this model leads to a marginal reduction in the general Gini index, from 0.58735 to 0.58695. Inequality within urban households is practically unchanged, and inequality within rural households, and even within family agriculture households, increases marginally.

The bottom part of Table 6 presents headcounts of population in extreme poverty, that is, people that do not receive income to buy food compatible with a minimum diet of calories and proteins. 15 Statespecific conservative poverty lines were used, meaning that the number of poor is smaller than if other poverty lines available were used. 16 Therefore, the impacts on the number of poor presented here are to be taken as maximum values. Again, results are very modest, for a number 160,000 people would be taken away from extreme poverty, representing changes close to 1.42% of the total number of people in that situation. There is an important regional aspect here, for in the Northeast region changes will be larger (2.31%), with 77.1% of people moving away from extreme poverty coming from this region.

These minor impacts on income inequality and poverty are expected, given the small aggregate effects on GDP, household income and employment, and the large share of the urban economy in Brazil. Since most changes only affect rural households, and these are only a small part of Brazilian population, these changes endup presenting only small impacts on aggregate income distribution.

Table 7. Impacts on Poverty and Income Distributional Benchmark Scenario Change

Gini Index Overall 0.58735 0.58695 0.00040 Urban 0.56912 0.56907 0.00005 Rural 0.54465 0.54529 0.00064 Family agriculture 0.50357 0.50407 0.00050

14 The necessary correction for price changes between 1999 and 2003 was applied. 15 Taken from Rocha, S. and Albuquerque, R. C. “Geografia da pobreza extrema e vulnerabilidade à fome”, Seminário Especial Fome e Pobreza – Fórum Nacional, Rio de Janeiro, Set 2003 (www.forumnacional.org.br/publi/ep/EP0054.pdf ) 16 For a discussion, see Takagy, M., Grazziano da Silva, J. and Del Grossi, M. “Pobreza e fome: em busca de uma metodologia para quantificação do problema no Brasil, Campinas IE/UNICAMP, Texto para Discussão N. 101, Jul 2001, and Silveira, F. G. et. all. “Insuficiência alimentar nas grandes regiões urbanas brasileiras: estimativas a partir da POF 1995/96IBGE” Economia Aplicada, Vol. 8, N. 3, Jul 2003

http://www.forumnacional.org.br/publi/ep/EP0054.pdf


T Theil Index Overall 0.70498 0.70411 0.00087 Urban 0.65291 0.65277 0.00014 Rural 0.66532 0.66749 0.00217 Family agriculture 0.48364 0.48463 0.00099

Extreme Poverty Number 11,187,966 11,028,779 159,187 % 6.7% 6.6% 0.10% Percentage change in extreme poverty 1.42%

Rural Northeast Number 2,654,763 2,601,942 52,821 % 19.1% 18.8% 0.38% Urban Northeast Number 2,670,702 2,600,758 69,944 % 10.8% 10.5% 0.28%

Overall Northeast 5,325,465 5,202,700 122,765 Percentage change in extreme poverty 2.31%

Northeast share 47.6% 47.2% 77.1%

Table 8 presents the impacts on some environmental indicators. Noteworthy is the increase in water consumption and organics pollutants, closely related to the performance of the agriculture sector.

Table 8. Environmental Impacts (in percentage changes)

Water Consumption 2.61 Electrical energy 0.94

Emission of CO2 1.41 Inorganics pollutants 0.56 Organics pollutants 2.73 Particulates pollutants 0.55 Sulfurates pollutants 0.96

Finally, a rough estimate of soil erosion was considered. Soil erosion in the Brazilian agriculture is estimated to be somewhere between 480,327 and 583,502 thousand tons of land per year. Considering no increase in productivity and no increase in zerotill agriculture (that reduces up to 90% of the soil erosion), one has that, in the worst case, soil erosion could reach up to an additional 30,100 tons of land per year due to the estimated increase in production and land use.

Final report for the agriculture sector study

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