FAO Fisheries and

Aquaculture Circular

FIPM/C1100 (En)

ISSN 2070-6065

THE WORLD TRADE ORGANIZATION ENLARGEMENT, TARIFFS AND GLOBAL SEAFOOD TRADE

FAO Fisheries and Aquaculture Circular No. 1100 FIPM/C1100 (En)

THE WORLD TRADE ORGANIZATION ENLARGEMENT, TARIFFS AND GLOBAL SEAFOOD TRADE Arne Melchior Senior Research Fellow Norwegian Institute of International Trade Oslo, Norway

FOOD AND AGRICULTURE ORGANIZATION OF THE UNITED NATIONS Rome, 2015

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PREPARATION OF THIS DOCUMENT

The study contributes to FAO’s ongoing activities to analyse international seafood trade and trade regulation, focusing particularly on developments in the World Trade Organization (WTO) since its establishment in 1995. While the latest negotiation round of the WTO, the Doha Round, has been protracted and difficult, the WTO has had a major success by adding 31 new members. This publication studies how this has affected seafood tariffs for the new members, and it concludes that WTO accession has clearly contributed to more liberal trade. The impact of WTO membership on trade in seafood is analysed, distinguishing between the number of suppliers (the “extensive” margin of trade) and the change in import value. The results, some of which were presented at the FAO and Eurofish regional seminar “The WTO and fisheries”, 29–31 October 201, St. Petersburg, the Russian Federation, indicate that WTO membership has promoted trade, particularly at the extensive margin, by increasing the number of suppliers for seafood in each market. This trade-promoting effect has been uneven across product groups, and driven particularly by trade in processed seafood and crustaceans.

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Melchior, A. 2015. The World Trade Organization: enlargement, tariffs and global seafood trade. FAO Fisheries and Aquaculture Circular No. 1100. Rome, FAO. 24 pp.

ABSTRACT

The document shows that there has been a major success in the World Trade Organization (WTO) with the addition of 31 new members. This has contributed to lower tariffs for seafood trade. Among the founding members of the WTO, many have considerable “water in the tariffs” and the legal option of raising their most-favoured nation (MFN) applied tariffs. The analysis shows that most countries have not used this option; there has been no protectionist backlash for fisheries tariffs but, on average, a trend towards more liberal trade. The econometric analysis investigated whether WTO membership affected trade, for whatever tariff or non-tariff reason. The results are in line with recent contributions showing that WTO membership leads to increased trade. According to the results, WTO membership stimulates trade particularly at the “extensive margin”, by promoting new entry into seafood markets. This result is driven particularly by trade in crustaceans and processed seafood.

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CONTENTS

Preparation of this document iii

List of tables vi

List of figures vi

Abbreviations and acronyms vii

Acknowledgements viii

1. INTRODUCTION: WTO – A SECRET SUCCESS IN THE SHADOWS OF TRICKY NEGOTIATIONS 1

2. SEAFOOD TARIFFS AND WTO DISCIPLINES: AN OVERVIEW 4

3. WTO ENLARGEMENT AND SEAFOOD TARIFFS 7

4. DID WTO MEMBERSHIP INCREASE TRADE? 9

5. FIXED EFFECTS: A MEASURE OF NON-TARIFF BARRIERS? 13

6. CONCLUDING COMMENTS 14

REFERENCES 15

APPENDIX 16

Tariffs for seafood for new WTO members, 1995–2013 16

Classification of seafood products 18

Fixed effects panel regressions: robustness checks, estimates for the WTO variable 18

Regressions for more detailed sub-groups of seafood 19

The 25 countries with the largest negative deviations for fixed effects 22

The 25 countries with the largest positive deviations for fixed effects 23

Seafood trade for new WTO members (USD millions) 24

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LIST OF TABLES

1. Tariff binding rates and average tariffs for seafood 4 2. Fixed effect panel regressions on the impact of WTO membership on seafood trade 11 3. Regressions for more-detailed subgroups of seafood – estimates for the impact

of WTO membership 12

LIST OF FIGURES

1. WTO members’ share of world GDP (current USD) and population, 1995–2013 2 2. Bound vs MFN applied seafood tariffs for 103 (129) WTO members, 2007–09 5 3. Changes in applied seafood tariffs for 88 WTO members, 2001–09 6 4. New bound tariff averages for seafood and the average of MFN applied

tariffs before accession 7 5. WTO binding vs real change in tariffs for seafood 8 6. Number of countries supplying seafood to each market

(median values for 111 countries), 1996–2012 10

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ABBREVIATIONS AND ACRONYMS

CTS Consolidated Tariff Schedules DDA Doha Development Agenda GATT General Agreement on Tariffs and Trade GDP gross domestic product MFN most-favoured nation NAMA Non-Agricultural Market Access (negotiations) NTB non-tariff barrier RTA regional trade agreement SPS sanitary and phytosanitary TRAINS Trade Analysis and Information System UNCTAD United Nations Conference on Trade and Development UR Uruguay Round WITS World Integrated Trade Solution WTO World Trade Organization

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ACKNOWLEDGEMENTS

Thanks are extended to Audun Lem and Victoria Chomo, FAO Fisheries and Aquaculture Department and to Hege Medin, Senior Research Fellow, Norwegian Institute of International Affairs, for their useful comments on an earlier version of this circular. Appreciation is also extended to Gloria Loriente, FAO Fisheries and Aquaculture Department, for the layout design of this publication.

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1. INTRODUCTION: WTO – A SECRET SUCCESS IN THE SHADOWS OF TRICKY NEGOTIATIONS

“We have saved the WTO” was the relieved expression of Karel de Gucht, Trade Commissioner of the European Union (Member Organization) after the Bali meeting of the World Trade Organization (WTO) in December 2013,1 and he continued that it “marks the return of the WTO from the darkness of multilateral irrelevance into the light of multilateral action and success.” However, the Bali package left out most of the major results negotiated over 12 years for the fisheries sector, including substantial tariff reductions under the Non-Agricultural Market Access (NAMA) negotiations (Melchior and Johnsen, 2011). In 2008, the WTO almost achieved agreement on these issues, but the moment was lost and the WTO was set for five years of dwindling ambition and frustration.2 Some important elements were included in the Bali package, in particular, the new agreement on trade facilitation, reducing the scope for non-tariff barriers at the border. This is certainly of importance for fisheries trade. On NAMA, however, it is uncertain what will happen in the future; few observers expect that the 2008 drafts can be recovered or reintroduced at this stage.3 While it is symbolically important that the Bali meeting succeeded, the post-Bali WTO is a less dynamic organization – few participants would aim for grand design reforms in the near future.

Notwithstanding this element of fatigue, this paper shows that there has actually been considerable progress and success in the WTO. Parallel to the protracted negotiations of the Doha Development Agenda (DDA), the number of WTO members has climbed steadily, and WTO disciplines now cover almost the whole world. The WTO was established in 1995 with 128 “founding members”.4 Since then, 31 new members have been added (country and year of entry in brackets):

Fifteen countries from East and Southeast Europe (Bulgaria, 1996; Kyrgyzstan, 1998; Latvia, 1998; Estonia, 1999; Georgia, 2000; Albania, 2000; Croatia, 2000; Lithuania, 2001; Republic of Moldova, 2001; Armenia, 2003; The former Yugoslav Republic of Macedonia, 2003; Ukraine, 2008; Montenegro, 2012; the Russian Federation, 2012; Tajikistan, 2013).

Seven countries from East and South Asia (Mongolia, 1997; China, 2001, Taiwan Province of China, 2002; Nepal, 2004; Cambodia, 2004; Viet Nam, 2007; the Lao People’s Democratic Republic, 2013).

Three countries from the Near East (Jordan, 2000; Oman, 2000; Saudi Arabia, 2005). Two countries from Latin America and four other countries (Ecuador, 1996; Panama, 1997;

Tonga, 2007; Cabo Verde, 2008; Samoa, 2012; Vanuatu, 2012).

As a result of this expansion, the WTO now covers almost the whole world. Figure 1 shows the cumulative share of world gross domestic product (GDP) and world population for the members of the WTO for 1995–2013.5 When the WTO was established in 1995, it covered 67 percent of the world population and 81 percent of world nominal GDP. In 2013, the share had risen to 93 percent of world population, and 97 percent of GDP. The most significant steps were the inclusion of China (2001) and the Russian Federation (2012).

1 http://trade.ec.europa.eu/doclib/docs/2013/december/tradoc_151951.pdf 2 The Doha Development Round of the WTO was launched in Doha, Qatar, 2001, and ambitions were reduced after the contentious WTO Ministerial Meeting in Cancun, Mexico, 2003, where there were sharp disagreements over the new issues suggested in Singapore in 1996. 3 The Doha Development Round also addressed some other aspects of fisheries, including subsidies (Meliado, 2012). 4 Sixteen founding members actually entered into the WTO in 1996. 5 For this illustration, GDP and population in 2011 are used as a basis for measuring the shares.

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Figure 1. WTO members’ share of world GDP (current USD) and population, 1995–2013

Source: World Development Indicators.

Many countries still remain outside the WTO. With Yemen about to become member number 160, there are 23 others involved in accession procedures. They includes important countries in East Europe (e.g. Kazakhstan, Belarus, Uzbekistan, Azerbaijan), and a number of countries in the Near East and North Africa (e.g. Algeria, Iran (Islamic Republic of), Iraq, the Syrian Arab Republic, Libya, Eritrea, Somalia, South Sudan, the Sudan).

Does WTO membership lead to trade liberalization and the expansion of trade? While this has been the general belief among trade economists and practitioners for decades, a paper by Rose (2004) cast some doubt on this. He ran a standard “gravity regression” where the trade flows between two countries are expected to be a function of their economic sizes and the distance between them, plus other aspects that could influence trade, such as common language, common border, and past colonial ties. To this equation, he added variables (dummies) measuring whether one or both of the countries in each trading pair were members of the WTO / General Agreement on Tariffs and Trade (GATT). Using data for 1948–1999, Rose found that WTO members did not trade more than others – according to this, there is no significant trade increase if one becomes a WTO member.

The paper by Rose ignited a new debate on WTO’s role. Subramanian and Wei (2007) criticized the econometric method used by of Rose.6 Distinguishing between the impact of WTO membership on imports vs total trade (imports plus exports), these authors used similar data to Rose and found that WTO membership led to a significant increase in imports, especially for developed countries. Balding (2010) also found that WTO membership affects imports and exports differently, and suggested this might be the underlying reason why Rose (2004) found no effect. His results indicated that WTO membership had a positive impact on trade (exports as well as imports), particularly for high-income countries. Dutt, Mihov and Van Zandt (2011) follow the more recent trade literature (see e.g. Melitz, 2003) by distinguishing between whether the WTO affects the intensive margin (changed trade volume for existing trade flows) or the extensive margin (trade increase due to new entry into markets). Measuring the extensive margin by trade in new products at a detailed level of classification, they find that WTO membership has a positive trade effect only at the extensive margin (+31 percent in their preferred specification), but a negligible or even negative effect at the intensive margin.

6 In particular, the authors show that results are changed when exporter and importer fixed effects are included, correcting for unobserved country characteristics that influence trade.

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In the light of these findings, this paper examines the impact of the WTO on world seafood trade, with a particular focus on tariffs and the impact of WTO enlargement. While the impact of WTO accession may capture tariff as well as non-tariff effects, this document does not present specific data and analysis of non-tariff barriers. Given that rich countries are globally the largest importers of seafood, the development of new and stricter regimes for food safety control of imports in some countries is a potentially important issue that is not addressed explicitly here. According to WTO (2012), most trade concerns raised by WTO members about non-tariff barriers are for trade in the food sector. While the econometric analysis of WTO accession effects may also capture the impact of non-tariff barriers in seafood trade, a more extensive study would be warranted, but this is outside the scope of the present study. For a useful analysis of selected sanitary and phytosanitary (SPS) issues in world seafood trade, readers may refer to Ababouch, Gandini and Ryder (2005).

The organization of the paper is as follows. Section 2 reviews the worldwide pattern of tariffs for seafood trade and how it is regulated by the WTO. Section 3 examines seafood tariffs for new WTO members and whether they have been affected by accession. Section 4 examines whether WTO accession has had a statistically measurable impact on seafood trade, distinguishing between the extensive and intensive margin of trade. Section 5 presents evidence on countries having particularly large or small imports of seafood. Section 6 concludes by discussing some limitations and possible extensions of the study.

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2. SEAFOOD TARIFFS AND WTO DISCIPLINES: AN OVERVIEW

Melchior (2006) presents an analysis of tariffs in world seafood trade, covering 169 countries with tariff observations later than 2000.7 Given that there have not been major global tariff reforms since 2006, many of these results for tariffs are still valid. The analysis covers bound as well as “most-favoured nation (MFN) applied” tariff rates. Bound rates are those written in the protocols of the WTO; i.e. upper bounds for the tariffs used by a member country for each tariff line/product. The “MFN applied” tariffs are the ordinary tariffs applied by a country for imports from all countries, unless they have special conditions owing to regional trade agreements or other trade preferences. As bound tariffs are upper bounds only, MFN applied tariffs – the tariffs applied in practice – may be lower. If the MFN applied tariffs are below the bound rates, there is said to be “water in the tariffs” or a “tariff overhang” or “binding overhang”. 8 An implication is that if bound tariffs are reduced because of WTO negotiations, it will not necessarily affect the MFN applied rates if there is water in the tariffs. For example, if the MFN applied rate is 10 percent and the bound rate 20 percent, the latter may be cut by half before it has to affect the applied rate. Owing to the Uruguay Round (UR) of trade negotiations, which led to the establishment of the WTO, the extent of tariff binding increased dramatically.

However, many tariffs remained unbound also after the UR. Melchior (2006) showed that out of 119 WTO members, about half (59 members) had bound all the tariff lines for seafood at the WTO. Forty-five members had bound less than 20 percent of the tariff lines for seafood. It was particularly the low-income WTO members that did not bind seafood tariffs. While the binding average for all 119 members in the data was 61 percent, low-income countries had only bound 43 percent on average (Table 1).

In the UR, the price to pay for more tariff binding was that many countries were allowed to bind their tariffs at rather high levels. Hence, a country could have a tariff average at 10 percent but bind tariffs at 80 percent in the more extreme cases. This was also the case for seafood. There was substantial water in the tariffs – while the median bound tariff average for seafood was 34 percent, the median MFN applied tariff average was 14 percent. Table 1 shows simple tariff averages for seafood for different country groups. There is wide variation across countries. For some countries, seafood is a “sensitive” sector with higher import tariffs; for others, trade is more liberal. On average, tariffs for seafood are slightly higher than for industrial goods (Melchior, 2006).

Table 1. Tariff binding rates and average tariffs for seafood

Source: Melchior (2006), Table 5.

Hence, there is considerable “water in the tariffs” for all country groups. As a consequence, reductions in bound tariffs would not “bite” strongly in all cases. For example, a 40 percent

7 Seafood includes the following items in the Harmonized System (HS) classification: Chapter 3, sub-headings 1603-1605, and positions 051191, 150410-20, 230120. 8 All three expressions are now standard in the trade policy vocabulary. For an introduction see www.wto.org/english/tratop_E/markacc_e/nama_negotiations_e.htm

Share of six-digit items bound for seafood

Simple average of bound tariffs

Simple average of MFN applied tariffs

High income 79 12.4 5.2

Upper middle income 60.7 42.9 18.7

Lower middle income 71 31.6 16.3

Low income 43.1 51 17.8

All countries 60.5 34.2 15.6

Countries covered by data: 119 WTO members 70 WTO members 140 countries, WTO members and non-members

(%)

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proportional cut in all bound seafood tariffs worldwide would only lead to a mandatory reduction in MFN applied tariffs of 9 percent (Melchior, 2006).

Using more-recent data for 2007–09, Figure 2 shows that bound seafood tariffs are still higher than MFN applied rates in the majority of cases. Most of the data are from the Trade Analysis and Information System (TRAINS) tariff database of the United Nations Conference on Trade and Development (UNCTAD), accessed though the World Integrated Trade Solution (WITS), supplemented with data from WTO’s Consolidated Tariff Schedules (CTS) database (also through WITS), and in some cases other WTO online data.

Figure 2. Bound vs MFN applied seafood tariffs for 103 (129) WTO members, 2007–09

  Sources: TRAINS, CTS, WTO.

If a data point is to the right of the 45 degree line, the bound average is highest. The MFN applied averages also include tariff lines that are not bound; this explains why some data points are above / to the left of the 45 degree line. In general, the data points are spread out, so there is a wide variation in the extent of water in the tariffs.

Countries are legally free to change their MFN applied tariffs provided they are below bound rates. It is therefore of some interest to examine what happened. Did existing WTO members use the “water in the tariffs” to raise tariffs for seafood? Figure 3 compares MFN applied tariffs for seafood in 2001–02 with levels in 2007–09, for 88 founding WTO members. As tariff data are not available for every year/country, ranges of 2–3 years have been to increase data coverage.

Most data points are close to the 45 degree line, showing that there was little change in many cases. Large deviations are more often to the right than to the left of the 45 degree line, showing that there was more liberalization than protectionism – a number of countries cut their MFN applied tariffs for seafood even though they did not have to. If one says that a change of more than one percentage point is an “increase” or “decrease”, then there was a decrease in 32 cases, an increase in 17 cases, and no change in 39 cases. Hence, on the whole, the trend was slightly in a liberal direction, with some exceptions.

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Figure 3. Changes in applied seafood tariffs for 88 WTO members, 2001–09

Sources: TRAINS, CTS, WTO.

 

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3. WTO ENLARGEMENT AND SEAFOOD TARIFFS

With respect to seafood trade, there are data available for 29 of the 31 new WTO members (Appendix Table A7). About half of them were net exporters, and half net importers. The largest exporters were China, Viet Nam, Ecuador, the Russian Federation and Taiwan Province of China. The largest importers were China, the Russian Federation and Taiwan Province of China. While the Russian Federation had almost balanced trade, China was a significant net exporter of seafood. Here, seafood also includes processed seafood (see footnote 7 for classification).

How did WTO accession affect tariffs for the new entrants? The newcomers had bound no tariffs before they became members. A first question is: Did they bind their tariffs? Or did they do like the old average, binding some but not all? The answer is straight and simple: all 31 new WTO members bound 100 percent of their tariff lines for seafood. This is good news: significantly raising the average binding rate to about 66 percent.9

At what level did the new entrants bind their tariffs? Did they bind them far above their MFN applied level or not? Appendix Table A1 shows the new bound rates, and MFN applied rates before and after accession. Figure 4 compares the new bound tariff averages for seafood with the average of MFN applied tariffs before accession.

Figure 4. New bound tariff averages for seafood and the average of MFN applied tariffs before accession

  Sources: Data for 23 countries from TRAINS, CTS, WTO.

There is wide variation. Some countries bound seafood tariff at levels far below earlier MFN tariffs, while other countries bound tariffs higher. The most liberalizing country was Albania, having an MFN applied average for seafood at 22 percent before accession, and then binding tariffs at zero. At

9 This is not fully comparable with the average of 61 percent shown in Section 2, owing to slightly different data coverage.

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the other end lies Vanuatu, with binding tariffs at 61 percent, far above the former applied level.10 On the liberal side are net exporters such as China, Viet Nam and Taiwan Province of China, but also net importers such as the Republic of Moldova, Georgia, The former Yugoslav Republic of Macedonia and Tajikistan. Hence, there is no clear correspondence between net export ratios and the extent of “water in the tariffs” that was introduced.

For Albania and other countries below the 45 degree line, it is certain that WTO accession led to a reduction in seafood tariffs. This was the case for a number of countries, including important countries such as China, the Russian Federation, Taiwan Province of China and Viet Nam. Some countries bound tariffs at low levels but had already cut MFN applied tariffs to a low level before entry; a case in point is Ukraine.

For countries that bound seafood tariffs at high levels, it would in principle be possible to raise tariffs after WTO accession. Using the data in Appendix Table A1, Figure 5 plots the newly acquired “water in the tariffs” (= bound average minus MFN applied average before accession) against the change in applied tariffs (= MFN applied tariffs after accession minus MFN applied tariffs before accession).

Figure 5. WTO binding vs real change in tariffs for seafood

Source: Appendix Table A1, using data from TRAINS, CTS, WTO.

Countries to the right in Figure 5 have “water in the tariffs”, so they could in principle raise their tariffs. Countries to the left, on the other hand, were forced to cut tariffs. The figure shows that none of the countries raised its applied tariffs; even Vanuatu reduced its applied tariff level in spite of very high binding. The data points follow an inverse U-shaped pattern. There were two “clusters”: in the middle are many countries with little change in their tariffs; and to the left there is a liberalizing group where WTO accession led to a significant tariff cut. On average, WTO accession was accompanied by lower applied tariffs.

10 The Baltic States are included. However, they joined the European Union (Member Organization) in 2007 and their tariffs were then changed to the levels of that organization.

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4. DID WTO MEMBERSHIP INCREASE TRADE?

From the analysis in Sections 2 and 3 above, it is evident that tariffs were reduced for existing as well as new members. Hence, there is not a very sharp one-to-one relationship between applied tariffs and membership. This is perhaps one reason why one may not necessarily find a strong trade effect of accession. Membership of the WTO may also lead to many changes other than tariffs. Often, WTO accession may be part of a broader process of reform, and it may then be difficult to distinguish the impact of WTO from the impact of reform more generally.

With respect to tariffs, this analysis has only examined MFN tariffs but not preferential tariffs within regional trade agreements (RTAs). In recent years, RTAs have become so prevalent that is little point in analysing the impact of MFN tariffs only, with no data for RTAs. However, obtaining accurate tariff data including preferences is an extensive data exercise that is beyond the scope of this study. Therefore, this analysis follows another route, more similar to the approach of Rose (2004) and later contributions, checking whether WTO membership as such affects trade. It uses dummy variables capturing WTO, and examines whether seafood trade is larger for WTO members. Following Dutt, Mihov and Van Zandt (2011), it checks whether the “intensive” vs the “extensive” margin of trade responds differently. Unlike Dutt, Mihov and Van Zandt (2011), data for aggregate seafood trade are used, i.e. not at the detailed product level. Instead of running a gravity regression with bilateral flows, two country-level variables are used: total import value for seafood (in current USD, using the definition in footnote 7); and the number of supplying countries for seafood in each market.

Data from WITS/COMTRADE for 1996–2012 are used, and panel regressions are run. There are 17 years in this period and data are required for at least 13 years for each importing country (= each cross-section in the panel regression). With this criterion, there are data for 111 countries, and 1 735 observations (i.e. with data for 15.6 years on average). Among the 111 countries are 83 “founding members” of the WTO, 20 acceding countries and 8 countries that were non-members all the time. First, simple panel regressions are run of the form:

Mit = α1 + α2Fi +α4 GDPit + β Dit + εit

Here, Mit is the dependent variable, which can be seafood import value or the number of seafood suppliers (exporting countries), while Fi is a set of fixed effects that control for time-invariant country characteristics that affect trade for each importing country i, and GDPit is assumed to be a main and time-variant country determinant of imports, capturing market size. As bilateral trade data are not used directly in the regression, and there are not have variables for common borders, language etc., it is assumed that these characteristics are time-invariant over the period covered and captured by the fixed effects. Some regions and countries consume more fish than others, but this probably does not change too much during the period studied so it will be reflected in the fixed effects. As a check, a set of time effects, Tt, is included in some specifications. This is a set of time controls, capturing common shocks at each year t such as the financial crisis, or supply shocks for seafood.

The key variable is Dit, taking the value 1 if the country is a WTO member and 0 if not. For the 83 founding members, it is 1 all the time, and for the 8 non-members it is always zero. For the 20 acceding countries, it varies over time from 0 to 1 from the year of accession and onwards.

Import value is derived directly from the data, and the number of seafood-supplying countries in each country is calculated from the data.11 Changes in the number of suppliers must clearly reflect the extensive margin of trade, while import value is affected by the extensive as well as the intensive margin. For seafood, it is to be expected that fresh seafood is different from frozen or preserved

11 In order to generate the “number of suppliers” variable, the analysis uses a data set with bilateral trade and 181 000 observations. Deriving the number of suppliers variable, one for each importing country/year, yields a data set of 2 404 observations. This is cut further to have at least 13 years in each cross-section, giving the final sample of 1 735 observations.

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seafood as fresh food often cannot be transported over long distances, and this limits the number of potential suppliers. Therefore, the data are split into fresh seafood and “other seafood”, and the regressions run separately, in addition to regressions for all seafood. Appendix Table A2 shows the classification of the two groups. Figure 6 shows the median number of suppliers for each cross-section in the data, for fresh and other seafood.

Figure 6. Number of countries supplying seafood to each market (median values for 111 countries), 1996–2012

Source: Author’s calculations using WITS/COMTRADE data.

The typical number of supplying countries varies from a handful in some markets to more than 100 at the other end. The two curves seem to converge at very high levels, but for intermediate levels the relative difference between fresh and other is larger.

In the panel regressions, the dependent variables and the GDP variable are expressed in logarithms. Table 2 shows the results for the whole sample and for the two subgroups.

Using fixed effects, R2 is very high, as would be expected, at 0.93 and above. The GDP variable is always strongly significant, as expected. Many of the fixed effects are also highly significant; as shown by the bottom line in each section of the table, 77–95 out 111 fixed effects were significantly different from zero at the 1 percent level or better (more on this below).

For the purpose of the analysis undertaken here, the most interesting variable is the WTO dummy. For seafood imports taken together, it is not significant in the “intensive margin” specification, with the value of imports as dependent variable. However, in the “extensive margin” specification, it is strongly significant – WTO membership leads to a 12 percent increase, on average, in the number of suppliers in a market.

The subdivision into fresh and other seafood reveals that the extensive margin effect of WTO membership is driven by “other seafood”. The WTO effect on the extensive margin is not significant for fresh but only for “other” seafood. This is in line with the expectation – the feasible set of suppliers is more limited for fresh seafood. For fresh seafood, there is a weakly significant (at the 10 percent level) WTO effect on the intensive margin. However, this is not strong enough to create an intensive margin effect that is significant for seafood as a whole.

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Table 2. Fixed effect panel regressions on the impact of WTO membership on seafood trade

Note: Number of observations: 1 735 (111 cross-sections).

Various checks of the result are undertaken:

dropping permanent non-members from the sample; including time effects; adding control variables reflecting income per capita and the net export ratio for seafood.

Appendix Table A3 shows the results for the WTO variable. The results are qualitatively identical, with some slight variation. The strongest and most robust result is an extensive margin effect for other seafood, which is also reflected in the seafood total. With control variables added, there is also a positive WTO impact for the seafood import value, although with lower levels of significance. The import value can be affected by the extensive as well as the intensive margin, and these results suggest that the extensive margin effect dominates.

In order to check whether the results vary across more detailed categories of seafood, regressions are also run at a more detailed level– mainly using the 4-digit level of classification, plus one group of fishmeal and fish oil combining various 4- and 6-digit subgroups (see Appendix Table A2 for the classification). Appendix Table A4 presents the regression results. Table 3 shows results for the WTO dummy. In order to distinguish better between the extensive and intensive margins, the analysis also includes regressions with average value of imports per supplier as independent variable.

The results indicate that the “extensive margin” results observed in Table 2 for the seafood total are driven by processed fish (1604), crustaceans and molluscs (306, 307 and 1605). For 307 Molluscs and 1604 Processed fish there is no “intensive margin effect”. For 306 Crustaceans and 1605 Processed crustaceans etc. there is also an intensive margin effect in the form of a significant and positive estimate when average value of imports per supplier is the independent variable. Similar results are also found for 303 Frozen whole fish. Hence, these more detailed regressions show that there is some variation across subgroups, and that the extensive margin effect does not apply to trade in whole or semi-processed fish (groups 301–305).

Est. P value Est. P value Est. P valueIntercept –1.104 <.0001 –0.361 0.0219 –0.989 <.0001WTO dummy –0.053 0.4257 0.094 0.0638 –0.059 0.3856

Log (GDP) 1.175 <.0001 0.251 <.0001 1.161 <.0001

R2 0.978 0.932 0.976

Fixed effectsFE with P<0.01

Est. P value Est. P value Est. P valueIntercept 0.83 <.0001 –6.237 <.0001 0.822 <.0001WTO dummy 0.122 0.0001 0.23 0.1525 0.099 0.002Log(GDP) 0.224 <.0001 1.226 <.0001 0.223 <.0001

R2 0.935 0.919 0.935

Fixed effectsFE with P<0.01

Yes Yes Yes95 80 80

80 81 77Dependent variable: Number of suppliers (in logs)

VariableAll seafood Fresh seafood Other seafood

Dependent variable: Import value (in logs)

VariableAll seafood Fresh seafood Other seafood

Yes Yes Yes

12

Table 3. Regressions for more-detailed subgroups of seafood – estimates for the impact of WTO membership

Therefore, the results suggest that WTO membership has a positive impact on seafood trade, but this effect is uneven across subgroups of seafood and only confirmed for 5 out of 10 subgroups. For the 5 subgroups with a positive WTO effect, there is an extensive margin effect in 4 cases, and an intensive margin effect in 3 cases. This suggests, supported by the results for the seafood total in Table 2, that the extensive margin effect is the strongest one – WTO membership increases competition and allows more competitors in a market. However, this effect is not supported for fresh seafood or for whole or semi-processed fish. The effect captured by the WTO variable can be related to all possible aspects of the WTO, not only tariffs.

Focusing on the impact of the WTO on imports, the results therefore support recent evidence from Subramanian and Wei (2007) and Balding (2010) suggesting that, after all, WTO membership has a positive impact on trade. In line with Dutt, Mihov and Van Zandt (2011), the results here support the hypothesis that the trade impact of the WTO is particularly at the extensive margin. However, the impact is uneven across subgroups.

Estimate P value Estimate P value Estimate P value301 Live fish 0.071 0.3884 0.045 0.778 0.116 0.5205302 Fresh whole fish 0.031 0.7 0.276 0.1581 0.307 0.1578303 Frozen whole fish 0.019 0.7483 0.395 0.0041 0.414 0.0073304 Fillets, fresh or frozen –0.009 0.8954 0.104 0.4462 0.095 0.544305 Fish, salted, dried, etc. 0.085 0.1724 –0.074 0.5692 0.011 0.9385306 Crustaceans 0.175 0.0136 0.551 0.0005 0.725 <.0001307 Molluscs 0.374 <.0001 0.038 0.7612 0.412 0.00261604 Processed fish 0.09 0.0359 0.092 0.2489 0.181 0.03061605 Processed crustaceans, etc. 0.223 0.0008 0.564 <.0001 0.788 <.0001

Fish oil Fish oil, fats, meal, etc. 0.04 0.4837 –0.011 0.9477 0.028 0.881

Item Short description

Dependent variable (in logs)Number of

supplying countriesAverage value of

imports per supplierValue of imports

13

5. FIXED EFFECTS: A MEASURE OF NON-TARIFF BARRIERS?

Panel regressions with fixed effects yield estimates for each country on time-invariant and systematic deviations from predicted levels of trade. In the regressions reported in Section 4, these estimates are statistically significant at the 1 percent level or better in the majority of cases, as shown in Table 2. While the absolute numbers are not so interesting, the ranking across countries is of some interest. The fixed effect parameter estimates can reflect a variety of influences, but essentially they measure whether a country imports less or more seafood than expected, given its market size. Such deviations can be due to taste patterns, trade barriers or own supply. While taste patterns and trade barriers are straightforward, own supply can be ambiguous. According to a neoclassical trade perspective, large producers should import less because they can supply themselves. According to a modern trade theory perspective, or in models with intermediate goods trade, large producers can also be large importers; importing other varieties or inputs. Further study is needed in order to distinguish between determinants of the fixed effects, and this is beyond the scope of this study. Nevertheless, some of the fixed effects are reported in the Appendix, as descriptive measures of deviating trade patterns. Appendix Tables A5 and A6 show fixed effects for the countries with the 25 largest negative and positive deviations for total seafood imports (value or the number of suppliers), respectively.

At the top of the “negative list” are many countries where trade barriers may be large. They include landlocked countries and countries where non-tariff barriers may be high (e.g. India). On the “positive list” are small city territories/States such as China, Hong Kong SAR and Singapore, and also some small island States. An issue for further study is to examine more closely the reasons underlying these fixed effects. Given the main interest here in the WTO issue, a limited number of variables were included in regressions, as the study was not per se interested in time-invariant country characteristics. One option in future work could be to examine more broadly the determinants of imports, including landlockedness, non-tariff barriers, etc.

14

6. CONCLUDING COMMENTS

This study has shown that, in spite of slow progress in recent WTO negotiations (notwithstanding the success at Bali), there has been a major success in the WTO by the addition of 31 new members. This has contributed to lower tariffs for seafood trade. Among the founding members of the WTO, many have considerable “water in the tariffs” and, therefore, the legal option of raising their MFN applied tariffs. If all this “water” had been used, the results in Melchior (2006) suggest that the simple average of worldwide MFN applied tariffs for seafood could have risen from 16 to 34 percent. The analysis showed that most countries did not use this option. On the contrary, many countries cut tariffs for seafood even where the WTO did not force them to do so. In the recent economic crisis, there has been a focus on the need to avoid a backlash into protectionism; and for tariffs, this has mainly been achieved. This study shows that there has been no protectionist trend for fisheries tariffs, but on average, with some exceptions, a trend towards more liberal trade.

Potentially, tariff reductions could be offset by rising non-tariff barriers (NTBs). For seafood trade, SPS measures could be particularly important. Driven by consumer demands and health concerns, SPS institutions have developed, particularly in wealthy countries, at the same time as tariffs have been reduced. One interpretation of such evidence is that there is “policy substitution” – when tariffs and quotas cannot be used any more, countries use NTBs. However, research evidence is mixed – see WTO (2012) for a discussion. Notifications from the WTO on non-tariff barriers and SPS aspects have risen in recent years (WTO, 2012), and notified NTB/SPS concerns suggest that NTB/SPS barriers in developed countries are a concern for developing country exporters. Therefore, further study of NTB/SPS measures in world seafood trade is important but beyond the scope of the present study.

While the trade policy analysis of the present study focuses on tariffs, the econometric analysis asks whether WTO membership has affected trade, for whatever reason. Contrary to Rose (2004), who found that WTO membership had no positive impact on trade, the results presented here are in line with more recent contributions showing that WTO membership does lead to increased trade. This study shows that WTO promotes trade, particularly at the “extensive margin”, by promoting new entry into seafood markets. However, the positive WTO effect is uneven across subgroups of seafood.

The analysis could be extended in several directions. While the present analysis has addressed the extensive/intensive margin issue using aggregate trade data, firm-level data would allow the extensive and intensive margins to be captured more precisely. Hence, analysing the impact of the WTO using firm-level trade data is one possible extension. As noted, an important extension would also be to add data allowing a more detailed examination of trade costs and NTBs.

15

REFERENCES

Ababouch, L., Gandini, G. & Ryder, J. 2005. Causes of detentions and rejections in international fish trade. FAO Fisheries Technical Paper No. 473. Rome, FAO. 110 pp. (also available at www.fao.org/docrep/008/y5924e/y5924e00.htm).

Balding, C. 2010. Joining the World Trade Organization: What is the impact? Review of International Economics, 18(1): 193–206.

Dutt, P., Mihov, I. & Van Zandt, T. 2011. Does WTO matter for the extensive and the intensive margins of trade? INSEAD Faculty and Research Working Paper 47/2011.

Melchior, A. & Johnsen, Å. 2011. Forhandlingsrunden i WTO: Tollreduksjoner for norsk sjømateksport (on the NAMA negotiations at the WTO), NUPI Report, May 2011. Written for the Norwegian Ministry of Fisheries and Coastal Affairs.

Melchior, A. 2006. Tariffs in world seafood trade. FAO Fisheries Circular No. 1016. Rome, FAO. 43 pp. (also available at ftp://ftp.fao.org/docrep/fao/008/a0431e/a0431e00.pdf).

Meliado, F. 2012. Fisheries management standards in the WTO fisheries subsidies talks: learning how to discipline environmental PPMs? Journal of World Trade, 46(2).

Melitz, M. 2003. The impact of trade and intra-industry reallocations and aggregate industry productivity. Econometrica, 71(6): 1695–1725.

Rose, A. 2004. Do we really know that the WTO increases trade? American Economic Review, 94: 98–114.

Subramanian, S. & Wei, S. 2007. The WTO promotes trade, strongly but unevenly. Journal of International Economics, 72: 151–175.

World Trade Organization (WTO). 2012. World Trade Report 2012. Trade and public policies: A closer look at non-tariff measures in the 21st century. Geneva. (also available at www.wto.org).

16

AP

PE

ND

IX

Tab

le A

1. T

arif

fs f

or s

eafo

od f

or n

ew W

TO

mem

ber

s, 1

995–

2013

Dat

a Y

ear

Dat

a Y

ear

Dat

a Y

ear

Sim

ple

Wei

ghte

dS

impl

eW

eigh

ted

Sim

ple

Wei

ghte

dEc

uado

r19

96na

1996

28.8

628

.620

0118

.89

12.0

410

0M

ongo

lia19

97na

2005

2020

2005

55

100

Pana

ma

1997

1997

15.3

68.

2819

9717

.29

16.6

420

0112

.89

7.68

100

Kyr

gyzs

tan

1998

na20

0210

.19

1020

069.

968.

9110

0Es

toni

a19

9919

960

019

9916

.86

15.8

920

033.

32.

6410

0Jo

rdan

2000

na20

0021

.83

14.4

220

0521

.514

.810

0G

eorg

ia20

0019

9912

1220

020.

450.

0720

060.

450.

0310

0A

lban

ia20

0019

9721

.42

20.7

820

010.

060

2005

0.04

010

0C

roat

ia20

00na

2001

7.33

7.83

2005

7.19

8.18

100

Om

an20

0019

974.

915

2002

19.1

519

.77

2005

3.27

3.08

100

Lith

uani

a20

0119

974.

743.

5920

0212

.93

9.56

2003

4.2

3.06

100

Rep

ublic

of M

oldo

va20

0119

966.

60.

8620

014.

291.

1620

065.

183.

5710

0C

hina

2001

1998

21.3

615

.56

2001

10.9

38.

2820

0610

.94

8.66

100

Tai

wan

Pro

vinc

e of

C

hina

2002

1999

29.4

420

.48

2002

23.2

212

.52

2007

22.0

512

.610

0

Arm

enia

2003

2001

9.43

4.43

2006

1515

2008

9.47

8.7

100

The

form

er Y

ugos

lav

Rep

ublic

of

Mac

edon

ia

2003

2001

13.4

812

.05

2004

0.26

0.05

2008

0.25

0.08

100

Nep

al20

0420

0010

.94

14.2

720

0421

.88

25.8

920

1010

.810

.64

100

Cam

bodi

a20

0420

0119

.38

8.66

2004

23.3

118

.85

2008

18.9

810

.62

100

Saud

i Ara

bia1

2005

2000

**12

1220

0510

.81

9.77

2009

3.28

3.36

100

Bul

garia

1996

1998

30.3

317

.35

2003

11.4

37.

2110

0V

iet N

am20

0720

0431

.75

25.8

920

0718

.16

12.1

520

1016

.64

9.69

100

Ton

ga20

07na

2009

19.8

19.5

220

1219

.18

18.7

810

0

Cou

ntry

Yea

r of

ac

cess

ion

MFN

app

lied

rat

es b

efor

e ac

cess

ion

Bou

nd r

ates

aft

er a

cces

sion

MFN

app

lied

rat

es a

fter

acc

essi

on%

of t

arif

f li

nes

boun

dT

arif

f ave

rage

Tar

iff a

vera

geT

arif

f ave

rage

17

Tab

le A

1 (c

onti

nu

ed)

1 S

audi

Ara

bia

had

low

er M

FN a

pplie

d ta

riff

s cl

oser

to a

cces

sion

; ave

rage

3.2

7 (w

eigh

ted)

/ 3.1

(si

mpl

e) in

200

3.

Not

es:

Tar

iff

data

are

not

ava

ilabl

e fo

r ev

ery

year

. The

aim

is to

hav

e “M

FN

app

lied

bef

ore

acce

ssio

n” th

ree

year

s be

fore

ent

ry, a

nd “

MF

N a

ppli

ed a

fter

acc

essi

on”

five

yea

rs

afte

r en

try,

as

ther

e ar

e so

met

imes

fiv

e-ye

ar p

erio

ds o

f ph

asin

g in

new

tari

ffs.

Ow

ing

to li

mit

ed d

ata

avai

labi

lity

, the

yea

rs in

clud

ed d

evia

te f

rom

this

. For

mem

bers

in 2

012

or

late

r, th

ere

is n

o “M

FN

app

lied

aft

er a

cces

sion

”.

Sou

rces

: T

RA

INS,

CT

S, W

TO

.

Dat

a Y

ear

Dat

a Y

ear

Dat

a Y

ear

Sim

ple

Wei

ghte

dS

impl

eW

eigh

ted

Sim

ple

Wei

ghte

dU

krai

ne20

0820

063.

172.

5920

083.

42.

6320

122.

431.

6610

0C

abo

Ver

de20

0820

0523

.49

21.0

620

0824

.96

29.5

720

1122

.96

26.0

410

0La

tvia

1998

1997

8.9

4.66

2001

35.5

329

.520

018.

346.

2810

0M

onte

negr

o20

1220

099.

3610

.31

2012

10.5

310

0Sa

moa

2012

2012

26.4

100

Rus

sian

Fed

erat

ion

2012

2009

10.4

210

.01

2012

6.92

100

Van

uatu

2012

2009

28.4

826

.23

2012

61.1

110

0La

o Pe

ople

’s

Dem

ocra

tic R

epub

lic20

1320

0812

.74

21.1

220

1331

.110

0

Taj

ikis

tan

2013

2010

10.3

111

.03

2013

6.07

100

Cou

ntry

Yea

r of

ac

cess

ion

MFN

app

lied

rat

es b

efor

e ac

cess

ion

Bou

nd r

ates

aft

er a

cces

sion

MFN

app

lied

rat

es a

fter

acc

essi

on%

of t

arif

f li

nes

boun

dT

arif

f ave

rage

Tar

iff a

vera

geT

arif

f ave

rage

18

Table A2. Classification of seafood products

 Note: The HS1996 classification is used in the analysis of trade.

Table A3 Fixed effects panel regressions: robustness checks, estimates for the WTO variable

Category Items in HS 1996 includedChapter 31603-1605

51191150410-20

230120301302

304103062130622306233062430629307103072130731307413075130760

“Other seafood”All seafood items not included under “Fresh seafood” above

51191150410-20

1603230120

“Seafood”

“Fresh seafood”

“Fish oil”

Est. P value Est. P value Est. P value

Import value 0.004 0.9512 0.303 0.0639 –0.006 0.9367Number of suppliers 0.084 0.0077 0.06 0.2392 0.064 0.0454Import value –0.014 0.8343 0.286 0.0796 –0.019 0.7836Number of suppliers 0.086 0.0076 0.054 0.2999 0.066 0.044Import value 0.12 0.061 0.13 0.4338 0.14 0.0273Number of suppliers 0.15 <.0001 0.04 0.4521 0.12 0.0002

Permanent non–members dropped

With control variables

Dependent variable

All seafood Fresh seafood Other seafood

Two–way fixed, with time dummies

19

Tab

le A

4. R

egre

ssio

ns

for

mor

e d

etai

led

su

b-g

rou

ps

of s

eafo

od

Est

.P

val

ueE

st.

P v

alue

Est

.P

val

ueE

st.

P v

alue

Est

.P

val

ue30

1L

ive

fish

–0.7

520.

0553

0.07

10.

3884

–0.0

790.

6569

0.35

10.

0731

0.15

30.

0243

0.92

871

284

302

Fres

h w

hole

fis

h–0

.599

0.11

160.

031

0.7

0.00

20.

9903

0.30

50.

1076

0.21

10.

0005

0.87

100

1 46

4

303

Froz

en w

hole

fis

h–2

.284

<.00

010.

019

0.74

830.

872

<.00

01–0

.570

0.00

01–0

.050

0.26

810.

8910

51

527

304

Fille

ts, f

resh

or

froz

en–0

.989

0.00

56–0

.009

0.89

540.

214

0.19

040.

164

0.35

96–0

.143

0.00

860.

9199

1 44

2

305

Fish

, sal

ted,

dr

ied,

etc

.0.

778

0.00

80.

085

0.17

24–0

.113

0.39

370.

384

0.00

840.

194

<.00

010.

8810

41

516

306

Cru

stac

eans

0.11

30.

7601

0.17

50.

0136

–0.3

790.

0264

0.71

30.

0001

0.05

10.

3646

0.89

103

1 49

530

7M

ollu

scs

–1.7

61<.

0001

0.37

4<.

0001

0.06

10.

6922

0.32

20.

0551

0.14

90.

0028

0.91

101

1 47

216

04P

roce

ssed

fis

h–0

.879

<.00

010.

090.

0359

0.59

4<.

0001

–0.3

960.

0002

–0.0

240.

4508

0.89

108

1 56

5

1605

Pro

cess

ed

crus

tace

ans,

et

c.

–1.9

26<.

0001

0.22

30.

0008

–0.0

510.

741

0.48

0.00

50.

061

0.23

010.

8810

21

489

Fish

oil

Fish

oil,

fat

s,

mea

l, et

c.–0

.436

0.13

770.

040.

4837

0.12

60.

3475

0.10

60.

4714

0.04

20.

374

0.91

981

432

Obs

.

Dep

ende

nt v

aria

ble:

Num

ber

of s

uppl

ying

cou

ntri

es in

eac

h im

port

ing

mar

ket

(in

logs

)

Item

Shor

t de

scri

ptio

nIn

terc

ept

WT

O d

umm

yL

og (

GD

P)

Log

(G

DP

/cap

ita)

Net

tra

de r

atio

R2

Cro

ss-

sect

ions

20

Tab

le A

4 (c

onti

nu

ed)

Est

.P

val

ueE

st.

P v

alue

Est

.P

val

ueE

st.

P v

alue

Est

.P

val

ue30

1L

ive

fish

–5.0

30<.

0001

0.04

50.

778

0.11

0.75

240.

783

0.04

080.

362

0.00

620.

9187

1 28

230

2Fr

esh

who

le

fish

–5.1

62<.

0001

0.27

60.

1581

–0.2

950.

4808

1.53

0.00

10.

379

0.01

040.

8810

01

464

303

Froz

en w

hole

fis

h–9

.296

<.00

010.

395

0.00

413.

986

<.00

01–3

.345

<.00

01–0

.394

0.00

020.

8810

51

527

304

Fille

ts, f

resh

or

froz

en–1

2.35

4<.

0001

0.10

40.

4462

3.28

4<.

0001

–2.0

94<.

0001

–0.1

950.

0683

0.92

991

442

305

Fish

, sal

ted,

dr

ied,

etc

.–3

.963

<.00

01–0

.074

0.56

921.

105

<.00

01–0

.236

0.43

82–0

.139

0.12

990.

9210

41

516

306

Cru

stac

eans

–7.2

11<.

0001

0.55

10.

0005

1.54

3<.

0001

–0.7

950.

0565

–0.2

640.

036

0.89

103

1 49

530

7M

ollu

scs

–5.9

94<.

0001

0.03

80.

7612

0.43

20.

1348

0.58

0.06

75–0

.166

0.07

80.

9410

11

472

1604

Pro

cess

ed f

ish

–4.1

00<.

0001

0.09

20.

2489

0.64

10.

0004

0.34

70.

0825

–0.5

97<.

0001

0.95

108

1 56

5

1605

Pro

cess

ed

crus

tace

ans,

et

c.

–6.6

26<.

0001

0.56

4<.

0001

–0.0

860.

782

1.31

80.

0001

–0.2

460.

0143

0.94

102

1 48

9

Fish

oil

Fish

oil,

fat

s,

mea

l, et

c.–0

.387

0.66

69–0

.011

0.94

771.

815

<.00

01–1

.512

0.00

08–0

.064

0.66

320.

8398

1 43

2

Cro

ss-

sect

ions

Obs

.D

epen

dent

var

iabl

e: A

vera

ge v

alue

of i

mpo

rts

from

eac

h su

pply

ing

coun

try

(in

logs

)It

emSh

ort

desc

ript

ion

Inte

rcep

tW

TO

dum

my

log

(GD

P)

log

(GD

P/c

apit

a)N

et t

rade

rat

ioR

2

21

Tab

le A

4 (c

onti

nu

ed)

N

ote:

For

cla

ssif

icat

ion

of F

ish

oil,

etc.

, see

Tab

le A

2.

Est

.P

val

ueE

st.

P v

alue

Est

.P

val

ueE

st.

P v

alue

Est

.P

val

ue30

1L

ive

fish

–5.8

00<.

0001

0.11

60.

5205

0.03

90.

9219

1.12

60.

0092

0.51

30.

0006

0.94

871

282

302

Fres

h w

hole

fis

h–5

.761

<.00

010.

307

0.15

78–0

.293

0.52

871.

836

0.00

040.

590.

0003

0.91

100

1 46

4

303

Froz

en w

hole

fis

h–1

1.57

9<.

0001

0.41

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22

Table A5. The 25 countries with the largest negative deviations for fixed effects

Notes: Fixed effect estimates from FE panel regressions reported in Table 2. Only estimates significant at the 5 percent level or better are reported.

CountryAll

seafoodFresh

seafoodOther

seafoodCountry

All seafood

Fresh seafood

Other seafood

India –3.565 –0.383 –4.058 Mauritania –0.901 –0.986 –0.934Sudan –3.200 –0.549 –3.283 Botswana –0.512 1.698 –0.487Uganda –3.034 –3.117 Bahamas –0.386 3.869 –0.429United Republic of Tanzania

–2.560 0.249 –2.873 Paraguay –0.346 –0.308

Mauritania –2.320 –0.685 –2.356 Sudan –0.327 –1.574 –0.378Turkey –1.757 0.484 –1.797 Brazil –0.305 –0.349Argentina –1.540 –1.585 India –0.302 –0.306Mexico –1.538 –1.530 Uganda –0.224 –1.714 –0.247Algeria –1.454 –1.605 Argentina –0.205 –0.263Paraguay –1.375 –0.845 –1.384 Cambodia –0.194 –0.189Azerbaijan –1.363 –1.392 Chile 0.16 –1.209 0.182Brazil –1.350 –0.331 –1.400 Kenya 0.185Indonesia –1.209 –1.163 Mexico 0.191 0.197Senegal –1.172 0.335 –1.292 Indonesia 0.202 –0.797 0.196Venezuela (Bolivarian Republic of)

–0.999 –0.352 –0.964 Cabo Verde 0.22 2.633 0.221

Nigeria –0.986 0.572 –1.313 Azerbaijan 0.228 0.18United States of America –0.965 0.901 –1.061 Benin 0.251 1.3 0.276Peru –0.895 –1.130 Turkey 0.271Saudi Arabia –0.859 0.436 –1.264 Oman 0.274 2.309 0.213Kazakhstan –0.817 0.366 –0.796 Nicaragua 0.275 1.895 0.215Kenya –0.802 –0.835 Panama 0.276 0.932 0.235South Africa –0.801 0.942 –0.773 Madagascar 0.281 0.284Malawi –0.710 –0.225 –0.721 Senegal 0.303 0.774 0.169Cambodia –0.523 –0.560 Algeria 0.309 0.247Germany –0.509 1.25 –0.655 Philippines 0.327 0.324

Regressions with import value Regressions with the number of suppliers

23

Table A6. The 25 countries with the largest positive deviations for fixed effects

Notes: Fixed effect estimates from FE panel regressions reported in Table 2. Only estimates significant at the 5 percent level or better are reported.

CountryAll

seafoodFresh

seafoodOther

seafoodCountry

All seafood

Fresh seafood

Other seafood

Mauritius 3.297 1.369 3.283 Mauritius 1.218 4.023 1.226Saint Kitts and Nevis 2.414 0.485 2.34 Lebanon 1.201 4.558 1.109Dominica 2.296 0.44 2.264 Republic of Moldova 1.114 1.57 1.106Malta 2.295 1.42 1.921 Malta 1.08 5.293 1.011Iceland 2.249 0.721 2.231 Slovenia 1.07 3.124 0.968

Togo2.227 2.163 China, Hong Kong

SAR1.046 5.102 1.043

Republic of Moldova 2.225 0.63 2.22 Cyprus 1.043 3.425 0.999China, Hong Kong SAR

2.157 1.374 1.897 The former Yugoslav Republic of Macedonia

0.992 3.332 0.959

Aruba 2.155 1.315 1.754 Thailand 0.983 2.655 0.964Jamaica 2.125 2.139 Croatia 0.982 3.016 0.893Estonia 2.109 1.073 1.863 Barbados 0.962 3.649 0.959Barbados 2.101 0.953 2.047 Estonia 0.947 5.031 0.928

Maldives2.068 1.199 1.898 Saint Vincent and the

Grenadines0.935 2.115 0.948

Lithuania 1.974 0.929 1.771 Singapore 0.922 4.388 0.885Saint Vincent and the Grenadines

1.928 0.651 1.894 China, Macao SAR 0.875 4.887 0.807

Belarus 1.904 1.886 Canada 0.854 2.664 0.77Cameroon 1.768 1.798 Jordan 0.842 3.49 0.722Portugal 1.756 1.166 1.647 Czech Republic 0.837 1.855 0.722Thailand 1.752 1.127 1.776 Iceland 0.829 3.184 0.842Denmark 1.699 1.253 1.425 France 0.814 3.129 0.701Benin 1.623 -0.273 1.599 Greece 0.79 3.24 0.687Namibia 1.58 0.355 1.517 Austria 0.789 2.288 0.724Latvia 1.558 0.888 1.309 Portugal 0.784 4.136 0.73Singapore 1.456 1.383 1.202 Bulgaria 0.774 2.026 0.727Cyprus 1.385 1.335 1.285 Spain 0.753 3.875 0.725

Regressions with import value Regressions with the number of suppliers

24

Table A7. Seafood trade for new WTO members (USD millions)

Notes: Figures in million current USD, most recent year available. Net trade ratio (Balassa index): (x-m)/(x+m) varies between –1 (only imports) and +1 (only exports). Sources: WITS/COMTRADE. Data for Montenegro and Lao People’s Democratic Republic not available.

Country Year Exports Imports Net trade ratioEcuador 2012 2881.6 208.4 0.87Cabo Verde 2012 44.3 3.8 0.84Viet Nam 2012 6284 829.3 0.77Tonga 2012 4.7 1.5 0.51Oman 2012 158.2 54.9 0.48Panama 2011 132.9 47 0.48Armenia 2012 22.5 9 0.43China 2012 18265.2 7435.6 0.42Taiwan Province of China 2012 1992.8 1044.2 0.31Estonia 2012 252 171.4 0.19Vanuatu 2011 6.4 4.7 0.15Croatia 2012 156 115.5 0.15Albania 2012 36.6 28.4 0.13Latvia 2012 244.4 190.5 0.12Samoa 2012 7.7 6.8 0.06Lithuania 2012 395.7 365.4 0.04Russian Federation 2012 2653.3 2738.4 -0.02Bulgaria 2012 35.3 73.3 -0.35The former Yugoslav Republic of Macedonia 2012 7.9 24.1 -0.51Cambodia 2012 1.7 6.6 -0.59Mongolia 2007 0.1 0.8 -0.74Saudi Arabia 2012 54.2 636.8 -0.84Ukraine 2012 66.3 801 -0.85Georgia 2012 2.8 45.4 -0.89Republic of Moldova 2012 0.1 53.2 -1.00Nepal 2011 0 6.1 -1.00Jordan 2012 0 116 -1.00Kyrgyzstan 2012 0 15 -1.00Tajikistan 2000 0 0.2 -1.00

 

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