Ten striking facts about agricultural input use in Sub-Saharan Africa Megan Sheahan and Christopher...

Ten striking facts about agricultural input use in Sub-

Saharan AfricaMegan Sheahan and Christopher B. Barrett

Presentation for the workshop on Structural Transformation in African Agriculture and Rural Spaces (STAARS)

African Development Bank Headquarters, Tunis, Tunisia, November 11-12, 2014

A summary of work prepared under the “Myths and Facts” project

Improved agricultural productivity is a primary pathway by which societies can begin down the path of economic transformation and growth

and out of subsistence level poverty.

Introduction

Expanded use of modern agricultural inputs, embodying improved technologies, is often seen as a prerequisite to increasing agricultural productivity.

Asia and Latin America enjoyed tremendous increases in agricultural productivity through rapid and widespread uptake of yield-enhancing modern agricultural inputs.

Benefits accrued to both producers and consumers, helping stimulate historically unprecedented economic growth and poverty reduction in east and southeast Asia.

What about Sub-Saharan Africa?

Introduction

Prevailing wisdom = “African farmers use few modern inputs”

Well-perpetuated claim grounded in:• Macro-statistics (e.g., FAOStat and World Bank’s

Development Indicators)• Studies derived from micro-data with small or purposively

chosen samples• Case studies with limited statistical underpinnings • Data collected 10-20 years ago

Major changes in SSA in last 10-20 years:• High and volatile food prices• Urbanization and growth of a middle class • Increased investments in agricultural sector (including

fertilizer subsidy programs)• New technologies available to farmers (cell phones)• Changing bio-physical environment (climate change, soil

erosion)

It’s time to update our understanding of the agricultural input landscape in Sub-Saharan

Africa.

Introduction

1. Large cross section of SSA’s population

2. Cross-country comparable3. Strong focus on agricultural

data collection4. Plot, household, and

community level information 5. Nationally-representative

statistics as well as within-country (and even within-household) analysis

6. Statistics derived from farmers’ accounts

7. Coupled with growing collection of geo-referenced data setsLiving Standards Measurement Study Integrated Surveys on

AgricultureBurkina Faso Ethiopia Malawi Mali Niger Nigeria Tanzania

Uganda

We use one cross section of LSMS-ISA data collected between 2010 and 2012 in each of six countries (Niger, Nigeria, Ethiopia, Malawi, Tanzania, Uganda), including over 22,000 cultivating households and 62,000 agricultural plots

• Objective: update the basic facts on agricultural input use in SSA through descriptive statistics

• Not our objective: uncover casual pathways for these conditions

Focus on fertilizer, improved seed varieties, agro-chemicals (pesticides, herbicides, fungicides), irrigation, and mechanization

Huge number of descriptive statistics included in Sheahan and Barrett (2014) World Bank Policy Research Working Paper No. 7014

10 most important facts presented here…

Introduction

Sample: any sampled household cultivating at least one agricultural plot in the main growing season (mostly rural but not exclusively)

Sample selection and

variable creation

Country Year Season # hh # plots

Ethiopia 2011/12 - 2,852 23,051

Malawi 2010/11 Rainy 10,086 18,598

Niger 2011/12 Rainy 2,208 6,109

Nigeria 2010/11 - 2,939 5,546

Tanzania 2010/11 Long rainy 2,372 4,794

Uganda 2010/11 First 1,934 3,349

Variable creation: • Variables created and data “cleaned” using the same rules

across all data sets and countries• Use of imputed plot size values to limit known reporting bias• Household sampling weights as well as calculated plot level

weights

Modern input use may be relatively low in aggregate, but is not uniformly low across these six countries, especially

for inorganic fertilizer and agro-chemicals.

1 of 10 “striking” facts

Ethiopia Malawi Niger Nigeria Tanzania Uganda 0

102030405060708090

31

38

33

13 11

56

77

17

41

17

3

Share of cultivating households (%) using input on fields

any agro-chemical inorganic fertilizer

• Relatively high shares of households use inorganic fertilizer, with 3 of 6 countries > 40 percent

• Where > 30 percent of households use agro-chemicals on plots (others used in storage), any implications for human health?

• Average inorganic fertilizer use rates > widely quoted 13 kg/ha statistic in 3 of 6 countries, simple six country average nutrient application rate of 26 kg/ha

• Application rates are highest in Malawi and Nigeria, both with government input subsidy programs, and Ethiopia

EthiopiaMalawi

Niger

Nigeria

Tanzania

Uganda

LSMS-ISA avgSSA avg

OECD

0

20

40

60

80

100

120

25

56

2

64

81

2623

33

16 7

2

12 13

121Inorganic fertilizer application

(nutrients in kg/ha)

Micro data (LSMS-ISA, 2009-2011)Macro data (World Bank, 2010)

The incidence of irrigation and mechanization, however, remains quite small.


• 5 percent of households use some form of irrigation, covering only about 2 percent of land under cultivation

Mechanization is proceeding slowly

• Ownership or rental:– Traction animal ownership >20

percent in all countries except Malawi

– 1-2 percent of households own a tractor, not many more rent

– 32 percent of households own and 12 percent of households rent some type of farm equipment that could be used for mechanization

• Use: – ~50 percent of households in

Nigeria used a mechanized input or animal power on their plots

– >50 percent of households in Ethiopia used oxen to prepare their plots

Ethiopia

MalawiNiger

Nigeria

Tanzania

Uganda

LSMS-ISA avg

0

1

2

3

4

5

6

7

8

9

10

1

0.2

1

32

4

2

9

0.4

7

44 4

5

Water control is limited

% of all cultivated land under irrigation by smallholders % of households with at least some irrigation on farm

Considerable variation exists within countries in the prevalence of input use and of input use intensity

conditional on input use.


Agro-chemicals Inorganic fertilizer

Suggests need for research to understand drivers of within-country agricultural input use variation.

There is surprisingly low correlation between the use of commonly “paired” modern inputs at the household- and,

especially, the plot-level.


Ethiopia: household level

Ethiopia: plot level

Raises important questions about prospective untapped productivity gains from coordinated modern inputs use.

Input intensification is happening for maize in particular.


Plots with mostly maize are among those most likely to receive a modern input and with the highest application amounts, including agro-chemicals

Related: plots that include a major cash crop (<25 percent of all plots) are generally no more likely to receive modern agricultural inputs

25-40 percent of maize cultivating households purchased new maize seed

~25 percent of maize cultivating households in Ethiopia and >50 percent in Malawi used an improved variety

An inverse relationship consistently exists between farm or plot size and input use intensity.


-50

0

50

100

150

200

Ave

rage

ino

rga

nic

fert

ilize

r u

se (

kg/h

a)

0 1 2 3 4Total hectares of land under cultivation

95% CI lpoly smooth

kernel = epanechnikov, degree = 1, bandwidth = .34, pwidth = .51

Local polynomial smooth

0

50

100

150

200

kg/h

a o

f in

org

anic

fert

ilize

r ap

plie

d to

fiel

d

0 .5 1 1.5plot size in hectares

95% CI lpoly smooth

kernel = epanechnikov, degree = 1, bandwidth = .2, pwidth = .3

Local polynomial smooth

Nigeria: farm level Nigeria: plot level

In most cases, this relationship is more pronounced at the plot level, therefore inter-household variation cannot explain relationship.

Suggests need to better understand intra-household agricultural input allocation decisions.

Farmers do not significantly vary input application rates according to perceived soil quality.


Simple descriptive statistics: farmers do not appear to adjust input application rates to accommodate their perceptions of plot soil quality (Malawi, Tanzania, Uganda)

“Within household” regression analysis: plots deemed “average” or “poor” quality are more likely to receive inorganic fertilizer applications, however only explains a tiny amount of variation

Farmers do not make different input use decisions across eroded and non-eroded plots (Niger, Uganda, Malawi, Tanzania), including with respect to organic fertilizer

Suggests a need for extension programming around soil fertility and input use and the need to invest in inexpensive soil quality tests

Few households use credit to purchase modern inputs.


In all countries except Ethiopia, less than one percent of cultivating households used credit— either formal or informal—to purchase improved seed varieties, inorganic fertilizer, or agro-chemicals.

In Ethiopia, where there exist widespread input credit guarantee schemes operated by cooperatives, nearly 25 percent of cultivating households claimed to receive some type of “credit service,” although we cannot be sure whether this is for agriculture or other household purchases.

Reinforces widespread perceptions of the weakness of agricultural input credit markets in the region.

Much scope remains for deepening rural financial markets, despite recent advances in money transfer systems based on mobile phone platforms, the proliferation of microfinance institutions, etc.


• Male headed households are more likely use modern inputs across almost all countries and input types

• Plots managed or owned by men (88 percent of all plots), are more likely to receive inorganic fertilizer and in higher amounts; almost always holds when controlling for gender of household head

• Related to work on “gender gap” in ag input productivity

Gender differences in input use exist at the farm and plot level.

• Male headed households are more likely use modern inputs across almost all countries and input types

• Plots managed or owned by men (88 percent of all plots), are more likely to receive inorganic fertilizer and in higher amounts; almost always holds when controlling for gender of household head

• Related to work on “gender gap” in ag input productivity


National-level factors explain nearly half of the farm-level variation in inorganic fertilizer and agro-chemical use.

Categories of variables Shapley value

Bio-physical variables: rain, soil, elevation, maximum greenness, agro-ecological zones

24

Socio-economic variables: consumption level, sex of household head, household size and dependency ratio

4

Farm operation characteristic variables: farm size, number of crops, type of crops

16

Market and accessibility variables: distance to market and road, prices of fertilizer and main grain

11

Country dummy variables 45

Variation in household-level inorganic fertilizer use

• Ultimately interested to learn where most of the variation in input use comes from: biophysical, infrastructure, market, socio-economic, or policy-specific variables?

• Binary use at household level (avoids bias from survey design)

• R2 decomposition using Shapley-Owen values

• 45 percent of variation in inorganic fertilizer use can be explained by country level

• Similar for agro-chemical use (43 percent)

Suggests the policy and operating environments facilitated by governments and regional processes (e.g., CAADP) are critically

important for ushering in a Green Revolution in Sub-Saharan Africa.

Conclusions

Confirmed longstanding conjectures: • Irrigation and mechanization remain limited• Women farmers use fewer inputs than men• Agricultural input credit use is virtually non-existent

New findings that suggest more policy-relevant research opportunities:• More agro-chemical use by smallholder farmers than commonly thought• Huge amount of across and within country variation in fertilizer and

agro-chemical use• Input use is no higher on cash crops; maize is receiving a fair amount of

input use• Very little pairing of inputs with bio-physical complementarities at the

plot level• Little correlation between farmer-perceived plot quality and input use• Input use intensity if more related to plot than farm size• Country-level factors explain large amount of variation in household

fertilizer and agro-chemical use

Modern agricultural input use in Sub-Saharan Africa is far more nuanced and

varied than current claims suggest.

Ten striking facts about agricultural input use in Sub-Saharan Africa Megan Sheahan and Christopher...

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