Ten striking facts about agricultural input use in Sub-Saha - PowerPoint Presentation

Slide1

Ten striking facts about agricultural input use in Sub-Saharan Africa

Megan Sheahan and Christopher

B. BarrettPresentation 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 Slide2

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. Slide3

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 samplesCase studies with limited statistical underpinnings Data collected 10-20 years agoMajor changes in SSA in last 10-20 years:High and volatile food pricesUrbanization 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)Slide4

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

Introduction

Large cross section of SSA’s populationCross-country comparableStrong focus on agricultural data collectionPlot, household, and community level information Nationally-representative statistics as well as within-country (and even within-household) analysis Statistics derived from farmers’ accountsCoupled with growing collection of geo-referenced data sets

Living Standards Measurement Study Integrated Surveys on AgricultureBurkina Faso

  Ethiopia   Malawi  

Mali

  Niger   Nigeria   Tanzania   UgandaSlide5

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 conditionsFocus on fertilizer, improved seed varieties, agro-chemicals (pesticides, herbicides, fungicides), irrigation, and mechanizationHuge number of descriptive statistics included in Sheahan and Barrett (2014) World Bank Policy Research Working Paper No. 701410 most important facts presented here… IntroductionSlide6

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

Sample selection and

variable creationCountryYearSeason

# 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

2010/11Long rainy2,3724,794Uganda2010/11First1,9343,349

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 weightsSlide7

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

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

EthiopiaSlide8

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

2 of 10 “striking” facts

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 plotsSlide9

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

3 of 10 “striking” facts

Agro-chemicalsInorganic fertilizerSuggests need for research to understand drivers of within-country agricultural input use variation.Slide10

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

4 of 10 “striking” facts

Ethiopia: household levelEthiopia: plot levelRaises important questions about prospective untapped productivity gains from coordinated modern inputs use.Slide11

Input intensification is happening for maize in particular.

5 of 10 “striking” facts

Plots with mostly maize are among those most likely to receive a modern input and with the highest application amounts, including agro-chemicalsRelated: plots that include a major cash crop (<25 percent of all plots) are generally no more likely to receive modern agricultural inputs25-40 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 varietySlide12

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

6 of 10 “striking” facts

Nigeria: farm levelNigeria: plot levelIn 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.Slide13

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

7 of 10 “striking” facts

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 variationFarmers do not make different input use decisions across eroded and non-eroded plots

(Niger, Uganda, Malawi, Tanzania), including with respect to organic fertilizerSuggests

a need for

extension

programming around soil fertility and input use

and the

need to invest in inexpensive

soil

quality testsSlide14

Few households use credit to purchase modern inputs.

8 of 10 “striking” facts

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.Slide15

9 of 10 “striking” facts

M

ale headed households are more likely use modern inputs across almost all countries and input typesPlots 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 headRelated to work on “gender gap” in ag input productivity

Gender differences in input use exist at the farm

and

plot level. 

M

ale

headed households

are more likely use

modern inputs across almost all countries and input

types

P

lots

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 productivitySlide16

10 of 10 “striking” facts

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

Categories of variablesShapley valueBio-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:

b

iophysical

, infrastructure, market, socio-economic, or policy-specific variables?

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

R2 decomposition using Shapley-Owen values45 percent of variation in inorganic fertilizer use can be explained by country levelSimilar 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. Slide17

Conclusions

Confirmed longstanding conjectures:

Irrigation and mechanization remain limitedWomen farmers use fewer inputs than menAgricultural input credit use is virtually non-existentNew findings that suggest more policy-relevant research opportunities:More agro-chemical use by smallholder farmers than commonly thoughtHuge amount of across and within country variation in fertilizer and agro-chemical useInput use is no higher on cash crops; maize is receiving a fair amount of input useVery little pairing of inputs with bio-physical complementarities at the plot levelLittle correlation between farmer-perceived plot quality and input useInput use intensity if more related to plot than farm sizeCountry-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.