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

2. 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.

3. 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)

4. 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 comparable 3.Strong focus on agricultural data collection 4.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 sets Living Standards Measurement Study Integrated Surveys on Agriculture Burkina Faso Ethiopia Malawi Mali Niger Nigeria Tanzania Uganda

5. 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

6. 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 CountryYearSeason# hh# plots Ethiopia2011/12-2,85223,051 Malawi2010/11Rainy10,08618,598 Niger2011/12Rainy2,2086,109 Nigeria2010/11-2,9395,546 Tanzania2010/11Long rainy2,3724,794 Uganda2010/11First1,9343,349 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 weights

7. 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 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

8. 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 plots

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

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

11. 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-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

12. An inverse relationship consistently exists between farm or plot size and input use intensity. 6 of 10 “striking” facts Nigeria: farm levelNigeria: 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.

13. 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 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

14. 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.

15. 9 of 10 “striking” facts 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

16. 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 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 variables45 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) R 2 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.

17. 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.