Research Topics

EPAR TECHNICAL REPORT #353
Publication Date: 12/28/2020
Type: Literature Review
Abstract

Recent research has used typologies to classify rural households into categories such as “subsistence” versus “commercialized” as a means of targeting agricultural development interventions and tracking agricultural transformation. Following an approach proposed by Alliance for a Green Revolution in Africa, we examine patterns in two agricultural transformation hallmarks – commercialization of farm output, and diversification into non-farm income – among rural households in Ethiopia, Nigeria, and Tanzania from 2008-2015. We classify households into five smallholder farm categories based on commercialization and non-farm income levels (Subsistence, Pre-commercial, Transitioning, Specialized Commercial, and Diversified Commercial farms), as well as two non-smallholder categories (Largeholder farms and Non-farm households). We then summarize the share of households in each of these categories, examine geographic and demographic factors associated with different categories, and explore households’ movement across categories over time. We find a large amount of “churn” across categories, with most households moving to a different (more or less commercialized, more or less diversified) category across survey years. We also find many non-farm households become smallholder farmers – and vice versa – over time. Finally, we show that in many cases increases in farm household commercialization or diversification rates actually reflect decreased total farm production, or decreased total income (i.e., declines in the denominators of the agricultural transformation metrics), suggesting a potential loss of rural household welfare even in the presence of “positive” trends in transformation indicators. Findings underscore challenges with using common macro-level indicators to target development efforts and track progress at the household level in rural agrarian communities.

EPAR Technical Report #363
Publication Date: 02/10/2019
Type: Data Analysis
Abstract

Studies of improved seed adoption in developing countries almost always draw from household surveys and are premised on the assumption that farmers are able to self-report their use of improved seed varieties. However, recent studies suggest that farmers’ reports of the seed varieties planted, or even whether seed is local or improved, are sometimes inconsistent with the results of DNA fingerprinting of farmers' crops. We use household survey data from Tanzania to test the alignment between farmer-reported and DNA-identified maize seed types planted in fields. In the sample, 70% of maize seed observations are correctly reported as local or improved, while 16% are type I errors (falsely reported as improved) and 14% are type II errors (falsely reported as local). Type I errors are more likely to have been sourced from other farmers, rather than formal channels. An analysis of input use, including seed, fertilizer, and labor allocations, reveals that farmers tend to treat improved maize differently, depending on whether they correctly perceive it as improved. This suggests that errors in farmers' seed type awareness may translate into suboptimal management practices. In econometric analysis, the measured yield benefit of improved seed use is smaller in magnitude with a DNA-derived categorization, as compared with farmer reports. The greatest yield benefit is with correctly identified improved seed. This indicates that investments in farmers' access to information, seed labeling, and seed system oversight are needed to complement investments in seed variety development.

EPAR Technical Report #349
Publication Date: 11/30/2017
Type: Literature Review
Abstract

Donor countries and multilateral organizations may pursue multiple goals with foreign aid, including supporting low-income country development for strategic/security purposes (national security, regional political stability) and for short-and long-term economic interests (market development and access, local and regional market stability). While the literature on the effectiveness of aid in supporting progress on different indicators of country development is inconclusive, donors are interested in evidence that aid funding is not permanent but rather contributes to a process by which recipient countries develop to a point that they are economically self-sufficient. In this report, we review the literature on measures of country self-sufficiency and descriptive evidence from illustrative case studies to explore conditions associated with transitions toward self-sufficiency in certain contexts.

  

EPAR Technical Report #335
Publication Date: 11/21/2017
Type: Data Analysis
Abstract
EPAR has developed Stata do.files for the construction of a set of agricultural development indicators using data from the Living Standards Measurement Study - Integrated Surveys on Agriculture (LSMS-ISA). We are sharing our code and documenting our construction decisions both to facilitate analyses of these rich datasets and to make estimates of relevant indicators available to a broader audience of potential users. 
Code, Code, Code, Code
EPAR Technical Report #356
Publication Date: 10/31/2017
Type: Data Analysis
Abstract

According to AGRA's 2017 Africa Agriculture Status Report, smallholder farmers make up to about 70% of the population in Africa. The report finds that 500 million smallholder farms around the world provide livelihoods for more than 2 billion people and produce about 80% of the food in sub-Saharan Africa and Asia. Many development interventions and policies therefore target smallholder farm households with the goals of increasing their productivity and promoting agricultural transformation. Of particular interest for agricultural transformation is the degree to which smallholder farm households are commercializating their agricultural outputs, and diversifying their income sources away from agriculture. In this project, EPAR uses data from the World Bank's Living Standards Measurement Study - Integrated Surveys on Agriculture (LSMS-ISA) to analyze and compare characteristics of smallholder farm households at different levels of crop commercialization and reliance on farm income, and to evaluate implications of using different criteria for defining "smallholder" households for conclusions on trends in agricultural transformation for those households.

 

Code
EPAR Technical Report #339
Publication Date: 09/28/2017
Type: Data Analysis
Abstract

An ongoing stream of EPAR research considers how public good characteristics of different types of research and development (R&D) and the motivations of different providers of R&D funding affect the relative advantages of alternative funding sources. For this project, we seek to summarize the key public good characteristics of R&D investment for agriculture in general and for different subsets of crops, and hypothesize how these characteristics might be expected to affect public, private, or philanthropic funders’ investment decisions. 

Code
EPAR Technical Report #341
Publication Date: 08/03/2017
Type:
Abstract
Data on public expenditures on agriculture are not systematically collected in any one database. Rather, a variety of sources collect and publish data on certain aspects of agricultural public expenditures. These sources vary in their data collection methods, their frequency of data collection, and the specific expenditures they report on. We collected data on agricultural public expenditures and conducted preliminary analyses for four countries: India (with a focus on Bihar, Odisha, and Uttar Pradesh), Ethiopia, Nigeria, and Tanzania. The data are disaggregated in a variety of ways depending on the source, but we include disaggregated data where available comparing planned or budgeted vs. actual spending, government vs. donor spending, soending by activity or funding area, and spending by commodity or value chain activity. Our goals are to facilitate further analysis of trends in agricultural public expenditures across countries and over time, and to highlight gaps and differences in data sources.
EPAR Technical Report #331
Publication Date: 06/20/2016
Type: Data Analysis
Abstract

Labor is one of the most productive assets for many rural households in developing countries. Despite the importance of labor—and time use more generally—little research has empirically examined the quality of time-use data in household surveys. Many household surveys rely on respondent recall, the reliability of which may decrease as recall length increases. In addition, respondents often report on time allocation for the entire household, which they may not know or recall as clearly as their own time allocation. Finally, simultaneous activities such as tending children while preparing dinner, may lead to the systematic underestimation of certain activities, particularly those that tend to be performed by women. This paper examines whether the identity of the survey respondent affects estimates of time allocation within the household. Drawing on the Ugandan LSMS-ISA household survey, we find that individuals responding for themselves report higher levels of time use over the previous week than when responding for other household members. Moreover, male respondents tend to underreport time allocation for females over the age of 15 as compared to female respondents, especially time spent on domestic activities. In addition, an analysis of the effects of two economics shocks—having a baby and floods or droughts—suggests that the identity of the respondent can affect substantive conclusions about the effects of shocks on household time use.

 

EPAR Research Brief #332
Publication Date: 02/26/2016
Type: Literature Review
Abstract

Household survey data are a key source of information for policy-makers at all levels. In developing countries, household data are commonly used to target interventions and evaluate progress towards development goals. The World Bank’s Living Standards Measurement Study - Integrated Surveys on Agriculture (LSMS-ISA) are a particularly rich source of nationally-representative panel data for six Sub-Saharan African countries: Ethiopia, Malawi, Niger, Nigeria, Tanzania, and Uganda. To help understand how these data are used, EPAR reviewed the existing literature referencing the LSMS-ISA and identified 415 publications, working papers, reports, and presentations with primary research based on LSMS-ISA data. We find that use of the LSMS-ISA has been increasing each year since the first survey waves were made available in 2009, with several universities, multilateral organizations, government offices, and research groups across the globe using the data to answer questions on agricultural productivity, farm management, poverty and welfare, nutrition, and several other topics.

EPAR Technical Report #310
Publication Date: 11/20/2015
Type: Literature Review
Abstract

Cereal yield variability is influenced by initial conditions such as suitability of the farming system for cereal cultivation, current production quantities and yields, and zone-specific potential yields limited by water availability. However, exogenous factors such as national policies, climate, and international market conditions also impact farm-level yields directly or provide incentives or disincentives for farmers to intensify production. We conduct a selective literature review of policy-related drivers of maize yields in Ethiopia, Kenya, Malawi, Rwanda, Tanzania, and Uganda and pair the findings with FAOSTAT data on yield and productivity. This report presents our cumulative findings along with contextual evidence of the hypothesized drivers behind maize yield trends over the past 20 years for the focus countries.