Research Topics

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 #362
Publication Date: 01/16/2019
Type: Data Analysis
Abstract

Self-Help Groups (SHGs) in Sub-Saharan Africa can be defined as mutual assistance organizations through which individuals undertake collective action in order to improve their own lives. “Collective action” implies that individuals share their time, labor, money, or other assets with the group. In a recent EPAR data analysis, we use three nationally-representative survey tools to examine various indicators related to the coverage and prevalence of Self-Help Group usage across six Sub-Saharan African countries. EPAR has developed Stata .do files for the construction of a set of self-help group indicators using data from the Living Standards Measurement Study - Integrated Surveys on Agriculture (LSMS-ISA), Financial Inclusion Index (FII), and FinScope.

We compiled a set of summary statistics for the final indicators using data from the following survey instruments:

  • Ethiopia:
    • Ethiopia Socioeconomic Survey (ESS), Wave 3 (2015-16)
  • Kenya:
    • Kenya FinScope, Wave 4 (2015)
    • Kenya FII, Wave 4 (2016)
  • Nigeria
    • Nigeria FII, Wave 4 (2016)
  • Rwanda:
    • Rwanda FII, Wave 4 (2016)
  • Tanzania:
    • Tanzania National Panel Survey (TNPS), Wave 4 (2014-15)
    • Tanzania FinScope, Wave 4 (2017)
    • Tanzania FII, Wave 4 (2016)
  • Uganda:
    • Uganda FinScope, Wave 3 (2013)
    • Uganda FII, Wave 4 (2016)

The raw survey data files are available for download free of charge from the World Bank LSMS-ISA website, the Financial Sector Deepening Trust website, and the Financial Inclusion Insights website. The .do files process the data and create final data sets at the household (LSMS-ISA) and individual (FII, FinScope) levels with labeled variables, which can be used to estimate summary statistics for the indicators.

All the instruments include nationally-representative samples. All estimates from the LSMS-ISA are household-level cluster-weighted means, while all estimates from FII and FinScope are calculated as individual-level weighted means. The proportions in the Indicators Spreadsheet are therefore estimates of the true proportion of individuals/households in the national population during the year of the survey. EPAR also created a Tableau visualization of these summary statistics, which can be found here.

We have also prepared a document outlining the construction decisions for each indicator across survey instruments and countries. We attempted to follow the same construction approach across instruments, and note any situations where differences in the instruments made this impossible.

The spreadsheet includes estimates of the following indicators created in our code files:

Sub-Populations

  • Proportion of individuals who have access to a mobile phone
  • Proportion of individuals who have official identification
  • Proportion of individuals who are female
  • Proportion of individuals who use mobile money
  • Proportion of individuals who have a bank account
  • Proportion of individuals who live in a rural area
  • Individual Poverty Status
    • Two Lowest PPI Quintiles
    • Middle PPI Quintile
    • Two Highest PPI Quintiles

Coverage & Prevalence

  • Proportion of individuals who have interacted with a SHG
  • Proportion of individuals who have used an SHG for financial services
  • Proportion of individuals who depend most on SHGs for financial advice
  • Proportion of individuals who have received financial advice from a SHG
  • Proportion of households that have interacted with a SHG
  • Proportion of households in communities with at least one SHG
  • Proportion of households in communities with access to multiple farmer cooperative groups
  • Proportion of households who have used an SHG for financial services

Characteristics
In addition, we produced estimates for 29 indicators related to characteristics of SHG use including indicators related to frequency of SHG use, characteristics of SHG groups, and individual/household trust of SHGs.

EPAR Technical Report #345
Publication Date: 12/01/2017
Type: Literature Review
Abstract

The share of private sector funding, relative to public sector funding, for drug, vaccine, and diagnostic research & development (R&D) differs considerably across diseases. Private sector investment in overall health R&D exceeds $150 billion annually, but is largely concentrated on non-communicable chronic diseases with only an estimated $5.9 billion focused on "global health", targeting diseases that primarily affect low and middle-income countries (LMICs). We examine the evidence for five specific disincentives to private sector global health R&D investment: scientific uncertainty, weak policy environments, limited revenues and market uncertainty, high fixed and sunk costs, and downstream rents from imperfect markets. Though all five may affect estimates of net returns from an investment decision, they are worth examining separately as each calls for a different intervention or remediation to change behavior.

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 #359
Publication Date: 11/13/2017
Type: Literature Review
Abstract

Cash transfer programs are interventions that directly provide cash to target specific populations with the aim of reducing poverty and supporting a variety of development outcomes. Low- and middle-income countries have increasingly adopted cash transfer programs as central elements of their poverty reduction and social protection strategies. Bastagli et al. (2016) report that around 130 low- and middle-income countries have at least one UCT program, and 63 countries have at least one CCT program (up from 27 countries in 2008). Through a comprehensive review of literature, this report primarily considers the evidence of the long-term impacts of cash transfer programs in low- and lower middle-income countries. A review of 54 reviews that aggregate and summarize findings from multiple studies of cash transfer programs reveals largely positive evidence on long-term outcomes related to general health, reproductive health, nutrition, labor markets, poverty, and gender and intra-household dynamics, though findings vary by context and in many cases overall conclusions on the long-term impacts of cash transfers are mixed. In addition, evidence on long-term impacts for many outcome measures is limited, and few studies explicitly aim to measure long-term impacts distinctly from immediate or short-term impacts of cash transfers.

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 Research Brief #316
Publication Date: 12/13/2015
Type: Literature Review
Abstract

The literature on poverty’s causes and cures in developing countries posits a variety of contributing factors. Most researchers acknowledge that a sustained exit from poverty is complex and no single causal pathway from poverty to non-poverty exists. In this review, we present a summary framework for categorizing the various theorized pathways out of poverty, and evaluate the empirical evidence for which interventions and resulting outcomes are most frequently and most strongly associated with poverty alleviation. We conducted a literature review on pathways out of poverty for low-income households in developing countries and identified and categorized general strategies and outcomes demonstrated to be empirically associated with poverty alleviation. We organized the general strategies into four asset groups that could be targeted to alleviate poverty: human, natural, built / financial, and social / political. Much of the literature presents positive results on poverty alleviation, but it is difficult to compare across studies because many of the studies were conducted in different countries and at different scales, and use a variety of outcome measures.

EPAR Technical Report #293
Publication Date: 03/31/2015
Type: Literature Review
Abstract

This report reviews the current body of peer-reviewed scholarship exploring the impacts of morbidity on economic growth. This overview seeks to provide a concise introduction to the major theories and empirical evidence linking morbidity – and the myriad different measures of morbidity – to economic growth, which is defined primarily in terms of gross domestic product (GDP) and related metrics (wages, productivity, etc.). Through a systematic review of published manuscripts in the fields of health economics and economic development we further identify the most commonly-used pathways linking morbidity to economic growth. We also highlight the apparent gaps in the empirical literature (i.e., theorized pathways from morbidity to growth that remain relatively untested in the published empirical literature to date).

EPAR Research Brief #167
Publication Date: 10/07/2011
Type: Data Analysis
Abstract

This is "Section B" of a report that presents estimates and summary statistics from the 2008/2009 wave of the Tanzania National Panel Survey (TZNPS), part of the Living Standards Measurement Study – Integrated Surveys on Agriculture (LSMS-ISA). We present our analyses of household characteristics by gender and by administrative zone, considering landholding size, number of crops grown, yields, livestock, input use, and food consumption.

EPAR Technical Report #166
Publication Date: 10/06/2011
Type:
Abstract

This is "Section H" of a report that presents estimates and summary statistics from the 2008/2009 wave of the Tanzania National Panel Survey (TZNPS), part of the Living Standards Measurement Study – Integrated Surveys on Agriculture (LSMS-ISA). We present our analysis of nutrition and malnutrition, and of the variation across agricultural and non-agricultural households, gender, age, and zones. For example, we find that stunting (low height for age) was the most prevalent indicator of malnutrition, with 43% of the under-five population categorized in the moderate to severe range, while less than 17% children under the age of five were reported to be underweight (low weight for age). A higher proportion of children in female-headed households experienced stunting (46% versus 42% in male-headed households) and were underweight (19% versus 16% in male-headed households).