Research Topics

EPAR Technical Report #374
Publication Date: 04/25/2019
Type: Portfolio Review
Abstract
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 #355 and EPAR Research Briefs #355A & #355B & #355C
Publication Date: 06/15/2018
Type: Literature Review
Abstract

Many low- and middle-income countries remain challenged by a financial infrastructure gap, evidenced by very low numbers of bank branches and automated teller machines (ATMs) (e.g., 2.9 branches per 100,000 people in Ethiopia versus 13.5 in India and 32.9 in the United States (U.S.) and 0.5 ATMs per 100,000 people in Ethiopia versus 19.7 in India and 173 in the U.S.) (The World Bank 2015a; 2015b). Furthermore, only an estimated 62 percent of adults globally have a banking account through a formal financial institution, leaving over 2 billion adults unbanked (Demirgüç–Kunt et al., 2015). While conventional banks have struggled to extend their networks into low-income and rural communities, digital financial services (DFS) have the potential to extend financial opportunities to these groups (Radcliffe & Voorhies, 2012). In order to utilize DFS however, users must convert physical cash to electronic money which requires access to cash-in, cash-out (CICO) networks—physical access points including bank branches but also including “branchless banking" access points such as ATMs, point-of-sale (POS) terminals, agents, and cash merchants. As mobile money and branchless banking expand, countries are developing new regulations to govern their operations (Lyman, Ivatury, & Staschen, 2006; Lyman, Pickens, & Porteous, 2008; Ivatury & Mas, 2008), including regulations targeting aspects of the different CICO interfaces. 

EPAR's work on CICO networks consists of five components. First, we summarize types of recent mobile money and branchless banking regulations related to CICO networks and review available evidence on the impacts these regulations may have on markets and consumers. In addition to this technical report we developed a short addendum (EPAR 355a) which includes a description of findings on patterns around CICO regulations over time. Another addendum (EPAR 355b) summarizes trends in exclusivity regulations including overall trends, country-specific approaches to exclusivity, and a table showing how available data on DFS adoption from FII and GSMA might relate to changes in exclusivity policies over time. A third addendum (EPAR 355c) explores trends in CICO network expansion with a focus on policies seeking to improve access among more remote or under-served populations. Lastly, we developed a database of CICO regulations, including a regulatory decision options table which outlines the key decisions that countries can make to regulate CICOs and a timeline of when specific regulations related to CICOs were introduced in eight focus countries, Bangladesh, India, Indonesia, Kenya, Nigeria, Pakistan, Tanzania, and Uganda.

EPAR Technical Report #346
Publication Date: 04/23/2018
Type: Literature Review
Abstract

The private sector is the primary investor in health research and development (R&D) worldwide, with investment annual investment exceeding $150 billion, although only an estimated $5.9 billion is focused on diseases that primarily affect low and middle-income countries (LMICs) (West et al., 2017b). Pharmaceutical companies are the largest source of private spending on global health R&D focused on LMICs, providing $5.6 billion of the $5.9 billion in total private global health R&D per year. This report draws on 10-K forms filed by Pharmaceutical companies with the U.S. Securities and Exchange Commission (SEC) in the year 2016 to examine the evidence for five specific disincentives to private sector investment in drugs, vaccines and therapeutics for global health R&D: scientific uncertainty, weak policy environments, limited revenues and market uncertainty, high fixed costs for research and manufacturing, and imperfect markets. 10-K reports follow a standard format, including a business section and a risk section which include information on financial performance, investment options, lines of research, promising acquisitions and risk factors (scientific, market, and regulatory). As a result, these filings provide a valuable source of information for analyzing how private companies discuss risks and challenges as well as opportunities associated with global health R&D targeting LMICs.

EPAR Research Brief #360
Publication Date: 02/05/2018
Type: Research Brief
Abstract

In this brief, we report on measures of economic growth, poverty and agricultural activity in Ethiopia. For each category of measure, we first describe different measurement approaches and present available time series data on selected indicators. We then use data from the sources listed below to discuss associations within and between these categories between 1994 and 2017. 

EPAR Technical Report #106
Publication Date: 11/02/2010
Type: Literature Review
Abstract

How development organizations, NGOs, and governments can best allocate scarce resources to those in need has long been debated. As opposed to universal allocation of resources, a more targeted approach attempts to minimize program costs while maximizing benefits among those with the greatest need or market opportunity. Drawing on literature from several sectors,this brief presents two categories of beneficiary targeting in the development context: administrative targeting and self-targeting. The paper includes a brief overview of targeting and segmentation in development, a summary of reasons for targeting, theoretical and practical critiques of targeting, and a discussion of targeting methods in research and practice, including examples from the literature. Implementation examples cited in this body of research include food aid program targeting by self-reported household income in Egypt; fertilizer use in low-potential zones of Uganda; and seven strategic initiatives to improve drought and disease resistance in crops in Asia and Sub-Saharan Africa.  We find that beneficiary segmentation has several theoretical advantages.  Improved targeting may increase the efficiency and equity of organizational and program efforts and help better match interventions to recipient preferences, increasing the likelihood of adoption and participation. Development organizations may improve the focus of both their strategic priorities and budgets through customized targeting methods. However, concerns exist regarding the accuracy, reliability, cost, and time-constraints of targeting methodologies. Creating valid and reliable target groups with implementation potential remains a significant challenge. 

EPAR Technical Brief #96
Publication Date: 09/02/2010
Type: Literature Review
Abstract

The purpose of this literature review is to examine research and decision-making tools that model the impacts of agricultural interventions. We begin with a short explanation of what model features are being described. We then review decision-support tools and user-end modeling tools (menu-driven tools with an interface designed for easy use), as well as academic and professional research models for assessing the potential impacts of agricultural interventions. This review also includes decision tools and models for analyzing agricultural and environmental policies outside of technology impacts in Sub-Saharan Africa and South Asia. The other tools mentioned here, for example a tool that considers nutritional intervention impacts, are included to help provide a broader understanding of the structure and availability of user-end, decision-making tools. In the final section of this brief, we review the most complex models used more in academic research than for in-field decision-making.

EPAR Technical Report #94
Publication Date: 08/17/2010
Type: Literature Review
Abstract

Market-oriented agricultural production can be a mechanism to increase smallholder farmer welfare, rural market performance, and contribute to overall economic growth. Cash crop production can allow households to increase their income by producing output with higher returns to land and labor and using the income generated from sales to purchase goods for consumption. However, in the face of missing and underperforming markets, African smallholder households are often unable to produce efficiently or obtain staple foods reliably and cheaply. This literature review summarizes the available literature on the impact of smallholder participation in cash crop and export markets on household welfare and rural markets. The review focuses exclusively on evidence from Sub-Saharan Africa regarding top and emerging export crops, with the addition of tobacco and horticulture due to the volume of research relevant to smallholder welfare gains from the production of these crops. It includes theoretical frameworks, case studies, empirical evidence, and historical analysis from 42 primary empirical studies and 112 resources overall.

EPAR Research Brief #72
Publication Date: 06/28/2010
Type: Literature Review
Abstract

How development organizations, NGOs, and governments can best allocate scarce resources to those in need has long been debated. As opposed to universal allocation of resources, a more targeted approach attempts to minimize program costs while maximizing benefits among those with the greatest need or market opportunity. Many international development organizations strategically target clients based on geographic location (e.g., community, region, country) or socio-economic indicators, such as the World Bank’s “$1 a day” poverty line. Drawing on literature from several sectors, this brief presents additional methods of beneficiary targeting that international development organizations might consider. We find that beneficiary targeting/segmentation has the potential to make organizational and program efforts more equitable and efficient. With limited resources, smaller organizations have tended to use single robust indicators or simple heuristics, whereas agribusinesses and private sector firms have used more data-intensive marketing tools to position their products. Technological innovation and better access to data have made targeting more prevalent and potentially more affordable in agricultural development. However, creating valid and reliable target segments remains the most significant challenge.