Research Topics

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 #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 Research Brief #242
Publication Date: 01/08/2014
Type: Data Analysis
Abstract

The purpose of this analysis is to provide a measure of marketable surplus of maize in Tanzania. We proxy marketable surplus with national-level estimates of total maize sold, presumably the surplus for maize producing and consuming households. We also provide national level estimates of total maize produced and estimate “average prices” for Tanzania which allows this quantity to be expressed as an estimate of the value of marketable surplus. The analysis uses the Tanzanian National Panel Survey (TNPS) LSMS – ISA which is a nationally representative panel survey, for the years 2008/2009 and 2010/2011. A spreadsheet provides our estimates for different subsets of the sample and using different approaches to data cleaning and weighting. The total number of households for Tanzania was estimated with linear extrapolation based on the Tanzanian National Bureau of Statistics for the years 2002 and 2012. The weighted proportions of maize-producing and maize-selling households were multiplied to the national estimate of total households. This estimate of total Tanzanian maize-selling and maize-producing households was then multiplied by the average amount sold and by the average amount produced respectively to obtain national level estimates of total maize sold and total maize produced in 2009 and 2011.

EPAR Research Brief #216
Publication Date: 08/08/2013
Type: Data Analysis
Abstract

In this brief we analyze patterns of intercropping and differences between intercropped and monocropped plots among smallholder farmers in Tanzania using data 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). Intercropping is a planting strategy in which farmers cultivate at least two crops simultaneously on the same plot of land. In this brief we define intercropped plots as those for which respondents answered “yes” to the question “Was cultivation intercropped?” We define “intercropping households” as those households that intercropped at least one plot at any point during the year in comparison to households that did not intercrop any plots. The analysis reveals few significant, consistent productivity benefits to intercropping as currently practiced. Intercropped plots are not systematically more productive (in terms of value produced) than monocropped plots. The most commonly cited reason for intercropping was to provide a substitute crop in the case of crop failure. This suggests that food and income security are primary concerns for smallholder farmers in Tanzania. A separate appendix includes the details for our analyses.

EPAR Technical Report #237
Publication Date: 06/09/2013
Type: Data Analysis
Abstract

Local crop diversity and crop cultivation patterns among smallholder farmers have implications for two important elements of the design of agricultural interventions in developing countries. First, crop cultivation patterns may aid in targeting by helping to identify geographic areas where improved seed and other productivity enhancing technologies will be most easily applicable. Second, these patterns may help to identify potential unintended consequences of crop interventions focused on a single crop (e.g. maize). This report analyzes the distribution of crop diversity and crop cultivation patterns, and factors that can lead to changes in these patterns among smallholder farmers in Tanzania with a focus on regional patterns of crop cultivation and changes in these patterns over time, the factors that affect crop diversity and changes in crop diversity, and the level of substitutability between crops grown by smallholder farmers. All analysis is based on the Tanzania National Panel Survey (TNPS) datasets from 2008 and 2010. The paper is structured as follows. Section I provides a description of regional patterns of crop cultivation and crop diversity between the two years of the panel. Section II presents background on the theoretical factors affecting crop choice, and presents our findings on the results of a multivariate analysis on the factors contributing to crop diversity. Finally, Section 3 provides a preliminary analysis of the level of substitutability between cereal crop of importance in Tanzania (maize, rice and sorghum/millet) and also between these cereal crops and non-cereal crops.

EPAR Research Brief #224
Publication Date: 02/04/2013
Type: Data Analysis
Abstract

This brief present our analysis of sorghum and millet cultivation in Tanzania using data 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).  In the 2007-2008 long and short rainy seasons, 13% of Tanzanian farming households cultivated sorghum and 6% cultivated millet, making these crops some of the least frequently cultivated priority crops in Tanzania. As a result, detailed analysis and determining statistical significance was limited by the low number of observations, particularly of millet. While sorghum and millet are often grouped together, our results suggest that in Tanzania there were differences among the households that cultivated these distinct crops. A separate appendix includes additional detail on our analyses.

EPAR Research Brief #219
Publication Date: 01/27/2013
Type: Literature Review
Abstract

This report provides a genderal overview of the sweet potato value chain in Ethiopia. The first section describes trends in sweet potato production and consumption since the early 1990s. The second section describes the uses and importance of sweet potatoes in Ethiopia. The final section discuss major issues in production, post-production, and marketing. The literature available on sweet potetoes in Ethiopia was quite limited and draws on the wider literature on sweet potatoes in East Africa where needed. We find that Ethiopia ranks fifteenth in the world in terms of sweet potato production. Production has been rising quickly since 2008, following a period of slow decline in the early 2000s. Yields have also been rising slowly since 2008, but are below their peak from 2001. Sweet potato roots are consumed domestically, mostly by poor rural households. The vines also provide an important source of feed for livestock during the dry season. Major constraints to sweet potato production in Ethiopia include a lack of quality planting materials, pests and disease, and underdeveloped markets.

EPAR Research Brief #217
Publication Date: 01/23/2013
Type: Literature Review
Abstract

Uganda is the biggest sweet potato producer in Africa in terms of area harvested and production, although Burundi, Rwanda and Madagascar have significantly higher yields.  Sweet potato is a major crop in Uganda, ranking third in cultivated area following plantains and cassava. Sweet potato ranks fourth in gross agricultural production value. The Government of Uganda has recognized sweet potatoes as an important crop for the country and a research priority, especially through establishing the National Agricultural Research Organization potato center. This report provides a general overview of the sweet potato value chain in Uganda. The first section describes trends in sweet potato production and consumption since 1996. The second section describes the varieties grown and their uses. The final section summarizes current practices and constraints in production, processing, and marketing.