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 #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 Research Brief #190
Publication Date: 03/30/2012
Type: Data Analysis
Abstract

This brief presents a comparative analysis of men and women and of male- and female-headed households 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). We compare farm activity, productivity, input use, and sales as well as labor allocations by gender of the respondent and of the household head. In households designated “female-headed” a woman was the decision maker in the household, took part in the economy, control and welfare of the household, and was recognized by others in the household as the head. For questions regarding household labor (both non-farm and farm), the gender of the individual laborer is recorded, and we use this to illustrate the responsibilities of male and female household members. An appendix provides the details for our analyses.

EPAR Research Brief #32
Publication Date: 06/30/2009
Type: Literature Review
Abstract

Though not indigenous to Sub-Saharan Africa (SSA), cassava plays, to varying degrees, five major roles in African development: famine-reserve crop, rural food staple, cash crop for urban consumption, livestock feed, and industrial raw material. Cassava production in SSA was historically a significant staple crop for smallholder farmers and continues to be the second most important food crop in Africa (after maize) in terms of calories consumed. Subsistence crops such as cassava are often considered women’s crops with the standard explanation that women are responsible for feeding the family and thus prefer to grow crops for the household. This brief reviews the role that women play in cassava production, and considers ways to better address gender issues from planting through post-harvest production. We find that the potential gains to cassava production made possible through improved technology will not be fully realized without the participation of women farmers and without women farmers having access to credit, markets, and extension services. Additionally, evidence from SSA suggests that labor for harvesting and processing, rather than labor for weeding, has become the key labor constraint for cassava, and addressing this concern may be more important than further yield increases for raising production levels.

EPAR Research Brief #27
Publication Date: 05/09/2009
Type: Literature Review
Abstract

As a source of employment for over 20 million Sub-Saharan African (SSA) farmers and the fastest-growing food source in Africa, rice plays a vital role in African economies and daily life. Women play a substantial role in SSA rice production and rely heavily on the income it generates. Not recognizing this role has often resulted in development and research projects failing to address women’s well-being and also failing to achieve project and development goals. Female farmers in SSA have been less likely than male farmers to adopt productivity-enhancing rice technologies such as improved seeds, fertilizer, pesticides, or small machinery, even when those technologies are designed specifically to help women. A more complete understanding of the dynamics and diversity of gender roles in rice farming is necessary to improve the likelihood of successful interventions. This brief provides an overview of the role of women in rice production, and provides a framework for analyzing technology’s impact on women throughout the cropping cycle. We find that labor constraints, low education levels, cultural inappropriateness, and asymmetric access to resources all contribute to low adoption of rice technology by women. In order to fully realize the poverty reduction benefits of increased rice production in SSA, evidence suggests that research and extension programs must consider how interventions will affect women along every stage of the production chain. The effect on women and their households will vary depending on region, culture, ethnicity, socio-economic status, and role in cultivating rice.