EPAR TECHNICAL REPORT #362
Self Help Groups Prevalence and Coverage
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.

Indicator Cross-Comparisons, All Countries Pivot Tables
EPAR Technical Report #355 and EPAR Research Briefs #355A & #355B & #355C
Impact of Regulations on Cash-In and Cash-Out Networks
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.

355 Full Report, 355 Results Coding, 355a Research Brief, 355b Research Brief , 355c Research Brief
EPAR Research Brief #360
Economic Growth and Poverty in Ethiopia
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. 

Research Brief
EPAR Technical Report #18
Labor Constraints in the Sub-Saharan Agricultural Market
Publication Date: 04/15/2009
Type: Literature Review
Abstract

This report present a thorough review of relevant literature regarding labor constraints currently being faced in Sub-Saharan Africa (SSA).  The review focuses on the impacts of labor supply issues, particularly as they relate to the use of new technology and management techniques, off farm labor migration, and the impacts of HIV/AIDS. The review is provides a basic breakdown of the different kinds of agricultural labor in SSA, before presenting the evidence on the causes and impact of agricultural labor constraints. Though labor constraints can be relevant on both the demand and supply side, especially for certain groups such as women and youth, our review follows the literature by focusing on the supply side issues. The literature reviewed was written between 1990 and 2008, and includes a combination of reports from government organizations and highly cited journal articles.

Full Report
EPAR Technical Report #19
The Impacts of Special Economic Zones
Publication Date: 02/06/2009
Type: Literature Review
Abstract

Special Economic Zones (SEZs) are generally defined as geographically delimited areas administered by a single body, offering certain incentives (duty-free importing and streamlined customs procedures, for instance) to businesses that physically locate within the zone. This literature review provides a baseline analysis of SEZs and their potential impacts on smallholder farmers in SSA. Criticism on SEZs is distinctly divided between those who criticize on social or environmental grounds versus those who question the economic impact of SEZs. SEZs are often criticized based on perceived negative socio-economic impacts—particularly their negative impact on women, labor, and working conditions. This review includes several country-specific studies that find evidence that SEZs actually have higher environmental standards and higher worker satisfaction than outside the SEZ. Most responses to criticisms do note, however, that the case studies’ results are not necessarily generalizable to SEZs throughout the world. The literature review includes key elements of successes and failures pulled from the case studies of SEZs in SSA. Though the evidence is insufficient to conclusively determine if smallholder farmers receive direct benefits from SEZs and their associated agroindustrial contracts, this review finds that resources provided to farmers (credit at rates lower than bank rates, technical or managerial assistance, pesticides, seeds, and fertilizer on credit) tend to be concentrated among larger farmers. The report concludes with a note on donor involvement as well as recommendations for further research. 

Literature Review