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Self-Help Group Interaction and Financial Service Use

This visualization summarizes data on Self-Help Group interaction and financial service use accross sub-populations in 8 Sub-Saharan African countries using data from the Financial Inclusion Insights (FII), FinScope, and LSMS-ISA surveys.

In contrast to Western contexts where the term “self-help group” often has mental health connotations, Self-Help Groups in Sub-Saharan Africa can be defined as mutual assistance organizations through which individuals undertake collective action to improve their own lives. Collective action implies that individuals share their time, labor, money, or other assets with the group. A recent EPAR data analysis used three nationally-representative survey tools to examine various indicators related to the coverage and prevalence of Self-Help Groups across six Sub-Saharan African countries. See the tables at the bottom of this page for more information on the sample and variable definitions.

To view this visualization in full-screen, visit the Tableau page here.

Hover over specific data points on either the map or figures to discover more information about what data and characteristics they represent. In order to focus the information presented in the charts on a particular country or type of group, either: 1) select a group type, country, or particular data point by clicking on the desired selection in the figure or legend (you can use CTRL to select multiple categories); or 2) select options from the filter menus at the top of the page. To revert back to a prior selection or reverse your last action, use the undo and redo buttons in the bottom right of the visualization. Clicking the reset button or a blank space in the selected chart will return the visualization to the standard view. 

The Visualization

The first visualization presents data on Self-Help Group interaction and financial service use at the individual level. The second presents the same data at the household level. These interactive figures, produced using Tableau, allow users to explore and compare these indicators across different countries and subpopulations.

Data

The data used to produce these visualizations comes from three different surveys:

The World Bank’s Living Standards Measurement Study – Integrated Surveys on Agriculture (LSMS-ISA), a nationally-representative household panel survey dataset for eight countries in Sub-Saharan Africa. The survey includes linked plot, household, and community level modules that provide information on crops, livestock, farming practices, and socio-demographics.

The Intermedia Financial Inclusion Insights (FII) Survey, a nationally-representative survey focused on financial inclusion and consumers’ financial behaviors.

The FinScope Survey,  a nationally-representative survey that has been conducted in over 30 countries. FinScope explores financial inclusion, attitudes, and behavior.

Below is a list of surveys used by country. We used the most recent wave of each survey for each country.

Ethiopia:
LSMS-ISA: Wave 3 (2015-16), available through the World Bank LSMS-ISA website

Kenya:
FinScope: Wave 4 (2015), available via the Financial Sector Deepening Trust website
FII: Wave 4 (2016), available via request from the Financial Inclusion Insights website

Nigeria:
FII: Wave 4 (2016), available via request from the Financial Inclusion Insights website

Rwanda:
FII: Wave 4 (2016), available via request from the Financial Inclusion Insights website

Tanzania:
LSMS-ISA: Wave 4 (2014-15), available through the World Bank LSMS-ISA website
FinScope: Wave 4 (2017), available via the Financial Sector Deepening Trust website
FII: Wave 4 (2016), available via request from the Financial Inclusion Insights website

Uganda:
FinScope: Wave 3 (2013), available via the Financial Sector Deepening Trust website.
FII: Wave 4 (2016), available via request from the Financial Inclusion Insights website

Sample

Table 1. Individual-level data sample sizes by data source and country

Kenya Nigeria Rwanda Tanzania Uganda Total
FII 3,000 6,352 2,003 3,029 3,000 17,384
FinScope 8,665 9,459 3,401 21,525
Cross-survey total 11,665 6,352 2,003 12,488 6,401 38,909

Table 2. Household-level data sample sizes by data source and country

Ethiopia Tanzania Total
LSMS-ISA 3,699 3,352 7,051

Group Type Definitions

Group Type Definition
ASCA Accumulating Savings and Credit Association
ROSCA Rotating Savings and Credit Association
SACCO Savings and Credit Cooperative
VLSLG Village-Level Saving-Lending Group
VSLA Village Savings and Loan Association

Variable Definitions

Variable Definition
Individual-level (FII, FinScope) Household-level (LSMS-ISA)
Self-Help Group Interaction Respondent has interacted with a Self-Help Group in any way (includes receiving financial advice, using financial services, or being a group member) Household has interacted with a Self-Help Group in any way (includes receiving financial advice, using financial services, being a group member, or acquiring agricultural inputs like seeds or fertilizer)
Self-Help Group Financial Service Use Respondent has used a Self-Help Group for any financial service, including saving, borrowing, and investing. Household has used a Self-Help Group for any financial service, including saving, borrowing, and investing.
Rural Individual lives in a rural area Household is located in a rural area
Gender Sex of the individual (male or female) Sex of the head of household (male or female)
Official ID Has some form of national ID Not included
Poverty Level Progress out of Poverty Index (PPI) scores. We define poverty as a score in the lowest two PPI quintiles. Purchasing power parity (PPP) per day. We define poverty as daily consumption per person in the household below $1.25.
Owns a Bank Account Individual has access to a bank account Household has access to a bank account
Has Access to a Mobile Phone Individual has access to a mobile phone, either through self-ownership, or through someone else Household has access to a mobile phone, either through self-ownership, or through someone else
Has Used Mobile Money Individual currently uses or has used mobile money in the past Household currently uses or has used mobile money in the past

by Elan Ebeling

Summarizing research by C. Leigh Anderson, Travis Reynolds, Pierre Biscaye, Kirby Callaway, Elan Ebeling, Annie Rose Favreau, Melissa Howlett, Daniel Lunchik-Seymour, Emily Morton, and Kels Phelps