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. SHGs are believed to be effective avenues through which to build empowerment, financial inclusion, agricultural outcomes, and/or health outcomes.
Recent EPAR data analysis includes PivotTables examining various indicators related to the coverage and prevalence of SHG usage across Ethiopia, Kenya, Nigeria, Rwanda, Tanzania, and Uganda. These PivotTables aggregate data from the following nationally-representative survey tools:
- Living Standards Measurement Study - Integrated Surveys on Agriculture (LSMS-ISA
- Ethiopia Socioeconomic Survey (ERSS)
- Nigerian General Household Survey (GHS)
- Tanzania National Panel Survey (TZNPS)
- Uganda National Panel Survey (UNPS)
- Financial Inclusion Index (FII)
- FinScope
What indicators exist?
Using the PivotTables, it is possible to explore the following indicators of coverage and prevalence:
- Proportion of individuals/households who have interacted with a SHG
- Proportion of individuals/households who have used an SHG for financial services
- Proportion of individuals who have received financial advice from a SHG
- Proportion of individuals who depend most on SHGs for financial advice
- Proportion of households in communities with at least one SHG
- Proportion of households in communities with access to multiple farmer cooperative groups
A data visualization summarizes the proportion of individuals/households who have interacted with a SHG or have used an SHG for financial services across the six countries, disaggregated by self-help group type and subpopulation.
EPAR also produced estimates for 29 indicators related to characteristics of SHG use, including indicators related to the frequency of SHG use, characteristics of SHG groups, and individual/household trust of SHGs. The project page includes a spreadsheet summarizing the construction decisions for each indicator.
Are data available by sub-population?
Where possible, we break these indicators down by: individuals who have access to a mobile phone; have official identification; are female; use mobile money; have a bank account; live in a rural area, and; their poverty quintile.
What do the data tell us?
Aggregate estimates of the nationally-representative sample indicators across countries suggest that Kenya has the greatest proportion of individuals interacting with and using financial services from SHGs (54.5% and 48.9% respectively). The SHG types with the most financial services usage in Kenya are Rotating Savings and Credit Associations (ROSCAs) (29.9%) and SACCOs (14.6%). Tanzania shows the smallest proportion of individuals interacting with and using financial services from SHGs (17.1% and 12% respectively).
Kenya has the most SHG types (9), followed by Uganda (8), Tanzania (5), Nigeria (4), and Rwanda (2). The SHG types with the most individual interaction in each country include ROSCAs in Kenya, burial societies in Uganda, cooperatives in Rwanda, merry-go-rounds in Nigeria, and savings groups in Tanzania.
Estimates at the household level were constructed using LSMS-ISA data for Ethiopia and Tanzania. The data indicate that about 45% of Ethiopian households had interacted with a SHG at the time of the survey compared to about 10% of Tanzanian households.
Why are the estimates different across tools?
A quick exploration of the data show that estimates can differ substantially between instruments. For example, estimates for the proportion of individuals who have interacted with a SHG in Kenya differ by more than 15% between FII and FinScope (42.6% and 58.66% respectively).
We attribute the differences between estimates to the way indicators are constructed across tools. There are differences in both the types of SHGs discussed in each tool, as well as the number of survey questions. For FII, this indicator is constructed from questions about whether respondents used a SHG for financial services, said they are a member of a SHG, report ever using a SHG, and/or report receiving advice from a SHG. Questions in FII reference cooperatives (unspecified), merry-go-rounds, and SACCOs.
For FinScope, this indicator is constructed from questions about whether respondents are a member of a savings group, used a SHG for financial services, report receiving advice from a SHG, and/or report using a savings/lending group to recover from a financial challenge. Questions in FinScope reference ASCAs, chamas, groups of friends, ROSCAs, SACCOs, savings groups, and self-help groups (unspecified).
Additionally, we used the most recent survey data available from each tool, which were typically collected in different years. For example, the most recent Kenya FinScope survey at the time of our analysis was administered in 2015 compared to the most recent FII data, which were collected in 2016. Therefore, some of the discrepancy in estimates may be attributable to temporal differences.
It is also important to note that FinScope surveys often differ substantially between countries and allow for more country-specific information. In contrast, the FII survey is consistent across countries, allowing for easier cross-country comparisons.
By Elan Ebeling and Melissa Howlett
Summarizing original EPAR data analysis by C. Leigh Anderson, Travis Reynolds, Pierre Biscaye, Kirby Callaway, Elan Ebeling, Annie Rose Favreau, Melissa Howlett, Daniel Lunchick-Seymour, Emily Morton, & Kels Phelps