Enabling microenterprise development in Sub-Saharan Africa through the provision of financial services
Most people in rural Africa do not have bank accounts. In this paper, we combine experimental and survey evidence from Western Kenya to document some of the supply and demand factors behind such low levels of financial inclusion. Our experiment had two parts. In the first part, we waived the fixed cost of opening a basic savings account at a local bank for a random subset of individuals who were initially unbanked. While 63% of people opened an account, only 18% actively used it. Survey evidence suggests that the main reasons people did not begin saving in their bank accounts are that: (1) they do not trust the bank, (2) service is unreliable, and (3) withdrawal fees are prohibitively expensive. In the second part of the experiment, we provided information on local credit options and lowered the eligibility requirements for an initial small loan. Within the following 6 months, only 3% of people initiated the loan application process. Survey evidence suggests that people do not borrow because they do not want to risk losing their collateral. These results suggest that, while simply expanding access to banking services (for instance by lowering account opening fees) will benefit a minority, broader success may be unobtainable unless the quality of services is simultaneously improved. There are also challenges on the demand side, however. More work needs to be done to understand what savings and credit products are best suited for the majority of rural households.
“The data sits under “”Additional Materials””. It consists of Stata data and do-files, and a ReadMe. The data comes from data collected by the authors in and around Bumala Town in Busia Disctrict, Western Kenya. The data was collected in three waves. Details on the sampling strategy and timing of the data collection can be found in the final manuscript. It includes 2 datasets, both in Stata format: (1) dataset_savingsAEJ.dta. This is the main dataset used in the analysis. This merges the three data sources listed above. All the substantial analysis in the paper uses this dataset. (2) sampling_frame.dta. This dataset includes background information for the entire sample of individuals initially sampled for the study, and the reasons why they could not be included in the study. This dataset is used to generate Appendix Table A1.
Do-File: The analysis was done in Stata 11 SE. The do-file named savingsAEJ.do produces all the results in the paper and the appendix. All results are clearly commented in the do-file with the Table number to which they refer. The file makes use of the Stata ado program “outreg”, which is available for free download from Stata (just type “ssc install outreg” in the command bar).”