Poverty Assessment and a Comparative Study of Rural Microfinance Institutions and Government Programmes in Ghana (ICPSR 35296)
Version Date: Aug 7, 2014 View help for published
Principal Investigator(s): View help for Principal Investigator(s)
Samuel Annim, University of Cape Coast (Ghana);
Kofi Awusabo-Asare, University of Cape Coast (Ghana);
Albert Abane, University of Cape Coast (Ghana);
Edwin Amonoo, University of Cape Coast (Ghana);
Isaac Acheampong, University of Cape Coast (Ghana)
Series:
https://doi.org/10.3886/ICPSR35296.v1
Version V1
Summary View help for Summary
This data collection assessed the delivery strategies of microfinance institutions (MFIs) in Ghana with the aim of identifying best practices to guide operations of the industry. The specific objectives of the study were to assess the socio-economic profiles of clients of selected MFIs and non-client households, assess the poverty levels of MFIs' client households in relation to the non-client sample, and to make recommendations for policy and planning with a view to strengthening the delivery of MFIs poverty-related programmes. Demographic information collected includes sex, age, education and health status of all household members, marital status, religion and occupation of adult household members aged 15 and above and ethnic group of household head. Other components of the study instrument were: footwear and clothing expenditure, food-related indicators, dwelling-related indicators, other asset-based indicators, and other living standards indicators.
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Subject Terms View help for Subject Terms
Geographic Coverage View help for Geographic Coverage
Smallest Geographic Unit View help for Smallest Geographic Unit
state
Distributor(s) View help for Distributor(s)
Study Purpose View help for Study Purpose
The purpose of the study was to assess delivery strategies of microfinance institutions in Ghana with the aim of identifying best practices to guide operations of the industry. Lessons learned were to be benchmarked against international practices with the view of sustaining and maximizing the returns of the identified delivery strategies of microfinance programmes. Also, given the plethora of microfinanc programmes, it is necessary to assess them in terms of depth of coverage that is, poverty levels of individuals, households and communities.
Study Design View help for Study Design
The data collection for the study was preceded by a reconnaissance survey to guide the selection of clients and non-clients. For this exercise, the country was zoned into coastal, middle and northern sectors and clients were selected from 17 micro-financing institutions in all the zones. The institutions were rural banks, financial non-governmental organizations, credit unions, a 'savings and loans' company and a susu group. Targeting clients who had received loans in the last six months or had been short-listed but yet to receive loans, people in 1,628 households were interviewed. In each of the institutions a minimum of 30 and a maximum of 160 clients were selected. For the selection of households of clients a two-stage sampling procedure was adopted. Initially, purposive sampling was used to select the number of clients by programme per institution, followed by a simple random sample for the selection of households. The minimum needed from each programme of a selected RMFI was 30 clients. Therefore, any programme with less than thirty new clients was ignored. For the rest, the following procedure was adopted: - A minimum of 30 clients from programmes with between 30 and 40 new clients. - 40 clients from programmes with between 41 and 100 new clients. - 60 clients from programmes with between 101 and 200 new - clients. - 80 clients from programmes with between 201 and 300 new clients. - 100 clients from programmes with between 301 and 400 new clients. - 120 clients from programmes with between 401 and 500 new clients. - 160 clients from programmes with 501 or more new clients. In addition, 1,104 households countrywide were selected based on a sample from the 2000 Census of Population and Housing as a control group. With the assistance of the Ghana Statistical Service, 70 enumeration areas (EA) were randomly selected from the three zones. Each selected EA consisted of 17 or 18 households, giving a potential sample size of between 1,190 and 1,260. The number of EAs selected from each zone and region were as follows: Northern Zone: (12): Northern: 7; Upper West: 2 and Upper East: 3. Middle Zone: (29): Ashanti : 12; Brong Ahafo: 7 and Eastern: 10. Coastal Zone:(29): Greater Accra: 10; Volta: 6; Central: 6 and Western: 7.
Sample View help for Sample
Purposive sampling technique was employed to sample microfinance institutions; random sampling technique was employed to sample clients and non-clients of microfinance institutions.
Time Method View help for Time Method
Universe View help for Universe
Clients and non-clients of microfinance institutions, and microfinance institutions.
Unit(s) of Observation View help for Unit(s) of Observation
Data Type(s) View help for Data Type(s)
Mode of Data Collection View help for Mode of Data Collection
Response Rates View help for Response Rates
91 percent
Presence of Common Scales View help for Presence of Common Scales
Microfinance Poverty Assessment Tool
HideOriginal Release Date View help for Original Release Date
2014-08-07
Version History View help for Version History
- Annim, Samuel, Kofi Awusabo-Asare, Albert Abane, Edwin Amonoo, and Isaac Acheampong. Poverty Assessment and a Comparative Study of Rural Microfinance Institutions and Government Programmes in Ghana. ICPSR35296-v1. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2014-08-07. http://doi.org/10.3886/ICPSR35296.v1
Notes
The public-use data files in this collection are available for access by the general public. Access does not require affiliation with an ICPSR member institution.
This study is provided by Centre for Data Archiving, Management, Analysis and Advocacy (C-DAMAA), a platform for collecting, processing, archiving, analyzing available data, and disseminating results for faculty and students at the University of Cape Coast in Ghana.