The research was undertaken in three stages: First, existing literature was reviewed to examine the theory and concept of microfinance and social performance. The theoretical analysis for the research derives primarily from the field of economics, sociology, organizational science, public administration and management. Second, empirical data were collected while the researcher was working with the AMK Research Department from March 2007 to June 2009. Quantitative data were collected from 2006 to 2008 while qualitative data were collected from 2007 to 2009. Third, ongoing social performance measurement initiatives in the private, NGO and microfinance sectors were evaluated in terms of: categories applicable across the microfinance industry; a MFIs capacity; and stakeholders’ requirements. The researcher had undergone training on some of the social performance tools.2
This chapter describes the research design and explains the sampling framework used in the cross-sectional and longitudinal research. Some of the indicators used in the empirical analysis are also explained at the end of this chapter.
3.1 Research design and empirical data
The empirical study is based on a cross-sectional and longitudinal survey collected from 2006 to 2008 in nine provinces of Cambodia where AMK operates (see Figure 3.1). The total sample of households in the data was collected in 55 randomly selected villages. Data were collected by a research team and not by loan officers to ensure unbiased answers from the respondents. The surveys used a detailed questionnaire (see Appendix A) to elicit information on social, economic, and demographic household characteristics which were useful in understanding correlates of poverty. Client profiling, loan use and client satisfaction inquiries were embedded in the questionnaire to capitalize on the research.
3.2 Sampling framework
One set of client and non-client households was surveyed in 2006 and another set in 2007 for the baseline survey. These data were used in the cross-sectional analysis as discussed in Chapter 4. Both 2006 and 2007 sets were revisited in
2
I took part in the USAID IRIS Poverty Assessment Tool Training (Phnom Penh, 2007), the World Bank /Asian Development Bank (ADB) Microfinance Training of Trainers (Phnom Penh, 2007), and the Microfinance Centre (MFC) Quality Audit Tool Training (Warsaw, 2009). I would like to thank the IRIS Center, World Bank, ADB and MFC for the support.
RESEARCH DESIGN AND SAMPLING FRAMEWORK
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2008 for the panel data. There were two points (round one and round two) at which data were collected from the same household. These data were used in Chapters 5 and 6. Table 3.1 presents an overview of the respondents as discussed below.
3.2.1 Round one - Baseline surveys in 2006 and 2007
For the baseline survey conducted in 2006, 450 households were randomly selected out of which 360 were AMK group clients (treatment group) and 90 were non-clients (control group) living in the same area as the clients. Fieldwork took place in five provinces where AMK operates: Banteay Meanchey, Battambang, Kampong Speu, Pursat and Siem Reap. Another set of households were visited in 2007 to increase the sample size of the panel data. 375 households were selected out of which 300 were AMK group clients and 75 were non-clients living in the same area as the clients. Sampling size was based on the growth of new AMK clients from 2006 to 2007. Fieldwork in 2007 then took place in nine randomly selected provinces where AMK operates: Banteay Meanchey, Battambang, Kampong Cham, Kampong Chhnang, Kampong Speu, Kampong Thom, Oddar Mean Chey, Pursat and Siem Reap.
For each baseline year, the survey employed a two-stage sampling method resulting in a self-weighting sample. The first stage of sampling used an equal-proportion method by which villages were randomly selected proportionate to the number of group clients in the provinces where AMK operates. A list of all clients in the selected villages was obtained from the Management Information Systems (MIS) department of AMK. 12 clients were selected from each of the chosen villages using a simple random sampling method on the village list. In each of the selected villages, three non-clients were randomly selected using a systematic random walk method. This method was implemented to avoid bias of spatial clustering in terms of economic status although a survey of the villages visited showed that there is no spatial clustering in terms of wealth in rural Cambodia (TORRES, 2009). The role of non-clients as control group was
important in identifying the social indicators and determining the different poverty groups. Data from this baseline survey were used to identify the variables or indicators used in the poverty index.
3.2.2 Round two – Survey in 2008
Client and non-client households surveyed in 2006 and 2007 were revisited in 2008 for the second round of data. Table 3.1 shows the distribution of respondents according to their client status by year and province. Figure 3.1
RESEARCH DESIGN AND SAMPLING FRAMEWORK 19
shows the areas of study. To allow for comparison over time, households were interviewed at the same time of the year as they were visited in round one. Respondents were asked the same questions as in round one with the same length of recall period.
The households that were considered to be part of the panel data have one of the following features: (1) the household in 2006 was fully intact in 2008 with the same person heading the household; (2) the household in 2007 was fully intact when revisited in 2008 with the same person heading the household; (3) the household head was the same for the two points at which data were collected, but all of the members of the household had not stayed together; and (4) the household head had changed but the rest of the household was intact. Unlike many impact studies, our panel data include client dropouts (households which are no longer clients). Those who dropped out are mostly wealthier clients who found no further need of the small loans.
The sampling technique faced threats of selection bias. There are two scenarios of selection bias problem in this type of research. The first scenario of selection bias involves missing information on the dependent variable in the part of the respondents. This happens when a sample consist of only clients. Non-client information is therefore missing. The second scenario is when information on the dependent variable is available for all respondents but the distribution of respondents over the independent variables are taken in a selective way (WINSHIP
& MARE, 1992). Inherent in group lending is the second scenario when groups
self-select the members. Different techniques, tests and models were applied as discussed in Chapters 5 and 6 to mitigate the problem.
Figure 3.1 Provincial Map of Cambodia Source:CANBY PUBLICATIONS CO.LTD., 2011
Table 3.1 Number of Household Respondents by Year and Province
Province 2006 2007
2008
2006 Set 2007 Set
Client Non-client Client Non-client Client Non-client Client Non-client
Banteay Meanchey 120 30 24 6 52 56 7 20 Battambang 24 6 36 9 15 10 24 11 Kampong Speu 84 21 24 6 51 33 14 15 Pursat 84 21 24 6 35 43 13 11 Siem Reap 48 12 48 12 14 29 20 23 Kampong Cham 60 15 43 16 Kampong Chhnang 12 3 5 6 Kampon Thom 48 12 29 22
Oddar Mean Chey 24 6 7 17
Total 360 90 300 75 167 171 162 141
SOCIAL PERFORMANCE OF MICROFINANCE INSTITUTIONS 23