Scope and Limitations of the Study

Studying the topic like microcredit, which requires multiple issues to be considered at a time, is challenging. Each of the methods used and its data collection process has limitations. These limitations are highlighted at the end of this thesis so that it can guide future research of similar kinds. It also portrays the scope of future research.

The first limitation is related to the case of BHB’s microcredit scheme. The program’s beneficiaries are handloom weavers whose credit requirements may differ from those of other non-agricultural occupations (e.g., rickshaw pulling, small business, and others). Therefore, the extent of credit impact estimated in this study can be regarded as more specific to the handloom sector in Bangladesh or other countries like India where this sector is prevalent. However, the finding may not be generalizable over all non-agricultural occupations.

In case of sample selection, the study classified the total samples into two groups as users and non-users of BHB’s credit from the same credit- implementing villages. However, such selection can cause potential bias due to the possibility of spillover effects. Even though many authors suggest controlling this spillover effect by selecting a control group from villages without the credit program, such selection can also raise some research problems. For example, if the study selects a sample from non-treated villages whose socioeconomic characteristics are not similar to the treated group, such selection also leads bias to the estimated impact. This might be the reason for those villages not to be included under the studied credit program. To address this issue, one could use a panel dataset. However, the study also acknowledges the limitation regarding the panel data because there is not any baseline survey on the microcredit program of BHB. Therefore, the over-time impact cannot be speculated from this analysis as the study used cross-sectional data. Even the use of methods such as propensity score matching or difference-in-differences cannot be applied in this study due to this limitation. Hence, one can conduct a follow-up longitudinal study to assess the long-term impact of BHB’s credit scheme.

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The impact of credit may differ at macro and intermediate levels due to changes in lending policies or lender’s ability. However, this analysis is limited to a micro level which considers the impact of credit to borrowers at the Sirajganj district only. Therefore, future research can be conducted at both macro and intermediate level involving the borrowers from 27 other basic centers of the studied case (i.e., BHB) to see the extent of impact.

For the credit information, there was a colossal mismatch of credit records between the the borrowers and the BHB’s officials. The borrowers were afraid of showing their passbook where the credit records were listed; one of the two study centers did not keep a complete record after 2013. Therefore, the researcher had to depend on the information recalled from the respondents’ memories. This incidence resulted in an estimation error of the credit amount in this study. However, the researcher technically asked the respondents how many times they received the credit, against how many handloom units in each time, and how much they have received per unit? Still, some of the information was missing that the researcher needed to adjust while analyzing. That is how the accuracy of the collected information has been ensured in this study.

The examination of governance challenges was a sensitive issue. Therefore, the KIs were very reluctant to provide information. Although the researcher promised to keep their identity secret, some of them still did not cooperate in verifying the accuracy of the collected information. Many even refused to record their responses or take photos. Due to this, the sample size for supply-side analysis was relatively small. Even though the small sample size is not the real issue for qualitative research, generalizing the findings regarding supply-side challenges may differ if it could have involved other KIs. One can check it through further research involving a larger sample size.

The PNM exercises were intended to know how the BHB’s credit program is implemented. However, the diagram prepared could not be verified by BHB’s central officials since it was not possible to ensure that they had sufficient time to examine all details that were revealed in the maps. Moreover, no clear documentation about the implementation process was also found in the project guideline. Therefore, understanding the implementing process depended on what the respondents knew about it.

During the data collection period, lending policies, such as increasing the loan volume, employee recruitment and other activities, were going through a revision. However, it was not approved by the government at the time. Therefore, those changes were not taken into account

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while drawing a conclusion. Through a shadow price analysis of credit, one can evaluate whether an increase in loan volume increases the borrowers’ outcome. Overall, we believe that acknowledging these limitations will guide future academic work in this area, but it appears reasonable to assume that the main findings and conclusions are nevertheless relevant and may guide policies, as further detailed below.