Abstract

1. Discrimination in microfinance: the effect on loan amount receivedDiana AlhindawiSIS 600.002, American University4400 Massachusetts Avenue NW, Washington DC 20016da6906b@american.edu Abstract Microfinance primarily aims to alleviate poverty in developing countries. This aim is best achieved if fair access to credit is ensured to all creditworthy candidates. What little study of discrimination in microcredit has been undertaken has usually assessed loan approval outcome; very few studies have investigated discrimination by assessing the size of the loan obtained. The current study therefore utilizes discrimination-in-lending methodology to investigate the presence of discrimination in microcredit as it manifests in the size of the loan received by an applicant. Cross-sectional household data from the Matlab [Bangladesh] Health and Socioeconomic Survey (MHSS), 1996, administered in the Matlab region of Bangladesh, is used to estimate the relationship between loan amount and factors of discrimination – gender, marital status, religion and education – controlling for age, collateral and loan duration, three factors normally used to assess credit worthiness. Findings suggest that discrimination does not affect loan amount. However, the putting up collateral for the loan and the duration of loan repayment both increase loan amount. Microfinance organizations are encouraged to accept non-traditional forms of collateral so as to ensure fair loan size to all recipients.

2. Research Question:Did discrimination along gender, marital status, religion, and/or education lead to discrepancies in loan amount obtained by a microfinance recipient in the Matlab region of Bangladesh prior to 1996? Significance of study: The effectiveness of microfinance programs can be compromised by limited or unfair access to applicants. Few studies have investigated the presence of discrimination in microfinance, ad these have focused on the role of discrimination in determining access to loans, but not in determining the size of the loan obtained. The current study therefore utilizes discrimination-in-lending methodology to investigate the presence of discrimination in microcredit as it manifests in the size of the loan received by an applicant. The current study therefore investigates the effect on loan amount of factors of discrimination(gender, marital status, religion and education) controlling for factors normally used to determine credit worthiness (age, collateral and loan duration).

3. Literature Review Abaru, Biruma M., Mugera, Amin W., Norman, David W. and Allen M. Featherstone(2006). The Uganda Rural Farmers Scheme: Women’s Accessibility to Agricultural Credit. Agricultural Finance Review 66(2), 215-234. • Used a multiple regression model to study the effect of various borrower characteristics on the loan amount disbursed to an applicant, as well as on loan approval, loan repayment, and credit rationing • Conclusion:Women displayed a higher loan approval rate and loan repaid/loan borrowed ratio than men, but lower actual disbursement levels. Agier, Isabelle and ArianeSzafarz (2010). Microfinance and Gender: Is there a glass ceiling in loan size? Available at SSRN: http://ssrn.com/abstract=1573872 • Employed a discrimination-in-lending methodology to study gender discrimination in the microfinance industry by looking at the effect on loan size • Conclusion: Detected no discriminatory practice in the approval rate faced by women, but did uncover unfair loan size.

4. Model Theory: Discrimination-in-lending methodology will be applied to study discrimination according to various factors, controlling for factors that determine credit worthiness. Model: la = 0 + 1gen + 2ms + 3rel + 4educ + 5age + 6col + 7dur + ut; where: la = loan amount, gen = recipient’s gender, age = recipient’s age, ms = recipient’s marital status, rel = recipient’s religion, educ = highest level of education in the household, col = the existence of collateral put up for the loan, and dur = duration allowed to pay back the loan. Hypothesis: • Coefficients 1, 2, 3, 4, 5, and 6 are expected to be positive, indicating greater loan amount for recipient who are male, married, practice Islam, educated at a higher level, older, and able to put up collateral for a loan, respectively. • Coefficient 7is expected to be negative, indicating that loan amount decreases as the duration to pay back a loan increases.

5. Data Source: Matlab[Bangladesh] Health and Socioeconomic Survey (MHSS), 1996, accessed through University of Michigan’s ICPSR database.

6. Descriptive Statistics Gender: Collateral Marital Status: Religion:

7. Bivariate Analysis Pearson’s r: Variable age _ La0.003 (0.956) Estimates significant at the 5% level are in boldface, p-values in parentheses. Estimates significant at the 10% level are in boldface and italics.

8. Estimates / Findings Model (1) (2) (3) . Intercept 3762.832 5409.354 3531.538 (0.083) (.000)(.143) gen -827.782 -672.702 -570.146 (.216) (.177) (.392) ms-118.926 484.406 957.724 (.866) (.486) (.345) rel2709.858 - 1688.734 (.212) (.463) educ4.932 - -1.983 (.776) (.914) age --22.234 -44.638 (.186) (.120) col - 2383.489 3052.068 (.000)(.000) dur - 222.187 330.999 (.053) (.028) N 288483 283 Adjusted R2-0.004 0.0390.064 Estimates significant at the 5% level are in boldface, p-values in parentheses. Estimates significant at the 10% level are in boldface and italics. *No heteroskedasticity or collinearity (VIF < 5) in Model 1, 2 or 3

9. Conclusions Estimated coefficients for gender, marital status, religion and education were not statistically significant at the 10% level in any of the three models • in the Bangladeshi context, discrimination according to these 4 factors does not affect a microfinance recipient’s loan amount Estimated coefficients for collateral and loan duration were significant in Model 3 • putting up collateral for the loan and loan duration, both factors that determine creditworthiness, increase loan amount Policy Recommendation: Microfinance providers should expand the boundaries of what they accept as collateral, so that fair access to loans be improved and recipients who do not own traditional forms of collateral may receive larger loans.