Should gender be a determinant factor for granting crowdfunded microloans?

This study examines the impact of gender on crowdfunded microloans, motivated by the increased empowerment of women in developing countries and the rise of microloans as a poverty reduction tool. The research uses a sample of microloans from Kiva, a global crowdfunding platform, to analyze the relationship between borrower gender and key loan characteristics. The context is particularly relevant given the focus on Sustainable Development Goals (SDGs) and the increasing use of crowdfunding in microfinance. Crowdfunding platforms offer a unique opportunity to connect micro-borrowers with a large number of individual lenders, potentially improving access to finance and reducing information asymmetries. The study investigates how the gender of the borrower might affect the amount, term, number of lenders, repayment system, and the time to secure funding for a given microloan. Microfinance, initially pioneered in Bangladesh, has spread globally, particularly benefiting women in developing countries and small and medium-sized enterprises (SMEs). This study builds on existing literature on group lending, crowdfunding, and the intersection of both with gender dynamics. The study seeks to determine if gender is a significant factor when analyzing the quality of crowdfunded microloans and its repayment rates. This will provide valuable insights for Microfinance Institutions (MFIs) and policymakers aiming to promote financial inclusion and sustainable development.

The study reviews existing literature on microfinance, crowdfunding, and their intersection, specifically focusing on gender. Microfinance literature extensively covers group lending practices and their impact on poverty reduction. Extensive research has been conducted on crowdfunding mechanisms, its various models (reward-based, donation-based, equity-based), and its role in supporting entrepreneurship. Existing studies on the overlap between microfinance and crowdfunding analyze how crowdfunding can enhance access to finance for micro-borrowers, particularly for women. Relevant research examines gender inequality in access to finance, highlighting how women often face greater barriers than men. Studies exploring the gendered impact of microfinance show that women borrowers often demonstrate better repayment rates compared to men. This literature further examines risk-averse behaviors among women and how this affects the success of microfinance initiatives. Recent research has explored the gender dynamics within crowdfunding campaigns for SMEs, revealing that companies with a balanced gender representation on their boards often have improved funding success. This review concludes that while microfinance has a proven success record in empowering women, there's a need to examine the specific context of crowdfunded microloans and if gender preferences exist among crowd-investors.

The study employs multinomial logit regression to analyze the relationship between borrower gender and five key microloan characteristics. The dependent variable is borrower gender (male, female, mixed group), while the independent variables include loan amount, loan term, number of lenders, repayment system (monthly, bullet, irregular), and lender recruitment period. The data comes from a sample of 385 microloans selected through simple random sampling from a larger Kiva database (1,048,575 microloans disbursed between July 25, 2007, and June 30, 2020). The sample represents microloans from 56 countries across various sectors. The multinomial logit model was chosen because the dependent variable has more than two categories. The model estimates the probability of each gender category (male, female, mixed) given the values of the independent variables. The model’s parameters are estimated using maximum likelihood estimation. Goodness-of-fit tests were conducted to assess the model's performance. Before finalizing the model, the authors checked assumptions such as linearity of independent variables, influential points, and multicollinearity. The results present the coefficients for each independent variable and their statistical significance, indicating how they affect the probability of a loan being given to a borrower of a particular gender category.

The multinomial logit regression analysis revealed that loan amount (X1), repayment system (X4), and lender recruitment period (X5) are significant predictors of borrower gender. Specifically, a higher loan amount increases the likelihood of the borrower being female. A more reliable repayment system (monthly or bullet) increases the probability of the borrower being male or a mixed group. A shorter lender recruitment period also increases the probability of the borrower being male or a mixed group. The loan term (X2) and number of lenders (X3) were not significant predictors. The overall model shows a good fit to the data, with the likelihood ratio test rejecting the null hypothesis that all coefficients are zero. These findings suggest that women are better borrowers in terms of loan amounts, repayment reliability, and speed of funding. Although, some variables are insignificant, it might be due to the correlation between them. For instance, loan amounts and the number of lenders are highly correlated. The study shows that when considering the loan amount, repayment method, and recruitment period, women consistently demonstrate to be the best borrowers.

The findings confirm the existing literature on women's superior repayment rates in microfinance, extending it to the crowdfunded microloan context. The significance of loan amount, repayment system, and lender recruitment period suggests that women borrowers attract larger loans, exhibit higher repayment reliability, and secure funding more quickly. The results reinforce the potential of crowdfunded microloans as a tool for female empowerment, highlighting the importance of gender considerations in microfinance initiatives. The findings suggest that policies and platforms supporting crowdfunded microloans should actively seek to improve access for women borrowers, who demonstrate a strong track record of repayment and efficient utilization of funds. This research offers evidence that contradicts some prevailing misconceptions about women's creditworthiness and the effectiveness of targeting female entrepreneurs through crowdfunded microfinance. The study's findings are valuable for MFIs, policymakers, and crowdfunding platforms, offering evidence-based insights for improving financial inclusion strategies.

This study demonstrates that women are better borrowers when considering several key microloan characteristics. The findings highlight the potential of crowdfunded microloans for women's empowerment and financial inclusion. Future research could explore the reasons behind these differences, investigate the role of specific cultural contexts, and analyze the effectiveness of various outreach strategies targeting women borrowers. Further investigations could also focus on exploring the relationship between “green and pink” microfinance strategies and their ability to attract more ESG-compliant crowdfunding resources.

The study's reliance on Kiva data, which might not fully represent all crowdfunded microloan platforms, limits the generalizability of the findings. The lack of data on loan defaults limits the analysis. The sample size, while substantial, might not fully capture the diversity of contexts in which crowdfunded microloans operate. The correlation between loan amount and number of lenders might have influenced the insignificance of the latter variable in the analysis.