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on Microfinance |
| By: | Varol İyidoğan, Pelin |
| Abstract: | The empowerment of women as a priority of economic development is a crucial issue for all economies, particularly for developing ones. Supporting employment is an inevitable aspect of women empowerment which enhances the socioeconomic conditions, nominately for the ones being a member of low-income households. As a developing country Turkey also tackles with the trouble of low labor force participation rate of women. More clearly, in 2018, the regarding rate was % 34 which is far more behind the developed economies. Furthermore, the rate of women entrepreneurship is low as well, that corresponds to around % 1.5 of employed women. Therefore, within the scope of gender equality, measures supporting the employment and entrepreneurship of women become the focus of economy and social policies. Regardingly, microcredit financing emerges as a policy solution for employment and other socio-economic struggle areas of women. In this context, this study aims to analyze the efficiency of microcredit schemes provided via Turkish Grameen Microfinance Program by employing a non-parametric approach, that is data envelopment analysis. The methodology enables to provide an efficiency ranking on the basis of input and output variables among the selected provinces of Turkey. The findings indicate that the microcredit programs in the East region of Turkey are implemented so as to ensure higher efficiency scores compared with others. |
| Keywords: | women employment, microcredit financing, data envelopment analysis |
| JEL: | C67 J16 J21 |
| Date: | 2019–10 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:102927&r=all |
| By: | Mirpourian, Mehrdad |
| Abstract: | Well-designed financial products improve the overall financial health of users. The design of products is particularly important for low-income customers, for whom product design drives behavior. In this paper, we offer insights on low-income customers’ savings behavior and on how they use their savings accounts. More specifically, we focus on detecting and measuring the effects of a set of explanatory variables on transaction amount. To do so, we use quantile regression (QR) and apply it to a novel dataset collected from a financial institution in Nigeria. The data show individual transactions made using the account over time, along with additional socioeconomic information on each customer. Using these data, we specify a model that incorporates customer age, account age, location, transaction type, gender, and seasonality effects, evaluating their correlation with transaction size. With the QR model, we are able to study the effect of the explanatory variables within each quantile of transaction amount instead of just showing trends on average. This is the first study to examine transaction size among low-income customers through a gender lens using QR. All of the variables incorporated in this model have a significant effect on transaction size. However, among all of the explanatory variables, the season in which a customer places a transaction (seasonality effect) has the largest impact on predicting transaction amounts. |
| Keywords: | Financial Inclusion, Behavioral Finance, Savings, Quantile Regression, Nigeria |
| JEL: | D01 |
| Date: | 2020–07–30 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:103062&r=all |