Search results

Islamic banking and microfinance institutions (MFIs) share the core objective of serving the underprivileged. This study aims to investigate whether Islamic banking development facilitates (greases) or hinders (sands) the social mission of MFIs.

Data for 19 countries covering the period 2010–2018 were collected from the World Bank, Bank Focus and International Monetary Funds and analyzed using conventional econometric methods. Endogeneity-corrected techniques and alternative proxies were employed to ensure robust results.

The study revealed that Islamic banking development (proxied by the size of the Islamic banking assets) weakens the depth of outreach of MFIs (measured by average loan size). In countries with growing Islamic banking, MFIs appear to shift their focus toward wealthier clients, potentially due to market saturation among the poor. This is evidenced by MFIs offering larger loans, suggesting a mission drift toward profit maximization. Therefore, it can be inferred that competition from Islamic banks, to some extent, erodes the social mission of MFIs.

This study is among the few to examine the recent and comprehensive relationship between Islamic banking development and the social mission of MFIs.

Earlier studies on employee turnover have invested enormous scholarly mileage to understand and address human resource challenges. Considering the substantial evidence on the negative and non-linear relationship between employee turnover and firms’ performance, the purpose of this study is to investigate the effects of employee turnover on the social outreach (e.g. breadth of outreach) of microfinance institutions (MFIs), also known as the financial inclusion agenda of the Sustainable Development Goals.

To achieve the study objective, the authors collected unbalanced panel data of 1,391 MFIs, covering a total of 96 economies and a period of 2010–2018. The organizational and macroeconomic data were obtained from the World Bank’s Mix Market and World Development Indicators databases, respectively, and subsequently analysed using the pooled ordinary least squares, random effects model, fixed effects model and generalized method of moments.

Overall, the authors found that employee turnover has a positive impact on the social outreach of MFIs, which suggests that employee turnover reduces organizational blindness and groupthink, potentiates efficiency gains and minimizes retention costs. On the contrary, this study does not find evidence of a non-linear effect of employee turnover on the outreach objectives of MFIs. Meanwhile, these effects were observed to vary depending on the proxy, sub-samples and techniques used in the analysis.

Motivated by the paucity of literature, the study has uniquely investigated the effect of employee turnover on the social outreach objective of MFIs by using relatively recent and global-level data. The study findings can help managers and the human resource departments to make optimum decisions about employee turnover management.

Despite being a Muslim-dominated country, Bangladesh has widely embraced traditional microfinance since its inception in the mid-1970s. However, Islamic microfinance, which has a lot to offer to the poor, is still in its infancy and has yet to gain momentum in the country. Therefore, the purpose of this study is to analyze the importance of Islamic microfinance and propose alternative Shariah-compliant microfinance models in Bangladesh.

This study is based on the desk research method, which relies on existing literature to collect secondary data on key concerns of traditional microfinance programs. In addition, institutional-level secondary data were also collected from the Microcredit Regulatory Authority (MRA) of Bangladesh. Guided by the Maqasid-al-Shariah, this study then proposes several Islamic microfinance models to overcome selected challenges faced by the microfinance industry in Bangladesh.

This study suggested three composite Shariah-compliant microfinance models, which are likely to help the underprivileged and thus ensure the achievement of the sustainable development goals in Bangladesh. The first model explained how the operational strategy of incumbent microfinance institutions (MFIs) could be restructured, while the second proposed the organizational strategies for establishing a new MFI. The third model used the notion of Sadaqah (charity) to address the multiple borrowing issues of the industry. Meanwhile, the successful transformation of the conventional microfinance industry to an Islamic one is dependent on the effective collaboration between the regulatory authorities, practitioners and MFIs.

Albeit the paucity of literature on the topic, the findings of this study will guide policymakers/practitioners in designing relevant microfinance models to help transform conventional microfinance into Islamic microfinance in Bangladesh.

Though microfinance has been working for many years as a tool to eradicate poverty from its root, most of the least developed and developing countries are yet to significantly alleviate it from the society. The purpose of this paper is to focus on Shariah-based microfinance products in the context of sustainable poverty alleviation approach and provide them financial benefits to enhance their livelihoods.

Here, this qualitative study critically analyzes the basics of the sustainable Islamic microfinance to exterminate the level of poverty.

Islamic microfinance is a more ethical practice than the traditional motives of profit maximization, and it encourages extending the time of repayment if the debtors are in hardship. In some case, it suggests to give charity if the creditor has capability.

Most importantly, research scholars and experts have already criticized the concept of conventional microfinance on the basis of various points, especially for its high rate of interest.

Islamic microfinance is provided with a view to fulfill two tools simultaneously, i.e., social and financial inclusion. In this case, credits and Zakah can be given to the extreme poor people for satisfying basic needs. In terms of social responsibility, Islam encourages the people to be soft in case of collecting the lending money.

The study discoursed that sustainable Islamic Microfinance (IM) may be a promising future option to draw the attention of the religiously sensitive people toward the Shariah-based microfinance which can, in turn, mitigate the poverty level.

Measuring the success of microfinance institutions (MFIs) using a single efficiency value and then exploring its determining factors might be misleading. Hence, this study decomposed the efficiency measure into three divisions, namely operational, financial sustainability and social outreach. Subsequently, the authors identified factors affecting these efficiencies in the second stage regression analysis.

This study employed the network data envelopment analysis approach to evaluate each division of efficiency of 90 MFIs from 2013 to 2018 and used second-stage regression techniques (Tobit and Truncated) to examine the effect of institutional factors.

The authors’ efficiency analysis revealed that financial sustainability and social outreach were responsible for the low overall efficiency. The second stage analysis revealed the negative influence of institutional factors such as efficiency wage (particularly among small MFIs) on financial sustainability, social outreach and overall efficiencies. Staff turnover reduced operational, financial and overall efficiencies, particularly for large MFIs. The presence of female board members and staff improved the efficiency of MFIs, thus highlighting the pivotal role of women in the success of MFIs. Besides, the effects of regional location of MFIs, regulation and legal status on efficiencies were further discussed.

The study has uniquely evaluated three different types of efficiency in MFIs and employed conventional techniques for the second-stage regression to identify the determinants of efficiency. The findings will enable managers to make appropriate decisions to enhance their organisational efficiency.

Considering the existing evidence on the impact of female board members on the default risks of an organization, the purpose of this study is to investigate the effect of board gender diversity, alongside institutional characteristics and macroeconomic factors, on the financing costs of microfinance institutions (MFIs).

This study collected unbalanced panel data of 1,190 unique MFIs between 2010 and 2018 from the World Bank. The collected data, which covers a total of 95 developing and emerging countries, was thereafter analyzed using the pooled ordinary least squares and random effects model. To overcome endogeneity and omitted variable bias (e.g. time-invariant variables), the authors have also used the generalized method of moments and fixed effects model, respectively. Different proxies of board gender diversity and sub-sample analysis by regions were further undertaken to examine the robustness of the obtained results.

The findings of this study revealed that board gender diversity has a statistically significant negative effect on the financing costs of MFIs. This suggests that a gender-diverse board can generate cheaper funding for MFIs by minimizing their default risks through effective monitoring and strategic management. Furthermore, the negative impact of board gender diversity on financing costs appears to be more pronounced when there is a minimum of two female board members in the boardroom of MFIs. The results of this study remain consistent and valid regardless of alternate model specifications (e.g. sub-sample analysis, use of alternative proxies of board gender diversity and application of different estimators) and endogeneity issues. Ultimately, the findings in this study reiterate the importance of promoting and implementing gender diversity in the boardroom to minimize the financing costs of MFIs.

This study investigated the relationship between board gender diversity and financing costs of MFIs by using relatively recent and global data. The minimum number of female board members required to significantly reduce the financing costs of MFIs was also identified.

Given the growing emphasis among scholars, practitioners and policymakers on financial sustainability, this study aims to explore the applicability of machine learning techniques in predicting the financial performance of microfinance institutions (MFIs).

This study gathered 9,059 firm-year observations spanning from 2003 to 2018 from the World Bank's Mix Market database. To predict the financial performance of MFIs, the authors applied a range of machine learning regression approaches to both training and testing data sets. These included linear regression, partial least squares, linear regression with stepwise selection, elastic net, random forest, quantile random forest, Bayesian ridge regression, K-Nearest Neighbors and support vector regression. All models were implemented using Python.

The findings revealed the random forest model as the most suitable choice, outperforming the other models considered. The effectiveness of the random forest model varied depending on specific scenarios, particularly the balance between training and testing data set proportions. More importantly, the results identified operational self-sufficiency as the most critical factor influencing the financial performance of MFIs.

This study leveraged machine learning on a well-defined data set to identify the factors predicting the financial performance of MFIs. These insights offer valuable guidance for MFIs aiming to predict their long-term financial sustainability. Investors and donors can also use these findings to make informed decisions when selecting their potential recipients. Furthermore, practitioners and policymakers can use these findings to identify potential financial performance vulnerabilities.

This study stands out by using a global data set to investigate the best model for predicting the financial performance of MFIs, a relatively scarce subject in the existing microfinance literature. Moreover, it uses advanced machine learning techniques to gain a deeper understanding of the factors affecting the financial performance of MFIs.

Although microfinance had experienced rapid growth in most developing economies, multiple borrowing remains a growing concern for practitioners and researchers in recent years. Hence, the main purpose of the study is to evaluate the factors affecting multiple borrowing among microfinance clients.

The primary survey data of 400 microfinance clients from Bangladesh was collected to execute the research objective. Considering the types of dependent variable, this study employed logistics, probit, ordinary least squares (OLS) and Poisson regression techniques to analyze the data.

Among others, it was discovered that the expected (requested) loan amount is positively associated with multiple borrowing, while the level of training, small cattle farming business and marital status (widow/separated) exhibited negative effects under logistic regression. These results are robust with respect to the regression method, the specification and the definition of the outcome variable. Also, supply-side incentives (e.g. training) were found to partly influence the multiple-borrowing behavior of microfinance clients. These findings reiterate the contribution of both demand and supply-side factors to the multiple-borrowing behavior of clients. Consequently, policy implications and future research direction are advanced.

The authors have examined some individual-level characteristics as well as some supply-side incentives to better understand the underexplored issue of multiple-borrowing behavior among microfinance clients.

The purpose of this paper is to measure and track the evolution of market concentration and competition in the microfinance industry in Bangladesh by employing both the structural and non-structural measurement techniques.

By using a unique panel data set generated from the microcredit regulatory authority (MRA) annual reports, the sample includes 169 microfinance institutions (MFIs) and covers the period 2009-2014. The authors employed the Herfindahl-Hirschman index (HHI) and concentration ratio (CR) (largest 3, 8 and 20 MFIs) as structural measurement techniques and the Lerner index as a non-structural measurement technique. In addition, four different market indicators are used as representatives of deposit and credit markets to better explain the evolution of market concentration.

The results of HHI indicate that the sector is moderately concentrated and currently transitioning to an unconcentrated market. However, based on CR, the industry is still dominated by a few large MFIs. The Lerner index (non-structural approach) also confirmed that the level of competition is relatively high and likely to follow an inverted U-shape during the study period.

The findings of this study will enhance our understanding of the market structure in the Bangladesh’s microfinance industry so as to inform important policy prescriptions. The results also provide impetus to the relatively young MRA to nurture competition in the market; simultaneously, the findings prompt management of the MFIs to cope with a competitive market environment.

This study is one of the first of its kind that includes a large data sample of microfinance market for a single country by employing both structural and non-structural measurement approaches.

Digitalization is one of the major factors that fosters economic growth across the world. However, the level of digitalization varies significantly between developed and developing countries, with the latter often lagging behind. To bridge this gap, it is crucial to pinpoint the drivers of digitalization, specifically from the macroeconomic and country-level governance dimensions. Therefore, this study aims to investigate the determinants of digitalization, particularly for countries in Asia and the Pacific region.

Our study utilizes unbalanced panel data from 46 Asian and Pacific countries for the period of 2001–2021. Initially, we analyzed the data using conventional econometric methods, such as pooled ordinary least squares (POLS), random-effects model (REM) and fixed-effects model (FEM). Moreover, we employed endogeneity-corrected techniques and alternative proxies to enhance the robustness and reliability of our findings.

Our findings reveal that economic development progress, government expenditure relative to country size and political stability are key drivers of digitalization. In contrast, corruption at the country level emerges as a significant impediment. Notably, our results remain robust to endogeneity-corrected techniques and alternative proxies of digitalization. Overall, these insights can inform policymakers, helping them to understand the macroeconomic and governance factors shaping digitalization and guide their decision-making toward effective policy interventions.

This study’s empirical findings add significant value to the existing literature by quantifying the impact of macroeconomic and governance factors on digitalization in selected countries. This offers valuable insights for policymakers, particularly in nations with lower levels of digitalization.