Abstract
This study focuses on the impact of asset size on financial performance and outreach. More specifically, we determine whether an increase in asset size is more relevant for microfinance institutions with low performance than for those with high performance. To achieve this goal, we applied a panel quantile approach with non-additive fixed effects that helps to organize our microfinance sample into subgroups with similar performance levels. The results reveal that an increase in asset size leads to increased profitability, with a greater impact for microfinance institutions that have poor or low-end profitability levels than for those with satisfactory levels. For outreach, we found that an increase in asset size positively impacts the average loan and the number of active borrowers, but reduces the percentage of female borrowers in the client portfolio. An increase in asset size reduces the percentage of female borrowers more for MFIs that target women less. Conversely, for MFIs that already have a high level of female borrowers, an increase in asset size reduces the percentage of female borrowers less. In other words, increasing asset size drives out female borrowers from the client portfolio, and this driving-out effect is greater for MFIs targeting fewer female borrowers.
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Notes
Financial development is measured as the domestic credit provided by the financial sector including all credits to various sectors.
In this study, we use the logarithm of GDP per capita, or gross domestic product, divided by midyear population.
In this study, we use the logarithmic value of the total remittances received divided by gross national income per capita in constant 2005 US dollars (lnremirec). Remittances include personal transfers and compensation of employees.
This represents aid flows (net of repayments) from official donors to countries and territories. Official aid is provided under terms and conditions similar to those for official development assistance (ODA). Data on official aid and other sources are in constant 2012 US dollars. In this study, we use the log value (lnaid).
A basic quantile analysis was developed by Koenker and Bassett (1978) and improved by Abadie et al. (2002) and Frölich and Melly (2010). Their improvements solved the limits observed on the standard errors of Koenker and Bassett (1978), which were not consistent in the presence of heteroscedasticity and led to biased quantile regression estimators in this case.
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Acknowledgments
The views expressed in this paper are those of the authors, and not necessarily those of AERC, or the University Catholic of Lille. We are grateful for the help group designed by AERC to be referees of research papers in banking and finance. Thanks to Pr. Victor MURINDE (SOAS University); Pr. Robert LENSINK (Groningen University); Pr. Issouf SOUMARE (Laval University); Pr. Christopher GREEN (Loughborough University); Pr. Machiko NISSANKE (University of London); Pr. Bo SJÖ (Linköping University), and all the research members for comments on the paper. We thank Nancy MURIUKI and Sheila LYAGA for excellent research assistance. We are also grateful to all the research heads and to the Social Business Chair, related research members and employees of University Catholic of Lille.
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AERC Research funds. Grant ref: RT17505.
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DEF and GHI performed the experiments, analysed the data and wrote the manuscript.
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Kendo, S., Tchakounte, J. Impact of asset size on performance and outreach using panel quantile regression with non-additive fixed effects. Empir Econ 62, 65–92 (2022). https://doi.org/10.1007/s00181-021-02057-9
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DOI: https://doi.org/10.1007/s00181-021-02057-9