The effect of corruption on microfinance loan portfolio: A semiparametric analysis

IF 1 4区经济学 Q3 ECONOMICS

Economics of Transition and Institutional Change Pub Date : 2022-05-23 DOI:10.1111/ecot.12332

Jeleta Kebede, Vincent Tawiah, Ernest Gyapong

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Abstract

In this paper, we examine the extent to which corruption affects the loan portfolio of microfinance institutions (MFIs). We employ robust econometric estimation on a sample of 507 MFIs across 63 countries from 2005 to 2018. Our results show that corruption is negatively associated with the loan portfolio. However, in semiparametric analysis, we find that lower-level corruption is beneficial to increase the loan portfolio while higher-level corruption is detrimental. The results imply that it is not just corruption that matters as far as its effect on MFIs' loan portfolio is concerned; what matters is the degree of corruption. In further analyses, we find that corruption reduces both the number of active borrowers and average loan per borrower indicating that corruption reduces both coverage and amount of credit extension. The results suggest that the effect of corruption on the loan portfolio is gender-sensitive. Corruption facilitates an increase in loans to female borrowers. Our results are robust to alternative variable measurements and different identification strategies, including two-stage least square.

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腐败对小额信贷组合的影响：半参数分析

在本文中，我们研究了腐败对小额信贷机构(mfi)贷款组合的影响程度。我们对2005年至2018年63个国家的507家小额信贷机构样本进行了稳健的计量经济学估计。我们的研究结果表明，腐败与贷款组合负相关。然而，在半参数分析中，我们发现低级别腐败有利于增加贷款组合，而高级别腐败则不利于增加贷款组合。结果表明，就其对小额信贷机构贷款组合的影响而言，不仅仅是腐败问题;重要的是腐败的程度。在进一步的分析中，我们发现腐败减少了活跃借款人的数量和每个借款人的平均贷款，这表明腐败减少了信贷的覆盖范围和数量。结果表明，腐败对贷款组合的影响具有性别敏感性。腐败助长了女性借贷者贷款的增加。我们的结果是稳健的替代变量测量和不同的识别策略，包括两阶段最小二乘法。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Economics of Transition and Institutional Change ECONOMICS-

CiteScore

1.70

自引率

11.10%

发文量