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Predicting Multiple-Borrowing Default among Microfinance Clients

机译:预测小额信贷客户之间的多重借贷违约

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In order to control over-indebtedness that often leads to capacity failure, the Reserve Bank of India recently issued directives for Micro Finance Institutions to restrict multiple loans to borrowers. These institutions are also required to regularly share their current borrowers’ loan records with a Credit Information Company. We argue here that ex-post loan record verification is inefficient and inadequate considering the socio-economic and informational asymmetries in micro-credit markets. Instead, we reason, household characteristics can predict multiple-borrowing behaviour. Our empirical analysis shows that this is true to some extent. We dwell on policy implications and ways to improve our model.
机译:为了控制经常导致产能不足的过度负债,印度储备银行最近发布了针对微型金融机构的指令,以限制向借款人提供多笔贷款。还要求这些机构与信用信息公司定期共享其当前借款人的贷款记录。我们在这里认为,考虑到小额信贷市场中的社会经济和信息不对称性,事后贷款记录核查效率低下且不足。相反,我们认为,家庭特征可以预测多重借贷行为。我们的经验分析表明,这在一定程度上是正确的。我们专注于政策含义和改进模型的方法。

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