ABSTRACT

This paper develops a tool to predict the percentage of compliance in the repayment of microloans granted by non-profit microfinance institutions (MFI) of the Uruguayan government. The database consists of 1,357 microloans granted by the Program for the Strengthening of Productive Entrepreneurs (PFEP) of the Uruguayan Ministry of Social Development (MIDES) during the period 2012–2016. The paper uses Cox (1972) proportional risk model, employing four penalty modes: ENET, LASSO, AENET and ALASSO. The analysis shows that with a reduced set of variables that are easy for the MFI to obtain, it is possible to obtain high predictive power.

摘要

本文开发了一种工具来预测乌拉圭政府非营利性小额信贷机构 (MFI) 提供的小额贷款偿还中的合规百分比。该数据库包含 2012-2016 年期间乌拉圭社会发展部 (MIDES) 加强生产型企业家计划 (PFEP) 授予的 1,357 笔小额贷款。本文采用 Cox (1972) 比例风险模型，采用四种惩罚模式：ENET、LASSO、AENET 和 ALASSO。分析表明，通过减少 MFI 容易获得的变量集，就有可能获得高预测能力。