GROUP LENDING WITH HETEROGENEOUS TYPES
提出并估计了一个混合结构模型，用于分析团体贷款中未观测到的群体异质性对还款行为的影响，发现存在“负责任”和“不负责任”两类群体，且影响因素的作用因类型而异，模型在识别潜在违约者方面优于标准概率模型。
This paper proposes and implements a mixture structure to model repayment behavior in group lending with unobserved group heterogeneity. We discuss the model properties and identification and estimate the model using a rich dataset from a group lending program in India. The estimation results support the existence of two different group types: “responsible” and “irresponsible” groups. We find that the effects of the factors driving repayment behavior differ across types. The model also shows a higher predictive performance than standard probabilistic models, particularly in the identification of potential defaulters. We provide evidence supporting the robustness of our estimations.