Estimation of Spillover Effects in Home Mortgage Delinquencies with Sampled Loan Performance Data

Hua Kiefer, Denghui Chen, Xiaodong Liu
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Abstract

This paper studies the spillover effect of home mortgage delinquencies using a discrete-choice spatial network model. In our empirical study, a main challenge in estimating this model is that mortgage repayment decisions can only be observed for a sample of all the borrowers in the study region. We show that the nested pseudolikelihood (NPL) algorithm can be readily modified to accommodate this missing data issue. Monte Carlo simulations indicate that the proposed estimator works well in finite samples and ignoring this issue leads to a downward bias in the estimated spillover effect. We estimate the model using data on single-family residential mortgage delinquencies in Clark County of Nevada in 2010, and find strong evidence of spillover effects. We also conduct some counterfactual experiments to illustrate the policy relevance of the spillover effect.
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基于样本贷款绩效数据的住房抵押贷款违约溢出效应估计
本文采用离散选择空间网络模型研究住房抵押贷款违约的溢出效应。在我们的实证研究中,估计该模型的一个主要挑战是,抵押贷款还款决策只能在研究区域的所有借款人的样本中观察到。我们表明,嵌套伪似然(NPL)算法可以很容易地修改,以适应这种缺失的数据问题。蒙特卡罗模拟表明,所提出的估计器在有限样本中工作良好,忽略这个问题会导致估计溢出效应的向下偏差。我们使用2010年内华达州克拉克县单户住宅抵押贷款拖欠的数据来估计该模型,并发现了溢出效应的有力证据。我们还进行了一些反事实实验来说明溢出效应的政策相关性。
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