 Estimation of discrete choice network models with missing outcome dataDenghui Chen, Hua Kiefer and Xiaodong Liu Regional Science and Urban Economics, 2022, vol. 97, issue C Abstract: This paper considers the problem of missing observations on the outcome variable in a discrete choice network model. The research question is motivated by an empirical study of the spillover effect of home mortgage delinquencies, where mortgage repayment decisions can only be observed for a sample of all the borrowers in the study region. We show that the nested pseudo-likelihood (NPL) algorithm can be readily modified to address this missing data problem. Monte Carlo simulations indicate that the proposed estimator works well in finite samples and ignoring this issue leads to a severe downward bias in the estimated spillover effect. We apply the proposed estimation procedure to study single-family residential mortgage delinquency decisions in Clark County of Nevada in 2010, and find strong evidence of the spillover effect. We also conduct some counterfactual experiments to illustrate the importance of consistently estimating the spillover effect in policy evaluation. Keywords: Missing data; Mortgage defaults; Networks; NPL; Rational expectation (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:regeco:v:97:y:2022:i:c:s0166046222000734 DOI: 10.1016/j.regsciurbeco.2022.103835 Access Statistics for this article Regional Science and Urban Economics is currently edited by D.P McMillen and Y. Zenou More articles in Regional Science and Urban Economics from Elsevier |
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