【摘要】Empirical models of mortgage default typically find that the influence of unemployment is negligible compared to other well known risk factors such as high borrower leverage or low borrower FICO scores. This is at odds with theory, which assigns a critical role to unemployment in the decision to stop payment on a mortgage. We help reconcile this divergence by employing a novel empirical strategy involving simulated unemployment histories to measure the severity of attenuation bias in loan-level estimations of default risk due to a borrower becoming unemployed. Attenuation bias results because individual data on unemployment status is unobserved, requiring that a market-wide unemployment rate be used as a proxy. Attenuation is extreme, with our results suggesting that the use of an aggregate unemployment rate in lieu of actual borrower unemployment status results in default risk from a borrower becoming unemployed being underestimated by a factor more than 100. In addition, our analysis indicates that adding the unemployment rate as a proxy for the missing borrower-specific unemployment indicator does not improve the accuracy of the estimated model over the specification without the proxy variable included. Hence, aggregate portfolio-level risk estimates for mortgage guarantors such as FHA also are not improved.These views represent those of the authors and not necessarily those of the Federal Reserve Bank of New York or the Federal Reserve System. This is a revised version of a paper that previously circulated under the title “Unemployment and Unobserved Credit Risk in the FHA Single Family Mortgage Insurance Fund (NBER Working Paper No. 18880). John Grigsby provided excellent research assistance. We appreciate the helpful comments of Andrew Haughwout, Wilbert van der Klaauw, the editor (Stuart Rosenthal) and referees, but remain responsible for any errors.

【关键词】Mortgage default; Unemployment; FHA

【文献来源】Gyourko J;Tracy J.?.Journal of Urban Economics.2014