An Empirical Model of Subprime Mortgage Default From 2000 to 2007

Abstract

The turmoil that started with increased defaults in the subprime mortgage market has generated instability in the financial system around the world. To better understand the root causes of this financial instability, we quantify the relative importance of various drivers behind subprime borrowers' decision to default. In our econometric model, we allow borrowers to default either because doing so increases their lifetime wealth or because of short-term budget constraints, treating the decision as the outcome of a bivariate probit model with partial observability. We estimate our model using detailed loan-level data from LoanPerformance and the Case-Shiller home price index. According to our results, one main driver of default is the nationwide decrease in home prices. The decline in home prices caused many borrowers' outstanding mortgage liability to exceed their home value, and for these borrowers default can increase their wealth. Another important driver is deteriorating loan quality: The increase of borrowers with poor credit and high payment to income ratios elevates default rates in the subprime market. We discuss policy implications of our results. Our findings point to flaws in the securitization process that led to the current wave of defaults. Also, we use our model to evaluate alternative policies aimed at reducing the rate of default.

Mortgage Market Design

“…At higher levels of negative home equity, default rates increase and the di¤erence in …nancial distress between defaulters and non-defaulters disappears. Bajari et al (2008), Bhutta et al (2010), Elul et al (2010), and Foote et al (2008) …nd patterns consistent with these predictions in recent US data. Li et al (2010) argue that the reform of the US bankruptcy code in 2005 made it harder for borrowers to escape non-housing debt through bankruptcy; by tightening constraints on indebted borrowers, the bankruptcy reform decreased the trigger level of negative home equity and increased defaults in the late 2000s.…”

Современные Возможности Оценки Кредитного Риска При Ипотечном Жилищном Кредитовании

“…Первая попытка эмпирически протестировать валидность данных теорий при моделировании вероятности ипотечного дефолта американских заемщиков была предпринята Джексоном и Кассерманом [15]. Более поздние исследования, в основном по американскому ипотечному рынку, не оставляли попыток тестирования данных теорий [7,9,13,17] и позволили заключить о целесообразности использования обоих теорий для моделирования вероятности ипотечного дефолта. В эмпирической литературе находит подтверждение зависимость вероятности ипотечного дефолта от социально-демографических характеристик заемщиков, включая их уровень финансовой грамотности, параметров ипотечного кредита и макроэкономических показателей.…”

Using Housing Futures in Mortgage Research

“…Because of this difficulty, current empirical mortgage research either (1) does not include housing expectation proxies in empirical models (e.g., Demyanyk and Van Hemert, 2009), (2) uses past housing appreciation (e.g., Bajari et al, 2008), or (3) uses a time series forecast (e.g., Goetzmann et al, 2009) as the proxy.…”