Mortgage Default during the U.S. Mortgage Crisis

Which theory can quantitatively explain the rise in mortgage defaults during the U.S. mortgage crisis? This paper finds that the double‐trigger hypothesis, which attributes mortgage default to the joint occurrence of negative equity and a life event such as unemployment, is consistent with the evidence. By contrast, a traditional frictionless default model strongly overpredicts the increase in default rates. This paper provides microfoundations for double‐trigger behavior in a model where unemployment causes liquidity problems for the borrower. This framework implies that mortgage crises may be mitigated at a lower cost by bailing out borrowers instead of lenders.     

Mortgage Default with Asymmetric Information

This article analyzes mortgage-market equilibrium when borrower default costs are private information. By applying the approach of Rothschild and Stiglitz (1976), it is shown that asymmetric information regarding default costs distorts the contract choices available in the mortgage market, preventing safe borrowers (those with high default costs) from fully satisfying their demand for mortgage debt. Large loans are available for a substantial interest-rate premium, but only risky borrowers find this premium worth paying. The article builds on an empirical literature designed to test the ruthless-default principle from option-based models of mortgage pricing. That literature provides evidence against ruthless behavior, suggesting that default costs play an important role in borrower decisions. The article takes a further step by arguing that such costs are private information, which has important implications for market equilibrium.     

Mortgage Default: Classification Trees Analysis

We apply the powerful, flexible, and computationally efficient nonparametric Classification and Regression Trees (CART) algorithm to analyze real estate mortgage data. CART is particularly appropriate for our data set because of its strengths in dealing with large data sets, high dimensionality, mixed data types, missing data, different relationships between variables in different parts of the measurement space, and outliers. Moreover, CART is intuitive and easy to interpret and implement. We discuss the pros and cons of CART in relation to traditional methods such as linear logistic regression, nonparametric additive logistic regression, discriminant analysis, partial least squares classification, and neural networks, with particular emphasis on real estate. We use CART to produce the first academic study of Israeli mortgage default data. We find that borrowers features, rather than mortgage contract features, are the strongest predictors of default if accepting icbadli borrowers is more costly than rejecting good ones. If the costs are equal, mortgage features are used as well. The higher (lower) the ratio of misclassification costs of bad risks versus good ones, the lower (higher) are the resulting misclassification rates of bad risks and the higher (lower) are the misclassification rates of good ones. This is consistent with real-world rejection of good risks in an attempt to avoid bad ones.     

House Price Markups and Mortgage Defaults

The transaction price of identical housing units can vary widely due to heterogeneity in buyer and seller preferences, matching, and search costs, generating what we term “markups” above or below the average market price. We measure markups for 3.4 million purchase-money mortgages and show that they can predict mortgage defaults and credit losses conditional on default even after accounting for collateral coverage (loan-to-value ratio) and a comprehensive set of other covariates. The findings suggest that standard collateral coverage estimation may be inaccurate, with implications for both individual and portfolio-level credit risk assessment.     

House‐Price Expectations,Alternative Mortgage Products,and Default

The goal of this paper is to better understand the forces that spurred use of alternative mortgages during the housing boom. A theoretical model shows that, when future house‐price expectations become more favorable, reducing default concerns, mortgage choices shift toward alternative products, which are characterized by backloading of payments. The empirical work confirms this prediction by showing that an increase in past house‐price appreciation, which captures more favorable expectations for the future, raises the market share of alternative mortgages. In addition, the paper tests the fundamental presumption that backloaded mortgages are more likely to default, finding support for this view.     

An Early Assessment of Residential Mortgage Performance in China

The residential mortgage market becomes a financial engine for the booming residential housing development and sustained economic growth in China. Our study provides the first rigorous empirical analysis on the earlier performance of residential mortgage market in China based on a unique micro dataset of mortgage loan history collected from a major residential mortgage lender in China. We found that while the option theory fails to explain prepayment and default behavior in the residential mortgage market in China, other non-option theory related financial economic factors play major roles in determining the prepayment and default risks in China. We also found that borrower’s characteristics are significant in determining prepayment behavior, hence may be used as an effective tool for screening potential high risk borrowers in the loan origination process. Adopting a risk-based pricing in residential mortgage lending in China can improve the efficiency of the market, and enhance the credit availability to the most needed households, i.e., the younger households, blue-collar workers, lower income households, and help them become homeowners.     

个人住房抵押贷款违约风险跃迁概率研究

巴塞尔新资本协议提出针对个人住房抵押贷款可采用内部评级高级法评估其风险,在满足某些最低条件和披露要求的前提下,商业银行可根据自己对个人住房抵押贷款违约概率、违约损失率、违约风险暴露和期限等要素的估计值确定相应的资本要求。本文提出将风险跃迁概率引入到对个人住房抵押贷款提前还款-违约概率的定量估计中。借助逻辑斯特模型,本文将这一概念实际运用到对个人住房抵押贷款微观数据的分析当中,得到的实证研究结论包括借款人历史还款状态可以作为表征其未来还款状态的重要指标,贷龄与借款人还款状态的跃迁概率显著相关等。     

Valuation of Residential Mortgage-Backed Securities with Default Risk Using an Intensity-Based Approach

This paper develops a valuation model for fixed-rate mortgages, mortgage pools, and residential mortgage-backed securities (RMBS's) using an intensity-based approach. This model incorporates full prepayment, partial prepayment, and default in valuing a mortgage. Full prepayment is further classified into “refinancing” and “sale of a house” depending on the reason. The time of occurrence of each of these three types of prepayment and default is modeled as the first jump time of a Cox process. Under these conditions, the valuation formula for a mortgage as well as a partial differential equation (PDE) that the mortgage value satisfies is provided. As for implementation of the model, the short-term riskless interest rate and the house price are adopted as state variables. Each intensity process is specified in a manner that allows a jump in intensity depending on the state variables and the borrower's incentive for prepayment or default. Through such specifications, it is shown that our model has characteristics similar to some structural models in previous literature. As for the numerical method for valuation, we propose a simple backward induction technique on a tree instead of the commonly used Monte Carlo method. Additionally, the method for estimating the model is discussed, and the results of numerical simulations are reported.This paper represents the view of the author and does note necessarily the views of the Mitsubishi UFJ Securities Co., Ltd. or members of its staff.     

The Effect of Mortgage Price and Default Risk on Mortgage Spreads

Variations over time in mortgage yield spreads should reflect changes in the underlying prepayment option value; moreover, the relationship between mortgage yield spreads and interest rate dynamics should weaken as the value of the borrowers prepayment option declines. We verify this hypothesis through an empirical analysis of residential mortgage yield spread behavior, and we also present evidence that the strength of the relationship between mortgage spreads and interest rate dynamics weakens (strengthens) as the level of default risk increases (decreases). This result is consistent with the competing risks effect between a borrowers option to prepay or default. Our results demonstrate the importance of accounting for mortgage price discount to par as well as default risk when developing time series of mortgage yields.     

Residential Mortgage Lending and Borrower Risk: The Relationship Between Mortgage Spreads and Individual Characteristics

The mortgage banking environment in Hong Kong is quite different from that in the United States. For example, the secondary mortgage market and mortgage insurance only started after 1997. Using a large data set on mortgages, we examine empirically how mortgage rates in this market vary with various individual borrower, property, and loan characteristics. We find that mortgage rates in Hong Kong do vary with individual characteristics, which suggests credit sorting according to both prepayment risk and default risk, as a higher mortgage rate is found to be related to either higher collateral (a lower loan-to-value ratio) or slower prepayment. The empirical results suggest that lenders in Hong Kong can observe the risk type of individual borrowers to a certain extent and charge a corresponding mortgage spread. Overall, the evidence is consistent with the sorting-by-observed-risk paradigm as in Berger and Udell (1990).     

Bias in an Empirical Approach to Determining Bond and Mortgage Risk Premiums

Empirical studies of bond and commercial mortgage performance often quantify a required risk premium by examining the difference between the promised yield and the realized yield as adjusted for default occurrence. These studies omit the effects of various other sources of risk, however, including collateral asset market risk, interest rate risk, and possibly call risk. These omissions downwardly bias the empirical risk premium estimate on the debt. In this paper, we disentangle and quantify the sources of this bias by modeling secured coupon debt (the commercial mortgage) as used in the calculation of a realized investment return. We consider deterministic and stochastic interest rate economies with mortgage contracts that are either noncallable or subject to a temporary prepayment lockout period. Given realistic parameter values associated with the term structure, underlying asset dynamics, and debt contracting, we show that the magnitude of the bias can be significant.     

Determinants of Mortgage Default and Consumer Credit Use: The Effects of Foreclosure Laws and Foreclosure Delays

The mortgage default decision is part of a complex household credit management problem. We examine how factors affecting mortgage default spill over to other credit markets. As home equity turns negative, homeowners default on mortgages and home equity lines of credit at higher rates, whereas they prioritize repaying credit cards and auto loans. Larger unused credit card limits intensify the preservation of credit cards over housing debt. Although mortgage nonrecourse statutes increase default on all types of housing debt, they reduce credit card defaults. Foreclosure delays increase default rates for housing and nonhousing debts. Our analysis highlights the interconnectedness of debt repayment decisions.     

Optimal Put Exercise: An Empirical Examination of Conditions for Mortgage Foreclosure

Implicit in option-pricing models of mortgage valuation are threshold levels of put-option value that must be crossed to induce borrower default. There has been little research into what these threshold values are that come out of pricing models or how they compare to exercised option values seen in empirical data. This study decomposes boundary conditions for optimal default exercise to look at the economic dynamics that should lead to optimal default timing. Empirical data on FHA insured mortgage foreclosures is then examined to discern the predictive influence of optimal-option-valuation-and-exercise variables on observed default timing and values. Interesting results include a new understanding of how to measure and use property equity variables during economic downturns, house-price index ranges over which default is exercised for various classes of borrowers, and implied differences in appreciation rates between market-price indices and foreclosed properties.     

Valuation of Mortgage Servicing Rights with Foreclosure Delay and Forbearance Allowed

We develop a bivariate binomial model to price Mortgage Servicing Rights (MSRs). Our model is an improvement over previous MSR pricing models by explicitly incorporating the realistic assumptions that there are additional costs involved in servicing delinquent loans. In addition to the Hilliard et al. mortgage-pricing tree, we extend additional sub-branches to model the borrower's decision of prepayment, cure, and foreclosure after a loan becomes delinquent. We then investigate how the value of the Mortgage Servicing Right varies with interest rate volatility, house price volatility, delinquency options, deficiency judgments, default penalties, forbearance periods, and speed of adjustments factors. JEL Classification: C15, G21     

Discrimination in Lending: Theory and Evidence

Using a general equilibrium model of credit market discrimination, I find that both taste-based discrimination and statistical discrimination have similar predictions for the intergroup differences in loan terms. The commonly held view has been that if taste-based discrimination exists, loans approved to minority borrowers will have higher expected profitability than those to majorities with comparable credit background. I show that the validity of this profitability view depends crucially on how expected loan profitability is measured. I also show that taste-based discrimination must exist if loans to minority borrowers have higher expected rates of return or lower expected rates of default loss than those to majorities with the same exogenous characteristics observed by lender at the time of loan originations. My analysis suggests that the valid method to test for taste-based discrimination should be reduced-form regressions. Empirically, I fail to find supporting evidence for the existence of taste-based discrimination.     

The changing fortunes of FHA's Mutual Mortgage Insurance Fund and the legislative response

The 1980s was a bad decade for FHA's Mutual Mortgage Insurance (MMI) program, the mainstay of FHA's single family mortgage insurance. While the MMI Fund is required by statute to be actuarially sound, the Fund lost close to $6 billion dollars, and its economic value declined from 5.3 percent of insurance in-force to under one percent. This study documents the decline in the soundness of the MMI Fund in the 1980s and describes the legislation enacted in October 1990 to shore up the Fund.     

Beyond the Transaction: Banks and Mortgage Default of Low‐Income Homebuyers

We evaluate the effects of the lending institution and soft information on mortgage loan performance for low‐income homebuyers. We find that even after controlling for the propensity of a borrower to get a loan from a local bank based on observable characteristics, those who receive a loan from a local bank branch are significantly less likely to become delinquent or default than other bank or nonbank borrowers, consistent with an unobserved information effect. These effects are most pronounced for loans originated to borrowers with marginal credit, where soft information may have a stronger effect. These findings support previous research on information‐driven lending, and provide additional explanation for observed differences in mortgage loan performance between bank and nonbank lenders.     

Expected Default Probabilities in Structural Models: Empirical Evidence

We apply a set of structural models (Black and Cox 1976; Collin-Dufresne and Goldstein 2001; Ericsson and Reneby 1998; Leland and Toft 1996; Longstaff and Schwartz 1995; Merton 1974) to estimate expected default probabilities (EDPs) for a sample of failed and non-failed UK real estate companies. Results are generally consistent with models’ predictions and estimates of EDPs for different models are closely clustered. The results of z-scores and synthetic ratings misclassify 33% of the total sample in contrast to 8% misclassification by structural models. Further analysis of EDPs based on logistic regressions suggests the observed misclassification of the companies by structural models is due to special company management and/or regulatory circumstances rather than limitations of these models.      

美国次级抵押贷款危机对银行业改进的启示

美国次贷危机促使银行业积极应对房地产周期性调整,改进风险管理框架,进一步加强表外关联机构管理,优化区域布局.美国次贷危机对于中国银行业的警示作用大于直接影响.中国商业银行应当认识到房价快速上涨会掩盖大量的风险,应当重视房地产周期性调整风险,尤其是房地产信贷业务的信用风险、操作风险、政策性风险以及突发性事件引发的系统性风险,谨慎推进金融工具创新,专注于核心业务增长,优化区域布局,提高中国银行业的整体经营水平及抵御国内经济周期的实力,完善金融监管协调机制.     

Competing Risks of Mortgage Termination: Who Refinances,Who Moves,and Who Defaults?

The Journal of Real Estate Finance and Economics - Why, when, and who terminates their mortgages? The primary reasons for mortgage termination are refinancing, selling of the property, and default....