Appraisal Quality and Residential Mortgage Default: Evidence from Alaska

We empirically examine the effect of appraisal quality on subsequent mortgage loan performance using data from the high volatility housing market of Alaska in the 1980s. We develop measures of appraisal quality by computing the residual between a hedonic estimate of house value using available information from other appraisals compared to actual ex ante appraised value. We then estimate proportional hazard models of mortgage default and find that several measures of appraisal quality, particularly appraised value in excess of hedonic estimates, are significantly related to default risk. Using valuations subsequent to loan default, we are also able to evaluate how well house price indices perform in terms of estimating current loan-to-value and offer some additional evidence on the controversy over the role of net equity versus trigger events as determinants of mortgage default. We also show that defaults are related to ex ante measures of housing market conditions, with additional implications for underwriting policies and the current industry trend away from traditional appraisal and toward automated valuation.     

Characteristics of Mortgage Terminations: an Analysis of a Loan-Level Dataset

Understanding mortgage termination behavior is crucial for valuating mortgage-backed securities. Analyzing a unique loan-level dataset, this study examines the characteristics of mortgage prepayment and default behaviors in the Korean housing and housing finance markets. We also analyze mortgage termination behaviors across regions, loan purposes, and periods. The results suggest that the prepayment rate of fixed-rate mortgages (FRMs) and the ratio of adjustable-rate mortgages to FRMs can provide meaningful signals for the Korean household economy. Although the macro-prudential policies pertaining to the loan-to-value ratio (LTV) and debt-to-income ratio (DTI) are very effective, their effects can vary depending on the region or loan purpose. Furthermore, the DTI and credit score cannot always identify the default risks of mortgages not intended for housing purchases even though such mortgages are more vulnerable to macroeconomic changes. The observed changes in default behavior indicate that the government’s policies to promote fixed-rate loans have achieved a certain degree of success.     

Bias in estimates of discrimination and default in mortgage lending: The effects of simultaneity and self-selection

The common practices of estimating single-equation models of mortgage rejection to test for discrimination in mortgage markets or single-equation ex ante mortgage default equations to validate underwriting criteria produce biased and inconsistent parameter estimates. This is due to problems of simultaneous equations bias which arise because, in a world of imperfect information, mortgage terms are not exogenous to the rejection or default decision. In addition, mortgage default estimates are also subject to selection bias. Monte Carlo experiments are used to study the nature and extent of likely bias in single-equation estimation results. We find that rejection equation estimates indicate discrimination when none exists and that estimated coefficients of mortgage terms, such as the loan-to-value ratio, are also subject to significant bias in both rejection and default equations.     

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.     

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.     

Predatory lending and the subprime crisis

We measure the effect of a 2006 antipredatory pilot program in Chicago on mortgage default rates to test whether predatory lending was a key element in fueling the subprime crisis. Under the program, risky borrowers or risky mortgage contracts or both triggered review sessions by housing counselors who shared their findings with the state regulator. The pilot program cut market activity in half, largely through the exit of lenders specializing in risky loans and through a decline in the share of subprime borrowers. Our results suggest that predatory lending practices contributed to high mortgage default rates among subprime borrowers, raising them by about a third.     

A Proportional Hazards Model of Commercial Mortgage Default with Originator Bias

A proportional hazards model with competing risks is specified and is extended to correct for the possibility of originator bias. The model is used to examine the ability of option-theoretic models of mortgage pricing to forecast commercial mortgage defaults. Among the findings, those especially of interest include the influence of contemporaneous loan-to-value and debt-service-coverage ratios on commercial mortgage default probabilities. The paper also finds that option-theoretic models of mortgage pricing are quite capable of producing default estimates that fit the actual default rates well, especially when the model is corrected for originator bias.     

SECONDARY MORTGAGE MARKET PURCHASE COMMITMENT YIELDS

We provide empirical evidence that quoted secondary market mortgage yields conform to the predictions of option theory. We compare Fannie Mae and Freddie Mac origination yields offered in the secondary market from 1985 to 2003 with the predictions of a two‐state binomial mortgage option valuation model. Our two‐state approach considers a mean‐reverting interest rate process as well as a stochastic housing price. Using predictions from option simulations, we find strong links between market practice and mortgage option prepayment and default factors over time. We also find cross‐sectional differences that are consistent with the institutional structure of the markets.     

Two Extensive Margins of Credit and Loan‐to‐Value Policies

We analyze a model of mortgage markets, housing tenure choice, heterogeneous agents, and default with closed form solutions. We uncover new insights which may inspire empirical work, and we ground already established insights in a series of tractable expressions. Then we study optimal loan‐to‐value (LTV) regulation and show that the choice of an LTV cap should balance the opposing forces of access to homeownership and the negative externalities associated with default. Homeownership affordability concerns induce procyclical elements into optimal regulation which attenuate the countercyclical regulation justified by the negative default externalities.     

The impact of macroprudential housing finance tools in canada

This paper combines loan-level administrative data with household-level survey data to analyze the impact of recent macroprudential policy changes in Canada using a microsimulation model of mortgage demand of first-time homebuyers. Policies targeting the loan-to-value ratio are found to have a larger impact on demand than policies targeting the debt-service ratio, such as amortization. In addition, we show that loan-to-value policies have a larger role to play in reducing default than income-based policies.     

A model of mortgage losses and its applications for macroprudential instruments

We develop a theoretical model of mortgage loss rates that evaluates their main underlying risk factors. Following the model, loss rates are positively influenced by the house price level, the loan-to-value of mortgages, interest rates, and the unemployment rate. They are negatively influenced by the growth of house prices and the income level. The calibration of the model for the US and Switzerland demonstrates that it is able to describe the overall development of actual mortgage loss rates. In addition, we show potential applications of the model for different macroprudential instruments: stress tests, countercyclical buffer, and setting risk weights for mortgages with different loan-to-value and loan-to-income ratios.     

Improvements in loss given default forecasts for bank loans

An accurate forecast of the parameter loss given default (LGD) of loans plays a crucial role for risk-based decision making by banks. We theoretically analyze problems arising when forecasting LGDs of bank loans that lead to inconsistent estimates and a low predictive power. We present several improvements for LGD estimates, considering length-biased sampling, different loan characteristics depending on the type of default end, and different information sets according to the default status. We empirically demonstrate the capability of our proposals based on a data set of 69,985 defaulted bank loans. Our results are not only important for banks, but also for regulators, because neglecting these issues leads to a significant underestimation of capital requirements.     

Using Housing Futures in Mortgage Research

Expectations of housing prices play an important role in real estate research. Despite their importance, obtaining a reasonable proxy for such expectations is a challenge. The existing literature on mortgage research either does not include housing expectation proxies in empirical models, or uses “backward-looking” proxies such as past housing appreciation or time series forecasts based on past housing appreciation. This paper proposes to use the transaction prices of Case-Shiller housing futures as an alternative “forward-looking” proxy. As an example, we compare the performances of four different expectation proxies in explaining mortgage default behavior. The loan level analysis shows that the futures based expectation proxy outperforms other proxies by having the highest regression model fit and being the only proxy that shows a significant negative effect on mortgage default behavior, as theory suggests. Out of sample predictions also show that futures have better prediction accuracy than other proxies. In addition, the paper shows that futures contain additional information that is not present in the backward-looking proxies.     

A Model of Mortgage Default

In this paper, we solve a dynamic model of households' mortgage decisions incorporating labor income, house price, inflation, and interest rate risk. Using a zero‐profit condition for mortgage lenders, we solve for equilibrium mortgage rates given borrower characteristics and optimal decisions. The model quantifies the effects of adjustable versus fixed mortgage rates, loan‐to‐value ratios, and mortgage affordability measures on mortgage premia and default. Mortgage selection by heterogeneous borrowers helps explain the higher default rates on adjustable‐rate mortgages during the recent U.S. housing downturn, and the variation in mortgage premia with the level of interest rates.     

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.     

次贷危机、信息不对称和指数交易

次贷危机源于房价上涨停滞后的次贷及其衍生品市场的快速萎缩,信息不对称在危机爆发前风险累积阶段和危机后市场过度反应阶段都是关键因素.次贷及其衍生产品设计繁复且对房价系统性下跌高度敏感,次贷的衍生产品多在场外市场交易使得危机前相关信息未被充分披露.随着指数交易的陆续推出,如基于次债的ABX.HE指数和CME的房地产价格指数期货期权合约,使房价、次贷及其衍生产品的概括性信息得以揭示,基于信息不对称因素的恐慌加重了危机程度.综上,本文针对衍生品设计和市场的完善提出了建议.     

基于房地产市场的我国系统性金融风险测度与预警研究

本文阐释了基于房地产市场的系统性金融风险形成机制,据此建立了分阶段、跨部门的房地产市场的系统性金融风险网络模型,并运用2006-2017年16家上市银行数据,分析和测度了我国房价大幅下跌所引发的系统性金融风险水平和结构,构建了基于房地产市场的系统性金融风险预警指标并进行测算。研究发现:在房价下跌30%的压力情景下,我国金融体系的潜在总损失总体呈级数式上升,年均增长22.70%;基于房地产市场的系统性金融风险值(SR)呈现先上升后波动下降的总体趋势;系统性金融风险(SR)的脆弱性指标(FLI)整体呈现波浪式振荡变化,且与房地产贷款/权益整体呈反向变动,系统性金融风险(SR)的传染性指标(CTI)在2012-2017年呈持续下降趋势,且与金融市场压力指数、金融机构间资产占总资产比重呈现出高度的一致性变化趋势。最后,基于房地产市场的系统性金融风险预警指标(SRWI)值呈收敛式振荡走势,表明基于房地产市场的系统性金融风险总体可控且呈收敛式下降。     

Mortgage Debt Overhang: Reduced Investment by Homeowners at Risk of Default

Homeowners at risk of default face a debt overhang that reduces their incentive to invest in their property: in expectation, some value created by investments in the property will go to the lender. This agency conflict affects housing investments. Homeowners at risk of default cut back substantially on home improvements and mortgage principal payments, even when they appear financially unconstrained. Meanwhile, they do not reduce spending on assets that they may retain in default, including home appliances, furniture, and vehicles. These findings highlight an important financial friction that has stifled housing investment since the Great Recession.     

Breakeven Determination of Loan Limits for Reverse Mortgages under Information Asymmetry

Since the loan limit of a reverse mortgage is a major concern for the borrower as well as the lender, this paper attempts to develop an option-based model to evaluate the loan limits of reverse mortgages. Our model can identify several crucial determinants for reverse mortgage loan limits, such as initial housing price, expected housing price growth, house price volatility, mortality distribution, and interest rates. We also pay special attention to the important implication of mortgage lenders’ informational advantage over reverse mortgage borrowers concerning housing market risk. In reverse mortgage markets, the elderly borrowers typically hold far less, relative to the lenders, or no information about the lenders’ underlying mortgage pools. Such information asymmetry leads these two categories of market participants to generate different perspectives on the risk of the collateralized properties, which can be identified to be important in determining the maximum loan amounts of reverse mortgages. We further find that the maximum loan amount of a reverse mortgage decreases in the correlation between the returns on the pooled underlying housing properties but increases with the number of the pooled mortgages.