Do Predatory Lending Laws Influence Mortgage Lending? An Analysis of the North Carolina Predatory Lending Law

In this paper, we examine the effect of the 1999 North Carolina predatory lending law on mortgage activity in that state as compared to other states in the Southeastern United States. Using 1998–2000 Home Mortgage Disclosure Act (HMDA) data, we find that the North Carolina law reduced the overall level of subprime mortgage lending activity. Furthermore, we find that the North Carolina decline was caused by a decline in loan application volume and not by a change in loan denial rates, suggesting less aggressive marketing in that state after the imposition of the law. Finally, the impact of the legislation was different by both the type of financial service provider and borrower. Specifically, non-bank subprime lending contracted faster in North Carolina when compared to the control group, while both minority and low-income applicants were also less likely to get loans following the legislation. These results have wide ranging policy implications given that several predatory lending proposals are currently before Congress, as well as proposed in almost forty other states.     

Under-specified Models and Detection of Discrimination: A Case Study of Mortgage Lending

This study examines how omitted variables affect underwriting models the OCC estimates during fair lending examinations. The purpose is to assess the effects of omitted variable bias common to most studies of discrimination in mortgage lending. The results show omitted variables have an important impact on both the estimate of the effect of race and on the identification of outliers for review. Further, there appears to be no consistent patterns to the direction of these impacts. This suggests that it is inappropriate to make generalizations concerning the direction of bias based on assumptions about correlations between omitted variables and race.     

A Reconsideration of the Jumbo/Non-Jumbo Mortgage Rate Differential

Consistent with a series of recent papers, the interest-rate differential between mortgages eligible for purchase based on loan size by Fannie Mae and Freddie Mac and larger loans is estimated to be 22 basis points over the 1986–2000 period. This differential averaged 19 basis points for the 1996–2000 period. Other significant effects include: loans slightly above the conforming loan limit and originated late in a calendar year often have a lower rate that nearly fully anticipates their likely characterization as a non-jumbo loan after the conforming loan limit is indexed effective each January; loan-to-value ratios affect jumbo loan rates much more than they affect non-jumbo loan rates; loans located in non-metropolitan areas have a 3 basis point differential versus loans in metropolitan areas that is surprisingly small given the likely higher cost to service non-metropolitan loans and the higher degree of uncertainty about non-metropolitan collateral values; and estimated regional mortgage rate differentials have narrowed through time.     

Bank Lending to Native American Applicants: An Investigation of Mortgage Flows and Government Guarantee Programs on Native American Lands

We investigate the efficacy of government guarantee programs for mortgage loans made on tribal lands by comparing lending outcomes for White applicants and Native Americans (NAs) living on- and off reservation lands. Simultaneous equations models with the loan-to-income ratio endogenous indicate both on- and off-reservation NA applicants experience higher conditional denial rates compared with otherwise similar White applicants. NAs living on-reservation are equally as likely to be approved for mortgage loans as off-reservation NAs. On-reservation applicants self-select lower loan-to-income ratios, and are held to a higher standard for this credit variable, likely because lower housing values and other economic variables challenge on-reservation applicants. Our findings suggest lack of financial resources, lack of applicant education about and experience with the mortgage process, low creditworthiness, and lender reluctance to confront burdensome bureaucracy limit on-reservation guarantee program success.     

Frictions, Heterogeneity and Optimality in Mortgage Modeling

The purpose of this article is to provide a unified framework for incorporating frictions into a theoretical options-pricing model (OPM) for mortgages. This article presents formulation for a frictions-adjustable mortgage model that integrates borrower heterogeneity while simultaneously preserving prepayment and default financial decisions. Our model demonstrates the flexibility of the OPM by simulating separate and concurrent effects of three categories of frictions on the mortgage and mortgage components. Researchers can use our example formulation to determine the effects of specific borrower characteristics on mortgage values without destroying the options theoretic framework.     

排污权抵押贷款的障碍及法律完善

排污权抵押贷款作为一项绿色信贷措施,为商业银行开拓了信贷新产品,提升了商业银行的竞争力和社会形象。但由于排污权抵押立法的缺失,商业银行以排污权为抵押客体发放贷款时,将会面临一系列法律障碍,最终导致商业银行面临抵押权难以实现的风险。本文通过分析商业银行抵押权难以实现的法律原因,提出具体的解决措施和法律完善,以保障商业银行的经济利益,促进排污权抵押贷款业务的发展。     

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.     

Discrimination in Mortgage Lending: A Critical Review of the Literature

This article surveys the diverse research that examines racial disparities in mortgage lending markets in the context of the fair housing legislation of recent decades. A review of the theoretical models, data, and empirical methods reveals deficiencies in all three areas. A new research agenda focusing on development of more complete models of mortgage lending together with panel data tracking mortgage loan performance over time is needed.     

The Neighborhood Distribution of Subprime Mortgage Lending

Subprime lending in the residential mortgage market, characterized by relatively high credit risk and interest rates or fees, has developed over the past decade into a prominent segment of the market (Temkin, 2000). Recent research indicates that there is geographical concentration of subprime mortgages in Census tracts where there are high concentrations of low-income and minority households. The growth in subprime lending represents an expansion in the supply of mortgage credit among households who do not meet prime market underwriting standards. Nonetheless, its apparent concentration in minority and lower income neighborhoods has generated concerns that these households may not be obtaining equal opportunity in the prime mortgage market. Such lending may undermine revitalization to the extent that it is associated with so-called predatory practices.     

Commercial Mortgage Default: A Comparison of Logit with Radial Basis Function Networks

This article explores the use of artificial neural networks in the modeling of foreclosure of commercial mortgages. The study employs a large set of individual loan histories previously used in the literature of proportional hazard models on loan default. Radial basis function networks are trained (estimated) using the same input variables as those used in the logistic. The objective is to demonstrate the use of networks in forecasting mortgage default and to compare their performance with that of the logistic benchmark in terms of prediction accuracy. Neural networks are shown to be superior to the logistic in terms of discriminating between good and bad loans. The study performs sensitivity analysis on the average loan and offers suggestions on further improving prediction of defaulting loans.     

A Comparison of Unexplained Racial Disparities in Bank-Level and Market-Level Models of Mortgage Lending

Statistical models of mortgage lending have been used by both academics and regulators to assess the importance of racial discrimination in lending decisions. Models estimated by bank regulators are specified at a bank level, allowing regulators to focus on possible disparate treatment discrimination against minorities. In contrast, the academic literature has tended to estimate models combining data across many banks. We argue that the market-level approach uses a mis-specified model whose estimates do not clearly measure any well-defined concept of discrimination. Using data from eight banks, we find important differences between bank-level and market-level models, with market-level models producing larger estimated racial effects than bank-level models.     

抵押评估究竟采用什么价值类型

对于银行贷款中抵押物价值评估应采用什么价值类型,美国价值评估行业认为对应的应该是“市场价值”。他们认为债权方决定贷多少款,那是债权方自己的事,评估师能够且只能够提供的是市场价值,评估师不能替代债权方决策。而欧洲价值评估行业认为贷款抵押物价值评估的价值类型可以使用抵押价值这一价值类型。     

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.     

Skewness of Returns, Capital Adequacy, and Mortgage Lending

We calibrate a simulation model of credit value-at-risk for mortgage lending to UK experience. Simulations to capture the skewness of returns that might arise in the context of a financial crisis suggest that the IRB calculations of the new Basel Accord can substantially understate prudential capital adequacy. The same model shows that raising capital requirements has only a small impact on bank funding costs. We conclude that Pillar 2 supervisory review should increase capital requirements above IRB levels for secured bank assets—those whose returns can potentially fall furthest, relative to other, normally “riskier” assets, in extreme outcomes. JEL classification: G21, G28, R31. Presented at the December 2003 conference at the University of Tor Vegata, Rome. We are grateful for comments from William Lang, Mario Onarato, Larry Wall, and from an anonymous referee. All errors and omissions are our own responsibility. “The lady doth protest too much, methinks. The Queen's response to the players in Hamlet, Act 3, scene 2.     

Discrimination and Mortgage Lending in Boston: The Effects of Model Uncertainty

In 1992 the Federal Reserve Bank of Boston conducted an analysis that examined the effects of race on mortgage lending in the Boston Metropolitan Statistical Area. Collecting data on all the possibly relevant information used in the lending process, they find when controlling for a subset of this information that race has a statistically significant effect on the decision to reject a mortgage application. Other researchers, using the same dataset, have shown that analysis of alternative subsets of the variables significantly reduces the effects of race. While theory should guide variable selection, there is often no unique theory to explain social science. In such cases, uncertainty in model specification causes one to be uncertain as to the true effects of the variables of interest. This paper accounts for the effects of model uncertainty by using Bayesian model averaging and finds a reduced effect of race and weakened evidence concerning the statistical significance of the effect.     

住房抵押贷款证券化中的税务问题

住房抵押贷款证券化作为一种全新的资产运作和风险分散模式在西方国家已经取得了显著的成就。我国的住房抵押贷款证券化也终于在学术界的呼吁和金融界的期盼中走向了前台,但在税务制度上尚难以对其形成有力的支持。本文从税务问题的角度对住房抵押贷款证券化的各纳税主体和税种进行分析,并借鉴国外经验提出相应的建议。     

Economic Consequences of Transparency Regulation: Evidence from Bank Mortgage Lending

We examine the economic consequences of a rule designed to improve consumers' understanding of mortgage information. The 2015 TILA-RESPA Integrated Disclosures rule (TRID) simplifies the mortgage disclosures provided to consumers. As a consequence, TRID-affected mortgages become a less attractive investment opportunity to banks. Our main results document that mortgage applications affected by TRID are less likely to be approved following the rule's effective date. We find evidence consistent with both a decrease in consumers' information processing costs and an increase in banks' secondary market frictions, providing insight into the potential channels through which this reduction in mortgage credit operates. We also find that banks partially compensate for reduced mortgage lending by increasing small business lending, and that fintechs absorb mortgage demand in areas with reduced mortgage lending by banks. Our study documents real actions that firms take in response to disclosure transparency regulation and contributes to the literature on the economic consequences of such regulation.     

Cultural Affinity and Lending Discrimination: The Impact of Underwriting Errors and Credit Risk Distribution on Applicant Denial Rates

We examine the impact of underwriting errors on marginal loan denial rates when these errors or average creditworthiness differ across racial groups. We find that the noise in evaluating applicant credit risk can have a differential impact on marginal borrowers across racial groups. Consequently, discrimination can go undetected in an examination of relative loan denial rates when it is present. We also show that discrimination can be detected where none exists. Furthermore, we argue that it is likely that the errors a bank makes in assessing applicant credit risk are a consequence of its skill or affinity, which, in turn, is shaped by the underwriting experiences in the bank's market. A resulting implication is that banks that develop affinities in serving different market segments may have substantially different denial rate experiences across racial groups. This observation can shed light on the puzzling result that minority-owned banks tend to perform poorly in studies of lending discrimination. We conclude that underwriting errors call into question the reliability of the fair-lending guidelines used to assess all banks.