Institutional disparities in the pricing of adjustable rate mortgage loans

In recent years, commercial banks and savings and loan associations in South Florida have consistently offered initial adjustment period teasers, or subsidies, on their adjustable rate mortgage loans (ARMs). This study adopts the size of the initial subsidy as a proxy for a lender's willingness to offer ARM loans and develops an econometric model which relates the size of the teaser to a series of internal variables (other lending parameters), and external variables (financial market conditions).The results suggest that subsidization policies are not identical across institutions. Specifically, savings and loan associations seem to be less willing than commercial banks to accept the interest rate exposure inherent in ARM lending when future loan rates are constrained by adjustment limits. Consequently, the study argues that the character of a lender's existing assets influences its reactions to the risk/return properties of new assets.This paper has benefitted greatly from the comments of the Journal's reviewers. Responsibility for remaining errors rests with the author.     

Do mortgage rates vary based on household default characteristics? Evidence on rate sorting and credit rationing

Credit screening models suggest that lenders vary loan rates and debt ceilings across applicants on the basis of credit risk. We argue that regulatory constraints such as Fair Lending Laws may preclude rate sorting while increasing lender use of debt ceilings to adjust for applicant credit risk. Using household data from the 1983 SCF, we find that mortgage rates do not vary with applicant credit risk whereas related studies find that debt ceilings vary with borrower risk attributes. Together, these findings support arguments that regulatory constraints reduce rate sorting while increasing the use of non-price terms in the mortgage contract.     

Optimal Loan Interest Rate Contract Design

This paper analyzes optimal loan interest rate contracts under conditions of risky, symmetric information for one-period (static) and multi-period (dynamic) models. The optimal loan interest rate depends upon the volatility of, and co-variation among the market interest rate, borrower collateral, and borrower income, as well as the time horizon and the risk preferences of lenders and borrowers. For a risk-averse borrower with stochastic collateral, variable interest rate contracts are, in general, Pareto optimal. For plausible assumptions, the optimal loan interest rate for the multi-period model often exhibits muted responses to changes in market interest rates, making fixed rate loans a reasonable approximation for the optimal loan. Hence, in the absence of optimal contracts, long-term (short-term) borrowers tend to prefer fixed rate (variable) contracts.     

Changes in Non-Local Lending to Small Business

In this paper, I use recently collected Community Reinvestment Act loan data to examine how small business lending in local geographic areas (defined as markets) by lenders not physically located in those areas changed between 1996 and 2001. The results show that the importance of outside lending increased substantially over this period when measured in terms of the number of loans rather than the dollar volume of loans. The levels and rates of growth in out-of-market lending are more modest if the share of out-of-market lending is expressed in dollar volumes and almost insubstantial if organizations that engage in substantial credit card lending are excluded as out-of-market lenders. Using a fixed-effects model and an extensive panel data set, I find that the share of outside lending into local geographic markets is positively associated with local market concentration and the average wage of tellers in the market, consistent with the hypothesis that outside loans are to some degree substitutes for in-market loans.     

Differences in the Cost of Mortgage Credit Implications for Discrimination

This paper estimates the mortgage interest rate differences paid by Asian, Hispanic, and African–American borrowers to a national home mortgage lender in the years 1988–1989. Controlling for differences in market rates, rate lock protection, and borrower risk factors, conventional loan interest rates are almost perfectly race-neutral. The single deviation from race-neutrality is that when interest rates fall during the borrower's rate-lock period, only African–American borrowers are unable to capture a share of this decline. Government (FHA and VA) credit models show small premia paid by African–American borrowers of about $1.80 per month on average. In government lending, Hispanic borrowers alone are unable to capture rate declines occurring during the borrower's rate-lock period.     

Subprime Borrowers: Mortgage Transitions and Outcomes

Public policy concerns increasingly have focused on subprime lending. Our research uses a survey of prime and subprime borrowers to address whether borrowers inappropriately are channeled to the subprime segment, if once having taken out a subprime mortgage borrowers are stuck in this market segment, and whether borrowers face higher costs by taking out subprime mortgages. We find that subprime borrowers are less knowledgeable about the mortgage process, are less likely to search for the best mortgage rates, and are less likely to be offered a choice among alternative mortgage terms and instruments—possibly making them more vulnerable to unfavorable mortgage outcomes. Our analysis of market segmentation confirms that typical mortgage underwriting criteria are most important in explaining whether borrowers obtain prime or subprime mortgages—higher credit risk borrowers are more likely to get a subprime loan. Our results further show that search behavior and other demographic factors including adverse life events, age, and Hispanic ethnicity contribute to explaining market segment, suggesting that borrowers may inappropriately receive subprime mortgages. While we find some persistence to market segment—borrowers are more likely to take out a subprime mortgage if their previous mortgage came from the subprime segment—we also find that market segment is not immutable. Analysis of the survey responses indicates that borrowers with subprime mortgages significantly are more dissatisfied with their mortgage outcomes. This is not surprising because subprime borrowers look worse across typical mortgage underwriting criteria. Consistent with policy concerns, however, despite holding constant these and other factors, taking out a mortgage in the subprime segment, by itself, appears to increase dissatisfaction with mortgage outcomes. We do not provide a definitive answer to the question of whether subprime lending, on balance, serves homebuyers well by providing access to mortgage credit to those otherwise constrained, or rather serves homebuyers poorly by inappropriately assigning them to a market where costs are high and the ability to transition to more attractive prime mortgages remains low. Our analysis, however, does provide some empirical support for concerns raised by critics of subprime lending, and for this reason justifies continued public policy debate and analysis.     

Strategic default,workout, and commercial mortgage valuation

This paper extends existing equilibrium commercial mortgage pricing models by endogenizing negotiated workout into the usual noncooperative lending game. Workout is a feasible subgame strategy for the lender to play whenever foreclosure transaction costs exist for either party to a loan transaction. In particular, negotiated workout solutions Pareto dominate the foreclosure alternative when default occurs. To obtain our results, we embed a cooperative bargaining game within a noncooperative mortgage loan/default game. We also address the valuation wedge problem that occurs when foreclosure transaction costs are introduced. Through the notion of replacement game equilibrium, we find symmetric mortgage pricing solutions that eliminate the valuation wedge and thus suggest that lending will occur in commercial real estate mortgage markets even when foreclosure transaction costs exist.     

Using HMDA Data as a Regulatory Screen for Fair Lending Compliance

This paper describes and evaluates the Federal Reserve System's recently developed program designed to use HMDA data as a screening device for fair lending enforcement. The program is designed to identify institutions showing potentially discriminatory patterns in their treatment of minority mortgage applicants vis-a`-vis nonminority applicants. The program also selects specific loan files to pull for additional information in cases where a more comprehensive evaluation might be appropriate. This paper discusses the motivation behind the adoption of the program and its innovative matched-pair method and assesses its value and potential shortcomings.     

Fixed-Rate Endowment Mortgage and Mortgage Indemnity Valuation

We use a contingent claims framework for valuing the the default and prepayment embedded options in certain British fixed-rate endowment mortgages, with a (capped) mortgage indemnity guarantee (MIG). This methodology provides a template for the borrower, lender, and insurer to compare mortgage terms, including the fairness of contract rates, arrangement fees, prepayment penalties, any MIG premiums required, and co-insurance exposure. With empirical inputs, this model may eventually be useful as a mark-to-value proxy for all parties, as expected parameters change (especially interest rate and house price levels, and expected future volatilities), for purposes of determining valued added accounting, appropriate reserves, and indeed for setting premiums and business drivers. Fixed-rate endowment mortgages differ from fixed-rate repayment mortgages primarily because, in the event of early termination, the amount owed by the borrower is a function of the evolution of the term structure of interest rates, whereas for a repayment mortgage it is pre-determined. We compare endownment and repayment mortgages for different levels of loan-to-value ratios, interest rate and house price volatilities.     

The “Rent-To-Own” mortgage and prepayment risk

The most important risk factor in the mortgage and mortgage-backed security market has been prepayment risk. Various innovations have arisen to deal with it but none hedge it fully. The Rent-To-Own (RTO) mortgage discussed here is a mortgage instrument that reduces or even reverses prepayment risk. It does so by creating an incentive structure within the framework of the mortgage contract that penalizes prepayment when interest rates are low and rewards it when interest rates are high. This is the opposite of standard mortgages. The RTO incentive structure is based on a unique buyout feature. Borrowers who want to buy out the financial interest of the lender may do so whenever they want, but the buyout price is a negative function of the market interest rates prevailing currently, that is, at the time of the buyout. Hence the lower these rates, the higher the buyout price. Other advantages of the RTO mortgage are also described.     

Mortgage credit availability in low- and moderate-income minority neighborhoods: Are information externalities critical?

This study conducts a cross-sectional analysis of U.S. metropolitan counties to inquire into the factors affecting white and minority mortgage loan approval rates during 1990–1991. In particular, evidence is sought on whether minority loan applicants are denied credit more frequently than white applicants because of information externalities. Within each county, all predominantly minority, low- or moderate-income census tracts are groupted together, and then regression equations are estimated across counties and tract groupings. Separate approval rate equations are estimated for conventional and federally insured (FHA or VA) home purchase loans. In addition, a regression equation for the percentage of applicants applying for federally insured loans is estimated.Both approval rate regressions indicate that across white tract groupings, the depth of the housing market (the number of sales of owner-occupied units during 1989) has a positive and statistically significant effect on the loan approval rate, consistent with the view that information externalities affect mortgage loan evaluations. However, this relationship appears not to hold across minority tract groupings.     

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.     

Banks as Interest Rate Managers

Most banks have a two-tier pricing system, offering accounts at market-related interest rates and at posted rates that are changed at discrete intervals. In this paper, I develop a model of bank interest rate management. I consider a bank with two classes of loans and deposits in its balance sheet: One pays a market rate of interest, the other a posted rate. Market rates are exogenous and evolve stochastically over time. Posted rates are altered intermittently by the bank itself. The bank faces imperfect arbitrage by its customers between posted and market rate funds. Under simple assumptions about the stochastic process governing the market rate, I derive optimal decision rules for the adjustment of the posted rate and determine conditions under which these rules are asymmetric. A key prediction of the model is a negative correlation between market loan rates and the gap; this is more consistent with the behavior of British banks than is the contrary prediction of more standard models.     

Balance Sheets, the Transfer Problem, and Financial Crises

In a world of high capital mobility, the threat of speculative attack becomes a central issue of macroeconomicpolicy. While first-generation and second-generation models of speculative attacks both have considerablerelevance to particular financial crises of the 1990s, a third-generation model is needed to make sense of thenumber and nature of the emerging market crises of 1997-98. Most of the recent attempts to produce such amodel have argued that the core of the problem lies in the banking system. This paper sketches another candidatefor third-generation crisis modeling—one that emphasizes two facts that have been omitted from formal modelsto date: the role of companies' balance sheets in determining their ability to invest, and that of capital flows inaffecting the real exchange rate.     

Comparing Present Value Cost Differentials between Fixed- and Adjustable-Rate Loans: A Mortgage Simulation

When a borrower chooses between a fixed-rate and an adjustable-rate loan, he is doing so based on expectations of future interest rates and the expected life of the loan. This paper demonstrates how Monte Carlo simulation can be employed to assist in decision making when the borrower is confronted with the choice of fixed or adjustable-rate mortgages. Present value costs of future mortgage payments are modeled using actual lending parameters offered over a 50-month period, at varying borrower discount rates, and with different mortgage holding periods. The selection of a fixed-rate or a variable-rate mortgage is shown to be sensitive to mortgagee holding period and discount rates as well as to market conditions.     

On the Economics of Subprime Lending

US mortgage markets have evolved radically in recent years. An important part of the change has been the rise of the subprime market, characterized by loans with high default rates, dominance by specialized subprime lenders rather than full-service lenders, and little coverage by the secondary mortgage market. In this paper, we examine these and other stylized facts with standard tools used by financial economists to describe market structure in other contexts. We use three models to examine market structure: an option-based approach to mortgage pricing in which we argue that subprime options are different from prime options, causing different contracts and prices; and two models based on asymmetric information–one with asymmetry between borrowers and lenders, and one with the asymmetry between lenders and the secondary market. In both of the asymmetric-information models, investors set up incentives for borrowers or loan sellers to reveal information, primarily through costs of rejection.     

Creditor Learning and Discrimination in Lending

I study the implications of creditor learning for the estimated racial disparity in access to credit. Utilizing a dataset of mortgage lending, I find that the estimated racial disparity in loan approval rates declines with the length of the borrower??s credit history. In addition, minority borrowers improve significantly their chances of obtaining a loan by accumulating longer credit histories, with the improvements being the largest for those with no credit history. Importantly, I find no significant racial disparity among borrowers with long credit histories, suggesting that one cannot reject the null hypothesis of no taste-based discrimination taking place. I also conduct a number of tests to detect statistical discrimination, which yield inconclusive results.     

Does credit rationing affect residential investment? Déjà vu all over again

This paper develops an empirical model to examine the impacts of credit rationing on residential investment for the 1960–1984 period. Our statistical results strongly support the position that noninterest rate variables affect mortgage activity and housing construction. Though we find a structural change in the housing construction and mortgage markets in the early 1980s, probably attributable to capital market integration and financial institutional deregulation, noninterest rate terms continue to matter. In other words, credit rationing continues to be an allocative device in the housing and mortgage markets.Earlier versions of this article have been presented at the Western Economic Association Conference, Los Angeles, June 1988; the Tenth Pacific Regional Science Conference, Pusan, Korea, July 1987; the AREUEA Annual Meetings New York City, December 1985; and the American Finance Association Annual Meetings, San Francisco, December 1983.     

The Relationships Between Mortgage Rates and Capital-Market Rates Under Alternative Market Conditions

Mortgage interest rates have become more integrated with other capital-market interest rates over recent decades, apparently as a result of the deregulation of financial markets. The link is both imperfect and time-varying. Mortgage rates during some time periods appear to be sticky with respect to their adjustment to changes in capital-market rates. We examine the relationship between weekly conventional mortgage rates and the interest rates on treasury and corporate securities under differing market conditions. We draw three conclusions based on the analysis. First, deregulation changed the link between mortgage rates and riskless interest rates, which confirms the findings of Goebel and Ma (1993). Second, mortgage rates were cointegrated with risky interest rates even before deregulation. Third, the link between mortgage rates and the risky bond rate can be associated with the behavior of the risk premium in the bond rate. The observed relationship is consistent with the stickiness observed by Haney (1988) and causes a more pronounced stickiness when rates are falling than when they are rising.     

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.