Stuart S. Rosenthal

Credit rationing, race, and the mortgage market

Abstract This study applies microdata from the 1983 Survey of Consumer Finances to evaluate the effects of borrower race and default risk in mortgage lending. The empirical analysis is based on a probit model of whether borrowers obtain FHA or conventional mortgages; the former are fully insured and are characterized by easier downpayment constraints, but are typically more expensive. Hence, households borrowing through the FHA will tend to be credit constrained in the conventional market. Results of the analysis indicate that variables which proxy lender concerns about default risk and cost have an important effect on the type of loan borrowers obtain. Empirical estimates also suggest that minority households are significantly less likely to obtain conventional financing than whites, even after controlling for various proxies of default risk. These results suggest that race effects in mortgage lending may persist for reasons unrelated to borrower default risk.

Borrowing constraints and access to owner-occupied housing

Abstract Cross-sectional data from the 1983 Survey of Consumer Finances (SCF) enable us to identify two groups of households: those whose housing tenure status is unaffected by borrowing constraints, and those whose housing tenure status may be affected by borrowing constraints. Using these data, a bivariate probit model is estimated to evaluate the joint probability of whether families prefer to live in owner-occupied housing and whether borrowing constraints affect access to owner-occupied housing. Findings indicate that borrowing constraints have a significant negative effect on homeownership rates. Indeed, if borrowing constraints had not been binding in our sample period (the early 1980s), ceteris paribus, owner-occupancy rates in the United States would have risen from 64.5% to nearly 73%. Moreover, borrowing constraints appear to have a disproportionate effect on the ability of younger families and non-white families to own a home, consistent with popular perceptions.

Credit rationing and the demand for owner-occupied housing

Abstract This study applies cross-sectional data to test whether default risk-induced credit constraints affect the demand for owner-occupied housing. Credit-constrained households are argued to exhibit different elasticities of demand for housing than less constrained households. Housing demand elasticities are then estimated separately for households obtaining VA-insured and non-VA loans: the government guarantee on VA loans insures lenders against default, enabling lenders to apply easier nonprice terms of credit. Results indicate that observed demand elasticities differ significantly across VA and conventional mortgage holders, that marginal changes in credit constraints affect housing demand, and that FHA financing mitigates the effect of mortgage constraints.

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.

Owner-occupied housing, capital gains, and the Tax Reform Act of 1986

Abstract Previous homeowners face a nonlinear (kinked) budget constraint because they can avoid paying tax on the capital gain from the sale of their home if they purchase a more expensive home when they move. Simulation results suggest that the Tax Reform Act of 1986 (TRA86) has enhanced the importance of the capital gains kink by raising the after-tax cost of housing through lower marginal income tax rates while increasing the tax rate on capital gains. As a result, a reduction in the capital gains tax rate would reduce housing demand as some families currently at the kink would buy a less expensive home. Our findings also indicate that the level of excess burden increases with the capital gains tax rate, but that TRA86 reduced the size of implicit price subsidies received by owner-occupiers, and related deadweight loss, by roughly one-half. However, the distribution of benefits and deadweight loss from the favorable tax treatment of housing remains heavily weighted to higher income families. In addition, the size of the implicit housing subsidy and related distortion is sensitive to the level of mortgage rates.

Housing Supply: The Other Half of the Market a Note from the Editor

When I first read Edgar Olsen’s (1987) excellent review of the literature on the demand and supply for housing several years ago I was reminded of a pamphlet I saw during graduate school. The pamphlet purported to be a guide to climbing and fishing at one of Wisconsin’s more obscure parks and included a description of various climbing opportunities. On its last page, the pamphlet reported that there was no fishing at the area. By contrast, Olsen’s review examines the lessons learned from a large amount of literature on housing demand but then concludes that there is a comparative dearth of research on housing supply. While the literature on housing supply (and demand) has certainly grown in the last ten years, housing supply remains enormously understudied relative to demand, a situation that at first glance is puzzling since housing supply comprises half of the housing market. Why then has housing supply received such limited attention? It is unlikely that lack of interest is the reason. Rather, I suspect there is a widespread belief that adequate data do not exist to properly examine empirical issues pertinent to housing supply or possibly that the conceptual foundations of housing supply are difficult to model. With these considerations as a backdrop, this issue seeks to accomplish three principle goals. First, to demonstrate that we can indeed study housing supply, both at the empirical and conceptual levels. Second, to summarize what we know about housing supply and provide an important increment to our knowledge of housing supply. Third, to highlight areas and questions that are both important and feasible to address in future research. To accomplish these goals this issue is organized as follows. The first article by DiPasquale conducts a selected review of the literature on housing supply. The review does not simply list what other studies have done but organizes the literature on housing supply into different categories and identifies areas in which our knowledge to date is lacking. An important point emphasized by DiPasquale is that most of the empirical work on housing supply has utilized aggregate time-series data and that there is a need to develop high-quality micro databases suitable for examining the micro foundations of housing supply. Both for readers familiar with the housing literature, and for readers new to the area, this article is a good starting point before examining the other articles in the issue. Blackley follows with an article that addresses the most frequently researched issue in the literature on housing supply: measuring the elasticity of new housing supply. Using a common database, Blackley estimates the long-run elasticity of new housing supply for four different specifications that have appeared in the literature since 1979 and

Adjustable-rate mortgages, household mobility, and homeownership: A simulation study

A semi-Markov model is used to evaluate the effects of adjustable-rate mortgages on housing tenure decisions of recent movers and steady-state homeownership rates. Simulations were undertaken based on household data from the Panel Study of Income Dynamics together with information on FRM-ARM rate spreads and Treasury yield curves. Results suggest that under most interest rate patterns that prevailed in the 1980s, ARMS had little effect on the relative cost of owning to renting and, as a result, had little effect on mover tenure choice and home sales. Moreover, despite some minor projected increase in the percentage of movers that choose to own when ARMs are available, ARM effects on steady-state owner-occupancy rates appear to be largely mitigated by an ARM-induced tilt toward a relatively more mobile steady-state pool of owner-occupiers.