Analysis of Discrimination in Prime and Subprime Mortgage Markets
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ANALYSIS OF DISCRIMINATION IN PRIME AND SUBPRIME MORTGAGE MARKETS by R. Glenn Hubbard* Darius Palia Wei Yu This Draft: September 2012 Abstract This paper examines evidence of lending discrimination in prime and subprime mortgage markets in New Jersey. Existing single-equation studies of race-based discrimination in mortgage lending assume race is uncorrelated with the disturbance term in the loan denial regression. We show that race is correlated with both observable and unobservable risk variables, leading to biased coefficient estimates. To mitigate this problem, we specify a system of equations and use a full information maximum likelihood (FIML) method and two-stage least squares (2SLS) We use as an instrumental variable for race, the number of African-American church members at the county-level. Both FIML and 2SLS show that minorities are more likely to be rejected than whites in the prime market, but less likely to be rejected than whites in the subprime market, results supportive of the information-based theory of discrimination. We also find that the reduction in rejection rates to minority neighborhoods from 1996 to 2008 cannot be fully justified by risk, suggesting a relaxation of lending standards to minority neighborhoods. Using the methodology of Mian and Sufi [2009], we also find evidence for strong credit supply effects. JEL codes: J15, G21 * Corresponding author. Address: Dean and Russell L. Carson Professor of Finance & Economics, Columbia Business School, 3022 Broadway, Uris Hall 101, New York, NY 10027. Phone: (212)-854-2888. Email address: [email protected]. We thank Orley Ashenfelter, Ivan Brick, Paul Calem, Markus Brunnermeier, Serdar Dinc, Alan Krueger, Henry Farber, Alexandre Mas, Atif Mian, and Cecilia Rouse for helpful comments. Part of this research was conducted when the second author was a visiting professor at Princeton University. All errors remain our responsibility. 1. Introduction: It is now widely accepted that the recent credit crisis and Great Recession has as one of its primary causes the excesses of the U.S. mortgage market (for example, see Blinder [2007, 2009], Stiglitz [2007], Calomiris [2008], and Brunnermeier [2009]). The adverse impact of declines in the value of residential real estate have been especially acute in the subprime mortgage markets, in which loans were made to borrowers with lower credit quality and/or short credit histories. According to Inside Mortgage Finance,1 the volume of subprime mortgage originations grew from $75 billion in 1994 to a peak of $625 billion in 2006, and then falling to $93 billion in 2009. The rise of the subprime mortgage market allows us to test for race-based discrimination in the residential real estate prime and subprime markets. With home ownership rates at 67.4 percent in 2009,2 housing is an important asset in households’ portfolio holdings, with consequences for other portfolio assets and asset returns.3 However, there are still significant differences in homeownership rates among African-Americans (46.2 percent), Hispanics (48.4 percent), and whites (71.4 percent).4 The Fair Housing Act of 1968 prohibits discrimination based on race, and is actively enforced by the Office of Fair Housing and Equal Opportunity in the U.S. Department of Housing and Urban Development (HUD). Moreover, the Home Mortgage Disclosure Act (HMDA) of 1975 and the Community Reinvestment Act (CRA) of 1977 were enacted by Congress5 to monitor lending institutions’ fair lending practices to minority and low-income borrowers and neighborhoods. The subprime market has both a beneficial and destructive impact on mortgage borrowers (see Gramlich [2007] for a good discussion). On the one hand, subprime lending makes credit accessible to borrowers with blemished credit histories and/or volatile income who do not qualify for mortgages in the prime lending market. On the other hand, a proportion of subprime borrowers were very vulnerable to any adverse economic shock due to low verifiable income stability and savings, and were forced to sell their houses early, often ending in foreclosures. 1Mortgage Market Statistical Annual [2010, volume 1]. 2 U.S. Census Bureau 2009 Housing Vacancies and Homeownership Survey. 3Hubbard [1985], Campbell [2006], Cochrane [2007], among others, propose that real estate is an illiquid/nontraded asset that has a significant affect on a household’s portfolio choice and asset returns. Empirical evidence of such effects has been found in Flavin and Yamashita [2002], and Piazzesi, et al. [2007], among others. 4 U.S. Census Bureau 2009 Housing Vacancies and Homeownership Survey. 5 The HMDA is enacted by Congress and implemented by the Federal Reserve Board's Regulation C. The CRA is enacted by Congress and implemented by Regulations 12 CFR parts 25, 228, 345, and 563e. 1 Some lenders have also been sued for allegedly targeting minority borrowers and minority neighborhoods for high-cost subprime loans, a practice referred to as “reverse redlining.” For example, the NAACP has filed a lawsuit in federal court in Los Angeles against 12 mortgage lenders for steering African-American borrowers into high-cost subprime loans (New York Times, October 15, 2007). Similarly, the City of Baltimore (National Public Radio January 11, 2008) and state of Illinois (Wall Street Journal July 31, 2009) both sued Wells Fargo bank, for high-cost subprime mortgage lending to minority borrowers. Given the importance of real estate and the stated objective of regulators to fair and equal access to housing, researchers have examined whether African-Americans and Hispanics are discriminated against by lenders (see, for example, Black, Schweitzer, and Mandell [1978]; King [1980]; and Munnell, et al. [1996], among others). These studies have examined whether minorities are rejected more often in prime mortgage loans than white applicants (referred to as the accept/reject decision). We add to this research in four ways. First, we examine discrimination in both prime and subprime markets. In doing so, we analyze for any differences in discrimination between prime and subprime markets, the latter being where a large proportion of minority borrowers tend to obtain their mortgages (Scheessele [2002]; Calem, et al. [2004]; and Mayer and Pence [2008]). Second, we use two economic theories of discrimination (taste-based, Becker, 1957; information-based statistical theory, Phelps, 1972, Arrow, 1973) to derive possible hypotheses for testing (See Section 2.1 for further details). Analyzing the subprime market along with the prime market allows us to test the differing implications of these theories using actual data. In order to test these theories, recent studies have used small samples of self-reported data, or studied a game, or conducted an experiment.6 For example, Levitt (2004) describes two important caveats in his study of the voting behavior on the television show titled the “Weakest Link,” namely, that the environment is not a market setting, and individuals who both apply and are then selected for the game show are not representative of the general population. Individuals 6 Some studies have tested for discrimination in a game setting (for example, Fershtman and Gneezy [2001]; Levitt [2004]) or in a paired-audit experimental setting (for example, Turner, et al. [2002]; Bertrand and Mullainathan [2004]). Yinger (1998), Ross and Yinger (2003), and Anderson, Fryer and Holt (2005) provide detailed surveys on the discrimination literature and Levitt and List (2009) provide an excellent overview of field experiments in economics. Hausman and Wise (1979), Heckman (1992), Heckman and Smith (1995), and Manski (1996), among others, have criticized these studies as not being generalizable to large-scale markets, not having true randomness, having attrition bias, and participants changing their behavior due to their awareness of being measured. 2 who own real estate are representative of the general population, and lenders are required to disclose details of every loan application to the Federal Financial Institutions Examination Council (FFIEC) under HMDA. Third, previous research on race-based lending discrimination uses a single-equation model of mortgage acceptance and assumes the race variable to be uncorrelated with the error term in the accept/reject model. Though problems associated with single-equation tests for discrimination have been observed in studies by Rachlis and Yezer [1993], Yezer, Phillips and Trost [1994], among others, these papers have focused on the endogeneity of loan terms, especially the loan-to-value ratio.7 None of these papers has tested the hypothesis that race is correlated with observable and unobservable risks.8 If such a hypothesis is not statistically rejected, the average disturbance term in these single-equation probit models is not conditionally zero, resulting in inconsistent regression parameter estimates. Fourth, we ameliorate the bias in the single-equation probit model using two methods. The first method uses the full information maximum likelihood method (FIML) or bivariate probit. The advantage of this method is that it is at the individual loan level, the unit at which the lending officer makes the decision. The disadvantage is that the regression estimates depends crucially on the normality assumption of the error terms in the two equations. The second method is two-stage least squares (2SLS) at the neighborhood census tract level. The advantage of 2SLS is that the regression estimates do not depends crucially on the statistical distribution