PPA786: Urban Policy

1. PPA786: Urban Policy Class 13: Discrimination in Mortgage Lending

2. PPA786, Class 13: Discrimination in Mortgage Lending • Class Outline • Definitions of discrimination in lending and of redlining • Evidence about discrimination in lending • Why does discrimination persist? • Fair lending policy

3. PPA786, Class 13: Discrimination in Mortgage Lending Discrimination in Mortgage Lending • The Equal Credit Opportunity Act of 1974 and the Fair Housing Act of 1968 prohibit: • Disparate-treatment discrimination, defined as using different standards to evaluate loan applications from people in different groups; • Disparate-impact discrimination, defined as using rules that are the same for everyone but that place loan applicants in certain groups at a disadvantage without business justification.

4. PPA786, Class 13: Discrimination in Mortgage Lending Redlining • These laws also prohibit redlining, which is defined as discrimination based on the racial or ethnic composition of the neighborhood in which a house is located. • There are some famous example of redlining (BBURG in Boston), but no clear evidence that it is a major problem today.

5. PPA786, Class 13: Discrimination in Mortgage Lending Disparate-Impact Discrimination, Example • Consider a city in which loans to purchase row houses are no more risky than loans for detached houses once other factors have been considered and in which blacks, unlike whites, tend to purchase row houses. • Under these circumstances, any lender that is less likely to approve a loan for a row house than for a comparable detached house is practicing disparate-impact discrimination.

6. PPA786, Class 13: Discrimination in Mortgage Lending Disparate-Impact, Example 2 • Predatory lenders often focus on neighborhoods with inexperienced homeowners, who are easier to fool. • Because these are black or Hispanic (or elderly) neighborhoods, this behavior may have a disproportionate impact on a protected class without a legitimate business purpose.

7. PPA786, Class 13: Discrimination in Mortgage Lending Disparate-Impact, Example 3 • Credit scores are a black box. They might give weight to traits that are correlated with race or ethnicity beyond the ability of those traits to predict default, they involve disparate-impact discrimination. • A recent Fed study finds that they do not: http://www.federalreserve.gov/pubs/feds/2010/201058/201058pap.pdf • The same goes for (unstudied) automated underwriting systems or the use of credit scores in decisions about home insurance or auto loans.

8. PPA786, Class 13: Discrimination in Mortgage Lending Why Outlaw Disparate-Impact Discrimination? • Why is it discrimination, some people ask, if a lender is using the same rules for every customer? • The answer is that disparate-impact discrimination is just a disguised form of disparate-treatment discrimination.

9. PPA786, Class 13: Discrimination in Mortgage Lending Discrimination By Any Other Name… • By considering factors that do not have a legitimate business purpose but are correlated with ethnicity, a lender can “predict” an applicant’s ethnicity. • Thanks to this type of prediction, a lender can reproduce virtually the same set of underwriting decisions using either disparate-treatment or disparate-impact discrimination.

10. PPA786, Class 13: Discrimination in Mortgage Lending Evidence On Discrimination • We do not have conclusive recent evidence on the extent of discrimination in mortgage lending, but we have hints in: • Homeownership gaps • Loan-denial gaps • Interest rate gaps

11. PPA786, Class 13: Discrimination in Mortgage Lending Homeownership Gaps • Recall from an earlier class that the homeownership rate for non-Hispanic whites is above 70%. • And that blacks and Hispanics have homeownership rates below 50%.

12. PPA786, Class 13: Discrimination in Mortgage Lending Changes in Homeownership Gaps • Mortgage discrimination may contribute to these homeownership gaps. • If mortgage discrimination is decreasing (as housing discrimination appears to be), these homeownership gaps should be going down. • In fact, however, they are just as high now as they were in the early 1980s.

13. PPA786, Class 13: Discrimination in Mortgage Lending

14. PPA786, Class 13: Discrimination in Mortgage Lending Disparities in the Lending Process • Inter-group disparitiesarise throughout the lending process. • These disparities do not prove discrimination, either, but they at least indicate the continuing power of discrimination in our past. • The following chart illustrates these disparities.

15. PPA786, Class 13: Discrimination in Mortgage Lending

16. PPA786, Class 13: Discrimination in Mortgage Lending Loan-Denial Gaps • Data collected under the Home Mortgage Disclosure Act (HMDA) cover virtually all mortgage applications in the country. • In 2011, black applicants were 2.6 times as likely as white applicants to be turned down for a conventional home-purchase loan. • Hispanic applicants were 1.8 times as likely to be turned down.

17. PPA786, Class 13: Discrimination in Mortgage Lending Loan-Denial Gaps and Discrimination • These loan-approval disparities do not prove that Blacks and Hispanics face discrimination in mortgage lending. • After all, they do not account for possible differences in applicant creditworthiness across groups. • But there are some hints.

18. PPA786, Class 13: Discrimination in Mortgage Lending Hint 1: The Boston Fed Study • By supplementing the 1990 HMDA data with every trait lenders identified as important, researchers at the Boston Fed were able to isolate disparate-treatment discrimination. • They found that a black or Hispanic applicant was 82% more likely to be turned down than an identically qualified white.

19. PPA786, Class 13: Discrimination in Mortgage Lending The Boston Fed Study, 2 • This study has been criticized by reporters and a few scholars, but strongly supported by most scholars who have looked at the data (including your professor!). • For a recent example, see http://faculty.maxwell.syr.edu/jyinger/publications/Reckless_Endangerment_Morgenson_Rosner.pdf • Although this study was done by the Federal Reserve Board, it has never been replicated!

20. PPA786, Class 13: Discrimination in Mortgage Lending Hint 2: Loan-Denial Gaps over Time • If discrimination is declining, the loan-denial gap should be closing over time—but it is not. • Indeed, the black/white and Hispanic/non-Hispanic-white loan-denial ratios have been growing in recent years. • The Asian/white ratio is about 1.0.

21. PPA786, Class 13: Discrimination in Mortgage Lending

22. PPA786, Class 13: Discrimination in Mortgage Lending Hint 3: Interest-Rate Gaps • Starting in 2004, the HMDA data flag approved loans with unusually high interest rates. • These new data were consistent with (but did not prove) discrimination. • In 2006, black applicants were 3 times as likely as whites to have a high-rate conventional home-purchase loan. • Hispanic applicants were 2.6 times as likely to have a high-rate loan. • Asians had about the same interest-rate profile as whites.

23. PPA786, Class 13: Discrimination in Mortgage Lending Interest-Rate Gaps, 2 • But something happened after the financial crisis. • Lenders have stopped making high-priced loans. • And differences by race and ethnicity have almost disappeared. • Will this situation continue?

24. PPA786, Class 13: Discrimination in Mortgage Lending

25. PPA786, Class 13: Discrimination in Mortgage Lending Limited Evidence • No large-scale study of discrimination in loan approval or loan pricing has emerged since 1992, when the Boston Fed Study first came out. • Regulators and lenders control the data and they do not want to release it. • But an unpublished study of FL and CA in 2005 finds discrimination (using the Ross/Yinger method) equal to $60 per month for Blacks and Hispanics. See • “Race, Redlining, and Subprime Loan Pricing,” by A. C. Ghent, R. Hernandez-Murillo, and M. T. Owyang. http://www.public.asu.edu/~aghent/research/ .

26. PPA786, Class 13: Discrimination in Mortgage Lending Will Discrimination Fade Away? • Some economists argue that, despite this evidence, discrimination is fading away. Two types of arguments have appeared. • Discrimination will be eliminated by competition. • Discrimination will be eliminated by automated underwriting.

27. PPA786, Class 13: Discrimination in Mortgage Lending The Profitability of Discrimination • Other, more careful economists have shown that this argument misses a key point: discrimination may be profitable. • Whenever ethnicity is correlated with default-relevant information the lender cannot observe (such as whether an applicant has relatives to provide financial help), then the lender has an economic incentive to (illegally!) consider ethnicity in making a loan decision.

28. PPA786, Class 13: Discrimination in Mortgage Lending Automated Underwriting and Discrimination • Some people also have claimed that credit scoring and automated underwriting will eliminate discrimination because the lender does not observe an applicant’s ethnicity. • After all, these people say, some mortgages are now granted over the internet with no face-to-face contact.

29. PPA786, Class 13: Discrimination in Mortgage Lending Automated Underwriting and Disparate-Impact Discrimination • Even if automated underwriting schemes do limit disparate-treatment discrimination, however, they by no means rule out disparate-impact discrimination. • Indeed, many of these schemes may “predict ethnicity” and thus have disparate-impact discrimination built into them, even if they appear to be group-neutral.

30. PPA786, Class 13: Discrimination in Mortgage Lending Automated Underwriting and Disparate-Impact Discrimination, 2 • Indeed, Steve Ross and I show in our book that an automated underwriting scheme that tries to be neutral by ignoring race or ethnicity is actually likely to build it in! • This happens because race and ethnicity are in the data and must be removed before a truly neutral scheme, i.e. one that predicts default but not group membership, can be devised.

31. PPA786, Class 13: Discrimination in Mortgage Lending Fair Lending Enforcement, in Principle • Fair lending laws are enforced by • The Consumer Finance Protection Bureau (which just took over from the federal financial regulatory agencies and the Federal Trade Commission). • The Justice Department • Department of Housing and Urban Development.

32. PPA786, Class 13: Discrimination in Mortgage Lending The Community Reinvestment Act • Another law often included isCRA, the Community Reinvestment Act of 1974. • CRA requires depository lenders to meet the credit needs of all neighborhoods in their traditional lending area. • It has complex administrative procedures, complemented by a role for community groups. • Several studies have found that CRA has a tiny positive impact on lending in underserved areas. • It goes beyond discrimination laws in principle, but is weaker in practice.

33. PPA786, Class 13: Discrimination in Mortgage Lending Fair Lending Enforcement, in Practice • The fair lending agencies have not been doing their job. • No agency has replicated the 1990 study to show how much discrimination still exists. • Few cases have been adjudicated in recent years by any of these agencies. • These agencies ignore small lenders and do not look for disparate-impact discrimination—either by lenders or in automated underwriting.

34. PPA786, Class 13: Discrimination in Mortgage Lending Fixing Fair Lending Enforcement • These problems could easily be fixed. • The fair-lending enforcement agencies could provide evidence on discrimination in loan approval and interest rates. • These agencies could implement procedures that would not ignore some lenders. • These agencies could implement procedures that would not ignore disparate-impact discrimination.

35. PPA786, Class 13: Discrimination in Mortgage Lending Fair Lending Challenges • The entry of the CFPB may help. • The culture of the federal financial regulatory agencies worked against fair lending enforcement. • Mortgage brokers were regulated by the FTC, which does not have the resources or mandate to do much. • However, • Fair lending laws do not apply if a subprime lender serves minority neighborhoods and a prime lender serves white ones. • No data set tracks loans after they are sold, so defaults can’t be tracked back to originators.