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ESSAYS ON ISSUES JULY 1995 NUMBER 95 THE FEDERAL RESERVE BANK OF CHICAGO Chicago Fed Letter Discrimination in mortgage lending In recent years much attention has been devoted to the issue of racial discrimination in the home m ort gage lending market. This interest has been fostered by the release of mortgage lending data under the Home Mortgage Disclosure Act of 1977 (HMDA). This act, which re quired depository institutions to disclose mortgage originations in m etropolitan areas by census tract, was am ended in 1989 to require lenders to report the disposition of every mortgage loan application, along with the loan am ount and the race or national origin and annual income of each applicant. Analysis of the raw data contained in the an nual HMDA data releases shows that there are persistent disparities in denial rates between white and m inor ity applicants. The table below re ports HMDA denial rates by ethnicity for home purchases involving govern ment-backed or guaranteed m ort gages and conventional mortgages. As this table shows, denial rates for black and Hispanic applicants were appreciably higher than those for whites in each year studied. The persistence of these disparate rejection rates has led many industry critics to accuse banks and other mort gage lenders of engaging in discrimi natory lending practices. However, HMDA data taken in isolation cannot shed much light into the question of discriminatory lending practices. This is because the HMDA releases do not provide other information crucial to the credit granting decision, such as the loan applicant’s credit history, net worth and general financial condition, and employment history. In response to this weakness in the raw HMDA data, the Federal Reserve Bank Loan denial rates G overnm ent-backed loans Applicant 1990 1991 1992 1993 Conventional loans 1990 (percent) 1991 1992 1993 (percent) A m e rica n In d ia n / A laskan N ative 22.5 22.1 17.5 17.5 22.4 27.3 26,6 27.8 A sia n /P a cific Isla n d er 12.8 12.5 13.5 11.7 15.0 15.3 14.6 Black 26.3 26.4 23.8 22.2 12.9 33.9 37.6 35.9 34.0 H ispanic 18.4 18.9 18.5 14.6 21.4 26.6 27.3 25.1 14.4 17.3 15.9 15.3 W h ite 12.1 16.3 12.8 O ther 18.4 16.3 16.0 17.8 19.0 19.9 21.0 23.1 J o in t (W h ite / M in o rity ) 14.1 15.9 14.8 14.7 14.9 17.5 17.6 17.3 11.8 Source: Federal Reserve System. of Boston conducted a study of mort gage denial rates in the Boston metro politan area based on a much wider range of data.1 Using a sample of ap plications from the 1990 Boston met ropolitan area HMDA files, Fed econo mists augmented the HMDA data with detailed information on applicants’ financial condition, credit history, personal characteristics, and the un employment rate in the industries in which applicants were employed. They then estimated the probability of a particular mortgage loan application being denied. Even with the addition of this infor mation, race still appeared to have a statistically significant effect on the probability of being denied. When other factors were held constant, the rejection rate for black and Hispanic applicants was about 1.6 times that for whites. Despite the interesting in sights provided by the Boston Fed analysis, some have challenged its conclusions, questioning both the reliability of the data and the underly ing empirical m odel.2 Given these concerns, the robustness of the study’s results remains an open ques tion. However, while the Boston study has been criticized, it represents the first rigorous study of the ques tion of discrimination in the loan approval decision. This Chicago Fed Letter reports the results of a recent Chicago Fed study reexam ining the role of race in the mortgage loan approval process.3 We began by carefully verifying and vali dating the data used in the Boston study. Then, unlike the Boston study, we analyzed the data using a model that tapped interaction effects among variables, examining approval proba bilities for various subsets of appli cants. While the Boston study found that Boston-area minority applicants were more likely to be rejected than white applicants with similar charac teristics, our study indicated that this was the case only for applicants at the margins of creditworthiness. Margin al black and Hispanic applicants ap peared to be held to higher quantita tive standards on such factors as credit history and debt ratios than were similarly situated marginal white applicants. The cultural affinity and thicker file hypotheses Despite the existence of legislation outlawing the use of irrelevant factors such as race and sex in mortgage lending decisions, lenders might still use these noneconomic facts as sig nals of whether to obtain additional information on marginal borrowers. Such information could ultimately influence the credit approval deci sion. One recent hypothesis suggests that a lack of “cultural affinity” be tween white loan officers and m inori ty applicants reduces the reliability and accuracy of the loan officers’ subjective evaluations, as a result of which white banks have more de m anding approval standards for black and Hispanic borrowers.4 According to this hypothesis, if the marginal cost to white lenders of obtaining addi tional credit information on white borrowers is lower than that associat ed with minority borrowers, then white loan officers will rely more heavily on (inexpensive) objective loan application information for their minority applicants than for their white applicants. As a result, white applicants with marginal objective indicators of creditworthiness will be more likely to be approved than mi nority applicants with identical mar ginal credit records, because the whites will have additional subjective information supporting their case. A somewhat similar hypothesis ad dresses the so-called “thicker file” phenom enon. Accepted marginal white mortgage applicants often have thicker loan application files than rejected marginal minorities. The common presum ption is that white applicants receive special counseling or extra coaching by sympathetic white loan officers, while minority applicants do not. The cultural affini ty and thicker file hypotheses both predict similar outcomes; they differ in that the cultural affinity hypothesis does not necessarily imply that whites receive special counseling and coach ing or even have thicker application files than minorities. The Chicago Fed study tested the cultural affinity hypothesis by examin ing whether loan officers perceive probability was 90%, blacks and His panics’ was 82%. These results suggest that for high-quality applicants, race was unim portant to lenders. It was the marginal minority applicant who was impacted by race. It appears, then, that lenders did treat the objective loan application inform ation of marginal black and Hispanic applicants differently from that of m arginal white applicants. In Our data and statistical model particular, credit history had a sub stantially greater im pact on the prob To correct for data errors and missing ability of loan approval for marginal values in the initial sample used in black and Hispanic applicants than the Boston study, we adopted an ex for marginal whites. While the ap tended version of the criteria devel by about oped by Carr and Megbolugbe.5 Our proval probability dropped minority 13 percentage points for a final sample contained 1,991 observa applicant undergoing an adverse tions: 1,726 approvals and 265 rejec change in credit history, the proba tions. The overall characteristics of bility dropped by only 5 percentage this subsample m irrored that of the points for a white applicant undergo original data set. ing a similar change. Our statistical analysis used a standard These results provide strong support logistic or logit regression model in for the cultural affinity hypothesis. which the lender’s loan approval On the other hand, they provide no decision is determ ined by a com pre support for the thicker file hypothe hensive set of borrower characteris sis. The estimated direct effect of tics. The model predicts the proba factors proxying for file thickness bility that a mortgage applicant with a on the probability of approval was given set of characteristics will receive loan approval. The variables entered insignificant. into the model were very similar to The study shows that race alone did those in the Boston Fed study, includ not determ ine the differences in ing standard financial ratios such as denial rates between applicants. To housing expenses relative to monthly analyze the determ inants more fully, income, total debt obligations relative however, one must consider the inter to monthly income, and other miscel action between race and several other laneous inform ation such as marital variables. In particular, the relation status, employment status, and wheth ship between race and creditworthi er the loan applicant had a cosigner. ness is key. The impact of race on the creditworthiness of a loan applicant will depend on the level of the appli Race effects cant’s ratio of total monthly obliga The results of our study indicated that tions to total monthly income. We when the credit history of an applicant com puted the effect of race on creditwas classified as good (i.e., the appli worthiness within two levels of the cant had no accounts 60 or more days debt obligation ratio—the lowest past due), the approval probability for quartile and the third quartile. For white applicants versus black and His applicants with bad credit histories, panic applicants was not appreciably the effect of race on denial rates was different—96% for whites and 95% for small and statistically insignificant as blacks and Hispanics. On the other long as the obligation-to-income ratio hand, when credit history was classi was low or favorable. However, when fied as bad (i.e., the applicant had one the ratio increased to an unfavorable or more accounts 60 or more days past level, the racial effect became larger due), the difference in approval prob and significantly significant, with ability was 8 percentage points in favor black and Hispanic applicants being of white applicants: Whites’ approval objective inform ation such as credit history and leverage ratios differently for minority applicants than for whites. In addition, using a measure of applicants’ prior credit m arket experience, the study examined the thicker file hypothesis. O ur results provided support for the cultural affinity hypothesis but not the thicker file hypothesis. adversely affected. For example, when the obligation-to-income ratio changed from a favorable 30% to an unfavorable 60%, the approval proba bility for marginal black and Hispanic applicants decreased by 72.1 percent age points, com pared to only a 24.5 percentage point reduction for mar ginal white applicants. Thus, as the ratio became less favorable, marginal white applicants appeared to be judged more creditworthy than were similarly situated marginal black and Hispanic applicants. These findings lend additional support to the cultur al affinity hypothesis. Other results The other findings reported in the study are consistent with traditional expectations. Specifically, increases in the ratio of total debt obligations to monthly income, evidence of prior public record defaults, self-employ ment, and having a less than favor able debt repayment history all low ered the probability of approval. So did being unm arried, being em ployed in an industry with a high probability of unemployment, and purchasing multifamily property. On the other hand, gender, the appli cant’s num ber of dependents, and the racial or economic status of the neighborhood in which the property was located had no significant impact on the probability of approval. The finding that neighborhood racial or economic status had no impact on approval probability implies that the loan officers in the sample did not engage in the practice of redlining, i.e., denying loans on the basis of the racial or economic status of the neighborhood in which the property was located. Implications Overall, the study suggests that the marginal minority applicants in the sample were held to higher quantita tive credit standards than were m ar ginal white applicants. This is a m ore precise finding than that of the Boston Fed’s study. O ur conclusion is im plied by the behavior of the race variable under differing sets of con ditioning inform ation. Race was not a significant factor in the accept/ reject decision for applicants with good credit profiles. However, it was very significant for those with bad credit histories, and a bad credit history, in turn, lowered the proba bility of approval for minorities m uch more than it did for whites. Similarly, race became an im portant factor only for those with high ratios of monthly debt to income. Minority applicants with high debt ratios were very much less likely to receive loan approval than similarly situated white applicants. These findings are consistent with the existence of a cultural affinity be tween white lending officers and white applicants, and a cultural gap between white loan officers and mar ginal minority applicants. Bridging or closing this gap will require more research to identify the factors that determ ine the repayment patterns of marginal minority and non-traditional borrowers. The search for evidence of racial discrimination in economic life is exceedingly difficult but can be made more manageable with the aid of statistical models. W hen used appro priately, these models can help regu lators and researchers uncover dis criminatory practices in mortgage lending. However, they should not be treated as replacements for sound judgm ent and inquiry. If one incor porates additional information into these models such as that included in bank underwriting policies and guide lines or other “omitted variables,” the models sometimes yield different results.6 Thus, in using statistical models in regulatory processes, poli cymakers face a classical problem: They must decide whether to expend additional resources to acquire more comprehensive information to build more customized models, when those models may add little value to the policymaking process. —William C. H unter Senior Vice President and Director of Research 1Alicia H. Munnell, Lynne E. Browne, James McEneaney, and Geoffrey Tootell, “Mortgage lending in Boston: Interpret ing the data,” Federal Reserve Bank of Boston, working paper, 1992. 2David K. Horne, “Evaluating the role of race in mortgage lending,” FDICBanking Review, Vol. 7, Spring/Summer 1994, pp. 1-15, and Stan Liebowitz, “A study that deserves no credit,” The Wall Street Jour nal, September 1, 1993, p. A14. William C. Hunter and Mary Beth Walk er, “The cultural affinity hypothesis and mortgage lending decisions,” Federal Reserve Bank of Chicago, working paper, 1995, forthcoming. 4Charles W. Calomiris, Charles M. Kahn, and Stanley D. Longhofer, “Housingfinance intervention and private incen tives: Helping minorities and the poor,” Journal of Money, Credit and Banking, Vol. 26, August 1994, pp. 634-674. 5 James H. Carr and Isaac F. Megbolugbe, “The Federal Reserve Bank study on mortgage lending revisited,” Federal National Mortgage Association, Office of Housing Research, working paper, 1993. 6See, for example, Mitchell Stengel and Dennis Glennon, “Evaluating statistical models of mortgage lending discrimina tion: A bank-specific analysis,” Office of the Comptroller of the Currency, Eco nomic and Policy Analysis, working pa per no. 95-3, May 1995. Michael H. Moskow, President, William C. Hunter, Senior Vice President and Director of Research; David R. Allardice, Vice President, regional programs; Douglas Evanoff, Assistant Vice President, financial studies; Charles Evans and Kenneth Kuttner, Assistant Vice Presidents, macroeconomic policy research; Daniel Sullivan, Assistant Vice President, microeconomic policy research; Anne Weaver, Manager, administration; Janice Weiss, Editor. Chicago Fed Letter is published monthly by the Research Department of the Federal Reserve Bank of Chicago. The views expressed are the authors’ and are not necessarily those of the Federal Reserve Bank of Chicago or the Federal Reserve System. Articles may be reprinted if the source is credited and the Research Department is provided with copies of the reprints. Chicago Fed Letter is available without charge from the Public Information Center, Federal Reserve Bank of Chicago, P.O. Box 834, Chicago, Illinois, 60690-0834, (312) 322-5111. ISSN 0895-0164 Tracking Midwest manufacturing activity Purchasing managers’ surveys (production index) 80 Manufacturing output indexes (1987=100) Apr. MMI IP Month ago Year ago 138.6 123.3 141.6 132.2 118.4 124.0 70 Motor vehicle production (millions, seasonally adj. annual rate) Apr. Month ago Year ago Cars 6.5 7.1 6.7 Light trucks 4.9 5.6 4.2 Purchasing managers’ surveys: net % reporting production growth May Month ago 60 50 Year ago MW 54.2 60.2 71.7 U.S. 47.9 55.3 62.2 40 1992 1993 Inventory paring prom pted retrenchm ent in Midwest industrial output growth in recent months. The composite index for purchasing m anagers’ surveys in Chicago, Detroit, and Milwaukee fell back significantly in March, April, and May. This indicator continued to depict positive growth in the m anufacturing sector, but just barely. Even after its recent decline, the Mid west index remains in line with or stronger than its level during previous epi sodes of slowing growth in late 1991, mid-1992, and mid-1993. 1994 1995 Sources: The Midwest Manufacturing Index (MMI) is a composite index of 15 industries, based on monthly hours worked and kilowatt hours. IP rep resents the Federal Reserve Board industrial pro duction index for the U.S. manufacturing sector. Autos and light trucks are measured in annualized units, using seasonal adjustments developed by the Board. The purchasing managers’ survey data for the Midwest are weighted averages of the sea sonally adjusted production components from the Chicago, Detroit, and Milwaukee Purchasing Man agers’ Association surveys, with assistance from Bishop Associates, Comerica, and the University of Wisconsin-Milwaukee. IU9-ZZZ (2I£) PF80-06909 siouipi ‘oStesuo P£8 xoH O d joiuoL) uopninjojuj oiyqnj OOVOIH3 TO MNW TAdTSTd lYHTQTT T > n o r] p a j o b t o i i p )