ple-selection bias and the power of the default approach to detect discrimina- tion, and the use of data on government-insured loans to detect discrimination in the conventional-loan sector.
Unobserved Underwriting Variables
The most extreme form of the default approach to studying discrimination, which is illustrated in Becker’s (1993) column, claims that, in the presence of discrimination, the average default rate for minorities will be lower than the average default rate for whites. This version of the default approach makes no sense at all because the pool of minority mortgage applications is of lower qual- ity than the pool of white mortgage applications. (See Peterson 1981; Galster 1993; Ferguson and Peters 1995; Tootell 1996b.) For example, minority appli- cants tend to average larger debt burdens, higher loan-to-value ratios, and poorer credit histories than white applications (based on the Boston Fed Study’s data). Even if lenders do not discriminate, therefore, the pool of approved minority applications will be of lower quality than the pool of approved white loans. This conclusion reflects, of course, a type of omitted- variable bias; intergroup comparisons of average default rates give biased results because they do not control for credit qualifications.
This point is illustrated by figure 1 at the end of this chapter. The horizontal axis represents the quality of loan applications, and the vertical axis represents the fraction (or density) of applications that have this quality. The distribution of minority and white loan applications are shown separately, with the minority distribution drawn so that minority loan applications are lower quality than white applications, on average. The quality cutoff below which loan applications are denied is labeled C. This cutoff is the same for whites and minorities, which
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implies no mortgage lending discrimination based on minority status. The aver- age quality of approved white applications, which is the mean of the white qual- ity distribution above C, is substantially higher than the average quality of approved minority applications because so many high-quality white applicants applied for and received mortgages. These high-quality white applicants pull up the average quality of white mortgages and drive down the average white default rate. Discrimination against minorities lowers the average minority default rate, but might not lower it enough to offset the higher average quality of white loan recipients. Thus, a lower average default rate for whites cannot be interpreted as evidence that discrimination does not exist.
Van Order and Zorn (1995) agree with this point, but also point out that lower default rates for minorities can provide evidence that discrimination exists. Given the lower average quality of minority applications, minority mortgages could only experience lower default rates if minorities were held to a substantially higher underwriting standard. To put it another way, a lower default rate for minorities than for whites is sufficient but not necessary to show discrimina- tion. In figure 2, the cutoff for minority applications is D + C, where D repre- sents the increased underwriting standard for minorities. The average quality of minority mortgages can only exceed the average quality of white mortgages if D is very large, that is, if substantial discrimination exists in mortgage lending.
Van Order and Zorn (1995) examine default rates across the country. In the southeastern United States, they find that default rates are either unaffected by or fall with the share of black households in a census tract. They also observe that HMDA loan application rejection rates fall with black concentration in all regions, including the Southeast. They conclude that racial differences in default rates in the Southeast do provide evidence of discrimination, because the pool of minority applications is of lower quality than the pool of white applications and yet minority default rates are equal to or lower than white default rates. As noted earlier, Van Order and Zorn recognize that equal or higher default rates for minority mortgages do not provide evidence that lenders treat white and minority applicants equally and therefore do not contradict other findings of discrimination.
Berkovec, Canner, Gabriel, and Hannan (1994) attempt to avoid the prob- lems inherent in examining average default rates, by using statistical analysis to examine whether the marginal minority applicant is treated the same as the marginal white applicant. They attempt to identify a marginal buyer by using regression techniques to control for many variables that lenders may consider during the underwriting process. Using a sample of FHA mortgages from 1987 through 1989, they find that minorities are more likely to default after control- ling for the underwriting variables that are available in the data set of FHA mortgages. On the basis of this finding, they reject the hypothesis that minori- ties encounter discrimination.
Regression analysis controls for variables that are observed by the analyst and compares minority and white treatment based on unobserved factors, which may include borrower characteristics observed and used by the lender for underwriting but not observed by the analyst, henceforth called unobserved underwriting variables, along with lender differences in underwriting criteria and behavior. This exercise essentially replicates the comparison of average
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default rates, therefore, except that the influence of observed underwriting vari- ables has been removed before the calculation of intergroup differences in default. Figure 3 is constructed in the same way as figures 1 and 2, except that the horizontal axis now represents the quality of loan applications based on unobserved underwriting variables and, as assumed by Berkovec et al. (1994), white and minority applications have the same average quality when only these unobserved underwriting variables are considered. In this case, even if minor- ity loan applications are worse on observed underwriting variables, having higher underwriting standards for minorities results in a pool of approved minority mortgages that has higher-than-average quality based on unobserved underwriting variables than does the pool of white mortgages.
The assumption of equal unobserved loan quality is critical. If minority applications have lower quality on the basis of unobserved underwriting vari- ables, figure 1 still applies, so long as the horizontal axis is relabeled “loan qual- ity based on unobserved underwriting variables.” In this case, therefore, average quality can be lower for minority than for white loans even if lenders practice discrimination. In effect, the Berkovec et al. conclusion that there is no discrimination is conditional on a set of very strong assumptions, includ- ing no difference in unobserved underwriting variables for blacks and whites.
Note that the impact of unobserved underwriting variables on default is actually the flip side of the omitted-variable bias problem in an analysis of mort- gage application denials. If minority applications are lower quality based on unobserved underwriting variables, a loan denial analysis will indicate a higher likelihood of denial for blacks even if lenders do not discriminate. With omit- ted underwriting variables, therefore, an analysis of loan denials is likely to overstate discrimination and an analysis of loan defaults is likely to understate discrimination. A key implication of this point is that any analysis based on loan performance or default must control for the same set of underwriting vari- ables used in an unbiased loan denial equation. Otherwise, the loan perfor- mance or default analysis may suffer from an omitted-variable bias even if the loan denial equation does not. Unlike the Boston Fed Study, for example, Berkovec et al. (1994, 1998) do not control for applicants’ credit history. In the Boston Fed Study’s data, minority applicants have worse credit history than white applicants, and the credit history variables are highly significant in pre- dicting denials. These results explicitly contradict Berkovec et al.’s key assump- tion and undermine their conclusion concerning discrimination.