Regulation: Cooked Books

A government study "proving" discrimination in bank loans doesn't add up


"So much injustice. so little time." That is the official battle cry of the "discrimination" police now running amok in the Clinton administration. That they may have little time left perhaps ought to give them pause, but do not bet on it: A crusade against "discrimination" is a gold mine for bureaucrats and ideologues in pursuit of bigger budgets and enhanced political power for themselves. That the greater spending and coercive authority derive from so lofty a moral goal as "antidiscrimination" creates both blindness and dishonesty on the part of the morally pure.

Consider, for instance, the 1992 study of racial discrimination in mortgage lending published by the Federal Reserve Bank of Boston. This plainly politicized paper has thrust the lending discrimination issue to the forefront of regulatory policy in banking, notwithstanding an econometric model that is highly suspect conceptually and poor as a predictor, variables defined poorly, and findings that disappear upon deletion of six observations out of about 3,000.

Moreover, the Boston Fed's study data include a substantial number of obvious and probable errors. For example, there are no fewer than 22 cases implying loans with large negative interest rates. One applicant with annual income of $34,000 supposedly received a $400,000 loan, to be repaid in 12 payments of $154. Another $140,000 loan was supposedly approved with a total of eight payments under $1,500.

One approved application was for a loan of $271,000 for someone with an annual income of $11,000; but the dataset indicates that this person's ratios of housing debt payments to income and total debt payments to income are zero. Another observation is similar: a loan of $245,000 was approved for an individual earning $47,000 per year, but the "front end" ratio of housing debt payments to income supposedly is zero. In all, there are no fewer than 13 large loans approved for individuals with modest incomes but with such ratios equal to zero. Other observations record "back end" ratios of total debt obligations to income lower than the ratio of only mortgage debt to income, an obvious inconsistency.

One applicant with annual income of $4,000 was approved for a $181,000 loan, while another applicant with annual income of $5,000 received a loan of $148,000. Those two latter cases, and others like them, may merely indicate that the lenders may have had other information about the borrowers' future income prospects. But even if that were the case, the Boston Fed's statistical analysis would not take such additional information into account, and so would yield misleading findings. It is just as possible, however, that the typist omitted a zero.

Indeed, some of the data seem to be obvious numerical errors. One loan was reportedly approved for $979,000 for a house costing $118,000; the actual loan amount was $97,900, as reconstructed from various data sources. A $3,115,000 loan was supposedly approved for the purchase of a $445,000 house; the actual loan was for $311,500. Another approved loan was for a home purchase listed in the dataset at a price of $124,000; the actual price was $240,000, so that the true loan/ value ratio of 65 percent was recorded instead at 125 percent.

One applicant supposedly was approved for a $55,000 loan to purchase a $174,000 home, even though his annual income was $30,000 and his net worth was ?$7.9 million. Four other applicants with net worths between ?$1.4 million and ?$4.3 million reportedly were approved for loans even though their annual incomes averaged only $95,000. All of the above cases involved loans approved for white applicants, a fact that may have biased the Boston Fed's findings.

Even more curious are the cases in which applications are recorded as having been denied, but in which the "denied" loans are recorded as loans subsequently sold on the secondary market. The Boston Fed's dataset is a subset of the Home Mortgage Disclosure Act data for 1990; in the HMDA data, there are 15 cases in which applications are recorded as denied but then sold on the secondary market. Of these 15 obvious inconsistencies, none is from a Hispanic applicant and one is from a black applicant. But in the Boston Fed's dataset—again, supposedly a subset of the HMDA data—there are 43 applications recorded as denied and then sold on the secondary market, of which 40 are black or Hispanic. That inconsistency remains to be explained.

It is at least plausible that other errors of similar magnitude exist in the Boston Fed's data along with numerous errors less obvious. Monthly and annual income figures often are inconsistent by substantial proportions. Another serious problem is presented by special programs for affordable housing. Applicants for such programs are disproportionately members of minority groups, and applicants are often found to be overqualified for the special programs. The Boston Fed study defines such overqualified applicants as "rejected" for mortgage loans even though the "rejection" has nothing to do with a conventional mortgage application.

More generally, David Horne of the Federal Reserve Board of Governors reports that data errors of varying magnitudes were found by examiners in 58 percent of the applications actually denied but predicted by the Boston Fed's econometric model to be approved. Ted Day and Stan Liebowitz of the University of Texas at Dallas report that of the 2,932 applications from the Boston Fed data that they examined, "hundreds" failed to pass various consistency tests.

Well, who cares about a few mistakes when "discrimination" is the target and bigger budgets are the goal? Accordingly, 10 federal agencies published a "Policy Statement On Discrimination In Lending," earlier this year. That 10 federal bureaus have clambered aboard this bandwagon says more about political and budgetary potential than about actual illegal discrimination by lending institutions. The "Policy Statement" declares, "The 1992 Federal Reserve Bank of Boston study on lending discrimination, Congressional hearings, and agency investigations have indicated that race is a factor in some lending decisions."

It is not clear whether by "indicated" the authors mean "demonstrated" or merely "asserted." The "Policy Statement" is based upon the Fair Housing Act and the Equal Credit Opportunity Act, the two statutes that specifically proscribe discrimination in lending. Liability under the two statutes is civil, not criminal, thus reducing the evidentiary standard required to prove discrimination. This evidence can be of "overt" discrimination, of "disparate treatment" on the basis of such prohibited characteristics as skin color, or of a "disparate impact" on applicants correlated with prohibited characteristics. Such disparate impacts would be illegal if "not justified by business necessity" or if a "less discriminatory alternative" exists.

The statement asserts that "Disparate treatment may more likely occur in the treatment of applicants who are neither clearly well-qualified nor clearly unqualified," because such cases leave more room for lender discretion in assistance and approval. Of course, "gray area" cases leave more room for discretion on the part of the enforcement agencies as well.

The likelihood of such enforcement discretion is enhanced by the assertion in the statement that "a pattern or practice of disparate treatment on a prohibited basis may also be established through a valid statistical analysis of detailed loan file information, provided that the analysis controls for possible legitimate explanations for differences in treatment."

That the interpretation of such econometric evidence is both science and art is clear to anyone familiar with the economic analysis of data. But will the agencies' lawyers understand this? Will the congressmen and senators considering the agencies' budget requests understand it?

Even without explicit discriminatory intent, some lending practices could have disparate impacts correlated with race. The statement makes it clear that such practices with disparate impact may be illegal if they are not justified by "business necessity" or if there exists a "less discriminatory alternative." But it is not clear just what constitutes a "business necessity." The "Policy Statement" states only that "factors that may be relevant to the justification [of business necessity] could include cost and profitability." If it means business survival, it is hard to imagine what in the context of lending discrimination might be "necessary," that is, any decision without which bankruptcy becomes certain.

Banks' lower profits caused by regulation would eventually drive up interest rates, causing lower demand for loans. Under such conditions, all lenders might simply lend less, and none would have to leave the market. Is avoidance of that effect "necessary"?

In any event, it would be hard to know or demonstrate that a practice is necessary until it's challenged by regulators. And even with demonstration of an undefined business necessity, a lending practice still might be judged illegal if a "less discriminatory alternative" exists. It is unclear from the "Policy Statement" how to compare a given lending practice with an alternative based on the degree of discrimination they yield. Perhaps a "less discriminatory" alternative is one that results in more lending to members of protected groups; but since a given bank can lend only so much, more lending to one group necessarily leaves less credit (that is, more "discrimination") for another. Besides, if a practice is truly necessary, then by definition there is no alternative, whether less discriminatory or not.

The section on "disparate impact" in the statement also leaves dangerously wide scope for regulatory discretion: "Frequently [the existence of a disparate impact] is [established] through a quantitative or statistical analysis….Not every member of the group must be adversely affected for the practice to have a disparate impact. Evidence of discriminatory intent is not necessary to establish that a policy or practice adopted or implemented by a lender that has a disparate impact is in violation of the [FHA] or ECOA." This means that no criminal intent is necessary for violation of this law, according to the bureaucrats, and that discovery of violation is to be made through the use of subjective numerical games played by ideologues of the sort who have already shown themselves in the Boston Fed study to be pretty fast and loose with their analysis.

Under such standards, can lenders know if they are in compliance? If not, then it is likely that they will be driven inexorably to adopt lending quotas. The statement notes that "a reason to believe" that the ECOA has been violated requires that "a reasonable person would conclude from an examination of all credible information available that discrimination has occurred." Is it reasonable to expect "reasonable" persons to agree on the implications of econometric findings? It seems reasonable to doubt it.

The "Policy Statement" notes that HMDA data don't provide enough information for statistical analysis of discrimination because the data omit such important variables as credit histories and debt ratios. Nevertheless, the statement argues that, "HMDA data are useful…for identifying lenders whose practices may warrant investigation for compliance with fair lending laws." Given the ambiguity inherent in data on lending decisions, and given the political volatility of the discrimination issue, such use of HMDA data in the search for culprits can prove perverse.

For example, suppose two lenders—the Equal Opportunity Bank and the Bigotry Bank—are open for business. Minority applicants know that only the most wealthy and famous among them will be approved for a loan at the Bigotry Bank. Accordingly, almost all minority applicants waste no time and effort there and instead attempt to do business with the Equal Opportunity Bank. The only minority applicants applying at the Bigotry Bank are those sufficiently wealthy or famous to be guaranteed approval. The Bigotry Bank will have a spotless record—all of its minority loan applications will be approved—while the Equal Opportunity Bank will have a substantial number of denials. The use of HMDA data to find discrimination malefactors is likely to ensnare lenders analogous to the Equal Opportunity Bank precisely because of their reputations for fairness.

On the basis of poor data and analysis, regulators now are delaying bank mergers until lenders accused of bias establish special funds for minority lending or for "compensatory" payments to past loan applicants who were denied credit and agree to enhance marketing and other efforts among potential minority customers. Lawsuits charging past racial discrimination are being settled along similar lines.

In D.C., for example, the Chevy Chase Federal Savings Bank recently settled, admitting no wrongdoing, with the federal government for allegedly ignoring predominantly black neighborhoods in its branch placement. No specific acts of discrimination were even alleged.

As part of its penance for not making business decisions that please the feds, Chevy Chase Federal Savings must commit $140 million in home loans—at lower than market rates—to areas dictated by regulators. Those sorts of charges, adverse publicity, defense costs, and expensive settlements work as a tax on lenders. The long-run implications for access to capital of discrimination accusations based on shoddy data and poor analysis are unlikely to prove salutary for anyone, even "protected" minorities.

Do-goodism is as old as sin. In the do-gooders' rhetoric, the problems of our inner cities are not the fruit of oppressive taxation and regulation, destructive welfare policies, the mindless drug crusade, or an education system monopolized by a government insatiable in its quest for coercive and confiscatory power. Nor is the cause our professional political class, the central characteristics of which are ignorance, ineptitude, and an all-powerful instinct for self-preservation. No, the cause is "discrimination" practiced by evil capitalists.

Analytic sloppiness, dishonesty, verdict first/trial later, and all the other hallmarks of media politics are much in evidence in the attacks on lending "discrimination." Nonetheless, the bureaucrats and the politicians should not be called liars. Instead, they are truth-challenged.

Benjamin Zycher is vice president for research at the Milken Institute for Job and Capital Formation in Santa Monica, California. This essay is based upon an article by Benjamin Zycher and Timothy A. Wolfe in the 1994 Number 2 issue of Regulation.