We all know that discrimination violates various federal and state laws, but the FTC has been insisting for a while now that it also violates Section 5. A recent joint complaint the agency brought with the State of Wisconsin against a local car dealer proves it wasn’t kidding and also raises interesting issues regarding how the agency intends to prove unlawful discrimination under Section 5.
The car dealer operated in an area of Wisconsin with a large American Indian population. The complaint alleges that the dealer obtained interest rate quotes for auto loans from third-party lenders but its reps had discretion to mark up those rates, with the dealer benefiting from any mark-up. In addition, as any car shopper knows, the dealer offered a host of optional add-on products. The complaint goes on to allege that American Indian customers had their loan rates marked up 0.34% higher than “similarly situated” non-Latino white customers. In addition, it alleges that American Indian customers paid on average $1,300 more for add-ons than did non-Latino white customers.
The FTC alleged that such unlawful discrimination was “unfair” in violation of Section 5. At the same time, the case raises fascinating issues regarding how the agency intends to prove unlawful discrimination. First, there is the use of statistics. Winston Churchill supposedly said, “[T]he only statistics you can trust are those you falsified yourself.” And there is the well-known phrase, “lies, damned lies and statistics.” But love them or hate them, statistics do have a role to play in the law. The FTC’s complaint raises more questions than it answers about what that role is for companies seeking to avoid an unfairness complaint for discrimination. Why did the agency compare American Indians to non-Latino white customers? How would the statistics have looked if the FTC compared American Indians to all other non-American Indian customers? And how did the agency determine what made customers “similarly situated?” Is the FTC going to adopt an approach toward the use of statistics similar to what DOJ utilizes for discrimination? If so, we all have a lot to learn. Below is an excerpt from the Civil Rights Division’s discussion about whether a statistical disparity is significant.
While there is no “rigid mathematical formula” for determining whether a disparity is significant, courts have adopted various tests to aid them in making this determination. For example, some courts have looked to whether the disparity is statistically significant. Hazelwood, 433 U.S. at 308 n.14 (an inference of discrimination will generally arise where “‘the difference between the expected value and the observed number is greater than two or three standard deviations.’”) Other courts have looked at whether the disparity is both statistically and practically significant. See Thomas v. Metroflight, Inc., 814 F.2d 1506, 1510 n.4 (10th Cir. 1987) (suggesting that courts may require, in addition to statistical significance, that the observed disparity be substantial). Still other courts have recognized the usefulness of multiple regression analyses, a statistical tool for understanding the relationship between two or more variables where there are several possible explanations for a given outcome, which, in turn, aids in isolating the most relevant variable and determining its effect on the outcome.
Admit it: Reading that hurt your brain a bit. At the same time, the FTC may have buried the lead. After wading through a bunch of statistics, one gets to a paragraph in the complaint that alleges staff at the dealership had brought the issue to the attention of senior management without success. So perhaps there was more here than just a statistical case.
The FTC’s case regarding the charging of undisclosed add-ons relied not just on statistical differences but also on an apparent survey of recent customers, which found, based on their recollection of their experience at the dealership, that many were charged for add-on products without authorization or as a result of deception. While there is no record of the actual survey that was conducted, research shows that memory of sales presentations fades very quickly. One expert who helps people create memorable presentations cites a study of 1,500 people who, 48 hours after a PowerPoint presentation, were on average only able to recall four slides out of 20. We can only wonder how the agency would react to a company under investigation submitting such a survey in its defense.
Now, none of this is intended to knock what the agency is trying to do. Discrimination is a terrible thing, and the government ought to use all the tools it has available to combat it. But if the agency is going to go down this path, as it apparently intends to, advertisers would be well served with some guidance on how the agency intends to determine whether an advertiser has acted in a discriminatory fashion.
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