The Dodd-Frank Wall Street Reform and Consumer Protection Act, which passed in the aftermath of the 2008 financial implosion, includes a mandate that public companies disclose their median employee compensation as well as the ratio comparing that with the pay of their CEOs.
Large multinational corporations and many others bristled at the potential costs, but many investors supported the new rule. Academic research has suggested that the ratio could predict employee morale, board independence, corporate effectiveness and, ultimately, profits. Investors in socially responsible funds, meanwhile, supported the rule because it encourages companies to pay a living wage.
The concern about expense proved legitimate; collecting and calculating median income was costly for businesses, and regulators found themselves searching for an efficient and fair way to implement the rule.
Forces on both sides of the issue – corporate attorneys and lobbyists battling the law, and SEC regulators charged with enforcing it – were mostly lawyers with little knowledge of statistics. Meanwhile, quantitatively trained experts with the mathematical skills to arrive at a solution lacked the legal training to know whether and how such a solution could be legally justified. Things had reached an impasse.
Enter Stanford Engineering doctoral student Michael Ohlrogge, a joint degree student pursuing a PhD in Stanford's Department of Management Science and Engineering and a law degree from Stanford Law School.
"The concept of a median salary sounds simple on the surface – you calculate all of the salaries and find the employee in the middle, right?" Ohlrogge said. "But when a company has hundreds of thousands of employees, many in different countries being paid in different currencies and so forth, things get complicated pretty quickly."
Ohlrogge saw a way out. He began to contemplate how the SEC might use statistical sampling to calculate the required median compensation at a reasonable cost. His quantitative training in engineering had taught him that highly accurate statistical estimates could be derived using relatively small samples drawn from large populations. On the other hand, his legal training taught him that the SEC has broad discretion in interpreting and implementing such laws as it deems appropriate.
"You can actually get a very accurate median estimate by sampling as little as one-half of 1 percent of a company's workforce, even for massive multi-national companies," Ohlrogge said.
Ohlrogge submitted several comment letters to the SEC, building his case for statistical sampling. He analyzed legal precedent to argue that, despite there being no specific mention of statistical sampling in Dodd-Frank, the SEC would be justified in using sampling. Then, relying on his engineering skills, he crafted the sampling technique companies could use to estimate median income.
Ohlrogge and his Stanford Law School professor, Joseph Grundfest, a former SEC Commissioner, met via teleconference with the SEC's director of corporate finance and her staff. Ohlrogge answered questions, defending his proposal from both a quantitative and a legal standpoint.
"It's unusual in this business for a graduate student to play such an instrumental role in the shaping of a law, and it's extremely unusual for that contribution to actually make it into the law," said Grundfest. "It took Michael's dual capabilities in statistics and in law to make it happen."
Ultimately, the SEC agreed, specifically citing Ohlrogge's work when it allowed companies to use statistical sampling to report the required median figures. In its coverage of the SEC’s proposed implementation of this Dodd-Frank rule, The New York Times cited Ohlrogge's work as did several trade publications.
"Many companies, investors and SEC staff were skeptical of Michael's ideas," said Kay Giesecke, an associate professor at Stanford Engineering and Ohlrogge's advisor. "But he proved them wrong."
"People tell me that what you learn in a university isn't useful in the real world and that you can't impact policy. I think those sentiments are wrong," Ohlrogge said. "U.S. regulatory agencies need to hear from individuals with expertise who have no direct financial stake in how regulations are written. The skills and insights students acquire at Stanford may help supply the missing piece of an important puzzle somewhere."