Are Wisconsin Public Employees Underpaid?

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Ezra Klein and a variety of other thoughtful liberal bloggers have been pointing to an Economic Policy Institute analysis that they claim demonstrates that Wisconsin’s public employees, even after adjusting for benefits and hours worked, face a “compensation penalty of 5% for choosing to work in the public sector.” Unfortunately, when you get under the hood, the study shows no such thing.

Klein links to an executive summary to support his claim, but reading the actual paper by Jeffrey H. Keefe is instructive. Keefe took a representative sample of Wisconsin workers, built a regression model that relates “fundamental personal characteristics and labor market skills” to compensation, and then compared public- to private-sector employees after “controlling” for these factors. As far as I can see, the factors adjusted for were: years of education, years of experience, gender, race, ethnicity, disability, size of organization where the employee works, and hours worked per year. Stripped of jargon, what Keefe asserts is that, on average, any two individuals with identical scores on each of these listed characteristics “should” be paid the same amount. 

But consider Bob and Joe, two hypothetical non-disabled white males, each of whom went to work at Kohl’s Wisconsin headquarters in the summer of 2000, immediately after graduating from the University of Wisconsin. They have both remained there ever since, and each works about 50 hours per week. Bob makes $65,000 per year, and Joe makes $62,000 per year. Could you conclude that Joe is undercompensated versus Bob? Do you have enough information to know the “fundamental personal characteristics and labor market skills” of each to that degree of precision? Suppose I told you that Bob is an accountant, and Joe is a merchandise buyer. 

Even if Bob and Joe are illustrative stand-ins for large groups of employees for whom idiosyncratic differences should average out, if there are systematic differences in the market realities of the skills, talents, work orientation, and the like demanded by accountants as compared to buyers, then I can’t assert that either group is underpaid or overpaid because the average salary is 5 percent different between these two groups.

And this hypothetical example considers people with a degree from the same school working in the same industry at the same company in the same town, just in different job classifications. Keefe is considering almost any full-time employee in Wisconsin with the identical years of education, race, gender, etc., as providing labor of equivalent market value, whether they are theoretical physicists, police officers, retail-store managers, accountants, salespeople, or anything else. Whether they work in Milwaukee, Madison, or a small town with a much lower cost of living. Whether their job is high-stress or low-stress. Whether they face a constant, realistic risk of being laid off any given year, or close to lifetime employment. Whether their years of education for the job are in molecular biology or the sociology of dance. Whether they do unpredictable shift work in a factory, or 9–5 desk work in an office with the option to telecommute one day per week. 

Keefe claims — without adjusting for an all-but-infinite number of such relevant potential differences between the weight-average public-sector worker and the weight-average private-sector worker — that his analysis is precise enough to ascribe a 5 percent difference in compensation to a public-sector-compensation “penalty.”

And his use of the statistical tests that he claims show that the total public–private compensation gap is “statistically significant” are worse than useless; they are misleading. The whole question — as is obvious even to untrained observers — is whether or not there are material systematic differences between the public and private employee that are not captured by the list of coefficients in his regression model.  His statistical tests simply assume that there are not.

I don’t know if Wisconsin’s public employees are underpaid, overpaid, or paid just right. But this study sure doesn’t answer the question.

Jim Manzi — Jim Manzi is CEO of Applied Predictive Technologies (APT), an applied artificial intelligence software company. Prior to founding APT, Mr. Manzi was a Vice President at Mercer Management Consulting where ...

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