Ezra Klein:
“Republicans say that public-sector employees have become a privileged class that overburdened taxpayers,” write Karen Tumulty and Brady Dennis. The question, of course, is whether it’s true. Consider this analysis the Economic Policy Institute conducted comparing total compensation — that is to say, wages and health-care benefits and pensions — among public and private workers in Wisconsin. To get an apples-to-apples comparison, the study’s author controlled for experience, organizational size, gender, race, ethnicity, citizenship and disability, and then sorted the results by education
[…]
If you prefer it in non-graph form: “Wisconsin public-sector workers face an annual compensation penalty of 11%. Adjusting for the slightly fewer hours worked per week on average, these public workers still face a compensation penalty of 5% for choosing to work in the public sector.”
Jim Manzi at The American Scene:
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, and 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% 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% 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.
Jason Richwine at Heritage:
Manzi is referring to “the human capital model,” which holds that workers are paid according to their skills and personal characteristics, like education and experience. Most scholars—including Andrew, myself, and Heritage’s James Sherk—use it to compare the wages of the public and private sectors. If the public sector still earns more than the private after controlling for a variety of factors, then it is said to be “overpaid” in wages. But because we cannot control for everything, Manzi is saying, the technique is not very useful.
His critique is reasonable enough, but overwrought. The human capital model has been around for three decades, and it is unlikely that economists have failed to uncover important variables that would drastically change its results. Nevertheless, there are other techniques that address most of Manzi’s concerns. An upcoming Heritage Foundation report uses a “fixed effects” approach, which follows the same people over time as they switch between the private and federal sectors. By looking at how the same person’s wage changes when he moves between sectors, a lot of unobservable traits—intelligence, extroversion, etc.—are accounted for.
In order to capture fringe benefits as well as wages, economists have also used quit rates and job queues. If public workers quit less often than private workers, we can infer (with some qualifications, of course) that there are not better options available to them. Similarly, if many more applicants apply for government jobs than there are positions—creating a “queue”—then we know that government jobs are highly desirable. Of course no methodology is perfect, but the scholarly literature can tell us a lot about pay comparisons. Andrew and I discussed this work in detail in a recent Weekly Standard article.
John Sides:
From one perspective, sure, I agree that a statistical analysis of the sort described above based on observational data can never be a true direct comparison. (Not to mention the difficulty of classifying people like me who work in the quasi-public sector.) But if you take things from the other direction, this sort of study can be valuable.
What do I mean by “the other direction,” you might ask? I mean, suppose you start, as people do, with raw numbers: Salary plus benefits = X% of the state budget. The state has Y number of employees. Average income of all Wisconsinites is Z. Then you start adjusting for hours worked, ages of the employees, etc etc, and . . . you end up with Keefe’s analysis.
My point is, people are going to make some comparisons. Comparisons aren’t so dumb as long as you realize their limitations. And once you start to compare, it makes sense to try to compare comparable cases. Taking Manzi’s criticism too strongly would leave us in the position of allowing raw numbers, and allowing pure unblemished randomized experiments, but nothing in between.
In summary:
1. Manzi’s right to emphasize that a simplistic interpretation of regression results can be misleading.
2. Regressions of observational data can be a good way of going beyond raw comparisons and averages.
Some of this discussion reminds me of the literature on the wage premium for risk, where people run regressions on salaries for comparable jobs in order to estimate how much people need to be paid to risk death or injury.. Based on my reading is that these studies can’t be trusted: if you’re not careful, you can easily estimate the value of life to be negative–after all, the riskiest jobs (lumberjack, etc.) tend to pay poorly, while the best-paying jobs (being Bill Gates, etc.) are pretty safe gigs. With care, you can get those regressions to give reasonable coefficients in the range of $1 million per life, but I don’t really see these numbers as meaning anything at all; they’re just the results of fiddling with the models until something reasonable comes out. I’m not saying that the people who do these analyses are cheating, just that they want reasonable results but the models seem too open-ended to be a good measure of risk premiums.
Jonathan Cohn at TNR:
Am I certain Keefe is right? No. Having spent some time reporting on public and private sector compensation before, I can tell you that there is a lot of disagreement over the proper way to adjust the raw compensation figures to account for variables like age, education, and so on. (The debate is as much philosophical as methodological: Some conservatives argue that public employers put an artificial premium on graduate education, effectively paying more for degrees that don’t make workers better qualified.) I haven’t seen a specific refutation of Keefe’s report on Wisconsin, but if you want to read an analysis that suggests public workers, in general, are over-compensated, Andrew Biggs of the American Enterprise Institute has done work along those lines–and has a new article in the Weekly Standard summarizing his views.
But I wonder if this whole debate misses the point. Suppose public workers really do make more than private sector workers. Who’s to say that the problem is public workers making too much, rather than private sector workers making too little?
Andrew Biggs at AEI:
While we’ll have a longer piece out on Wisconsin pay soon, I figured that in response to Cohn’s post I’d raise a couple issues regarding EPI’s report.
First, we’ve found a lower salary penalty for Wisconsin public employees than EPI did (around -5 percent versus -11 percent in EPI’s study). It’s not clear what’s driving the difference, since we’re using the same data, but that’s something to track down. It’s also worth noting that both our calculations and EPI’s control for firm size; this means that essentially we’re comparing Wisconsin public employees not to all private workers, but to employees at the very largest Wisconsin firms, who tend to pay more generous salaries and benefits. Whether to control for firm size is an open question, since if a given public employee didn’t work for the government there’s a good chance he wouldn’t work at a large private firm. But readers at least should be aware of the issue.
Second, the benefits shown in the EPI report aren’t actually for Wisconsin alone. They’re an average for the “East North Central Census Division,” which comprises Illinois, Indiana, Michigan, Ohio, and Wisconsin. Because the Bureau of Labor Statistics doesn’t publish compensation data at the state level (due to small sample sizes) regional figures are the best we’ve got. The problem is, if Wisconsin government workers get relatively better benefits than public employees in other states—which seems to be part of the argument that Governor Walker is making—then these figures will understate true compensation. For instance, in practice Wisconsin public employees make essentially no contribution toward their pensions (formally they must contribute around 5 percent of pay, but their employers almost always cover it). Nationally, public employees contribute an average of around 5.7 percent of pay to their pensions.
Third, the benefit measures in the EPI study are based on what employers pay, not what employees actually receive. This matters for public-sector defined-benefit pensions, which use much more optimistic investment return assumptions than private pensions (a 7.8 percent assumed return in the Wisconsin Retirement System, versus around a 4 percent riskless return in U.S. Treasury securities) and fund their benefits accordingly. Most economists think public pensions are wrong to make these assumptions, but what matters is that employees effectively receive those higher returns whether the investments pan out or not. Adjusting for the differences in implicit returns to pensions would increase total Wisconsin compensation by around 4 percent.
Fourth, and related, is that the EPI study omits the value of retiree health benefits, which most public workers receive but most private employees don’t. (Some very large firms still offer retiree health benefits, but they’re increasingly rare and increasingly stingy.) The value of retiree healthcare can vary significantly. For instance, most run-of-the-mill Wisconsin state retirees are offered the right to buy into the employee plan. This provides an implicit subsidy, since they’re buying at rates calculated for the working-age population rather than their own health risk. The value of this is equal to a percent or so of extra pay every year. Other employees, such as Milwaukee teachers, have almost all their premiums paid for them. Actuarial reports list these protections as costing over 17 percent of salaries, meaning that for these workers EPI’s approach would miss a lot of benefit income. In addition, even these actuarial studies value retiree health coverage at employer cost, not the benefit to the employee. A retired 60-year-old purchasing coverage in the individual market would pay significantly more than the reported cost of his public-sector retiree health plan, because individual coverage costs more than group coverage. Some studies place the cost differential at around 25 percent; the Congressional Budget Office’s health insurance model appears to assume something larger: they say that “once differences in the characteristics of nongroup versus ESI [employer sponsored insurance] policyholders are considered and different loading costs are considered, a typical nongroup policy has roughly 60 percent of the relative plan value of an average ESI policy. That finding is supported by a recent survey of nongroup and ESI premiums and relative plan values in California.” So we know something is being missed and we have good reason to believe that even when we find actuarial reports calculating the cost of retiree health coverage, it’s still an underestimate. Unfortunately, there’s no central data source for retiree health benefits, meaning there’s a lot of digging to get a correct answer.
Fifth, the EPI report doesn’t calculate the value of public-sector job security. In a given year, a state/local worker has less than one-third the chance of being fired or laid off as a private worker. There’s a long history in economics (back to Adam Smith, actually) of thinking in terms of “compensating wage differentials,” although it’s only in the last 20 years or so that there’s been much progress in measuring them. We took a somewhat different approach, of using financial tools to calculate the price of an insurance policy that would protect against job loss and counting the value of that insurance toward public-sector pay. In theory each should produce the same answer, but as always things are messy. There may be a way of using CPS data to get on top of this, though.
At the end of the day, I just don’t think we can make any final conclusions on state/local pay because so much of the data, particularly on the benefits end, is still too loosey-goosey. There’s just more work to be done. (At the federal level, though, the measured overpayment is so large that I’m willing to say I’m convinced.)
Ezra Klein, responding to Manzi:
Jim Manzi has posted a critique of the Economic Policy Institute’s study (PDF) suggesting that Wisconsin’s public-sector workers are underpaid relative to their private-sector counterparts. It basically boils down to the argument that this sort of thing is hard to measure. The study controls for most every observable worker characteristic that we can imagine controlling for. But there are, Manzi says, an “all-but-infinite” number of differences beyond that. Perhaps going into the public sector says something about a person’s level of ambition, or ability to take risks and tolerate stress, or tendency to innovate — something that, in turn, makes the private-sector worker worth more or less to the economy.
And fair enough. Maybe there is some systemic difference between Hispanic women with bachelor’s degrees and 20 years of work experience who put in 52-hour weeks in the public sector and Hispanic women with bachelor’s degrees and 20 years of work experience who put in 52-hour weeks in the private sector. If anyone has some evidence for that, I’m open to hearing it. But the EPI study is aimed at a very specific and very influential claim: that Wisconsin’s state and local employees are clearly overpaid. It blows that claim up. Even in Manzi’s critique, there’s nothing left of it. So at this point, the burden of proof is on those who say Wisconsin’s public employees make too much money.
Reihan Salam on Klein’s response:
I was struck by this sentence: “Even in Manzi’s critique, there’s nothing left of it.” I’ve known Jim for many years and I’ve read just about everything he’s written, including a few things that haven’t been published. I have never seen Jim write that Wisconsin’s state and local employees are clearly overpaid, or indeed that any employees are clearly overpaid. There are many right-wingers who’ve said that, but it’s not the way Jim has ever thought about the issue as far as I know.
I don’t want to put words in Jim’s mouth, here’s what I consider a slightly more Manzian take: the problem with public sector compensation is that there is often very little clarity in terms of whether or not taxpayers are getting a good deal. One of the big reasons right-wingers are so hot for merit pay, based on my limited experience, is that they’re generally pretty comfortable with the idea of at least some public workers making much more than they are making now, provided other workers who’d be willing to work for less because they’re not likely to attract better offers are either paid less or fired.
Let me underline this point: Some public workers, like really great federal procurement officers, might very well be “underpaid,” in that they’re always on the verge of jumping ship to better opportunities, they’re stressed about money all the time when they could be using their awesome Jedi procurement skills to save taxpayers money, and we could attract other awesome people to do this job if only we weren’t such tightwads. Others might be “overpaid,” in that there are people who really like the stability of working for a “firm” that will, short of invasion and military conquest, probably exist for at least another ten years and would be open to working for a bit less money if they had no choice in the matter. Do you think we have more of the former than the latter? That’s where analyses like Keefe’s come in, to offer a rough guide to the conversation.
I would love for conservatives to do a better job of talking about public sector compensation. The basic conflict is whether we think of creating more jobs, work effort, etc., as our goal, or if our goal is to deliver a service. If the latter is our goal, we presumably want to do it in the most cost-effective way, so that we can devote our time, money, and energy to other things we like doing more. By extension, this suggests that we really do want to pay people as little as we can to get the things that we want. Or:
Reihan Salam says:
We really do want to pay people as little as we can to get the things that we want.
What a bozo!
This relentless process of delivering services and goods for less money really does destroy jobs, but, in theory at least, it allows us to create new ones. We happen to be living in a historical moment when there’s not a lot of faith in that idea, partly because we’ve seen a steady decline in labor force participation rates due to tangle of implicit marginal tax rates, an incarceration crisis, interrelated social pathologies, and much else. I’m biased in favor of believing that we will create new job opportunities because almost everyone I’m close to works in jobs that they could not have done in the way they do them now even ten years ago. The goal is to use good public policy to bridge over transitional periods, and, by the way, a dynamic market economy is always in a transitional period.
Manzi responds to Klein:
Klein is correct to say that my post “basically boils down to the argument that this sort of thing is hard to measure.” But he then argues that the purpose of the original study was not to demonstrate that public sector workers are underpaid, but rather to rebut the claim that they are overpaid:
[T]he EPI study is aimed at a very specific and very influential claim: that Wisconsin’s state and local employees are clearly overpaid. It blows that claim up.
That may have been the author’s motivation, but here is the final conclusion of the executive summary of the report:
[P]ublic sector workers in Wisconsin earn less in annual or hourly compensation than they would earn in the private sector.
The report makes a positive claim that it has determined a compensation “penalty” for working in the public sector, and repeats it many times. My argument was that this report does not establish whether or not this claim is true.
By the same logic, it also fails to “blow up” the claim that Wisconsin’s public workers are overpaid. The methodology is inadequate to the task of establishing whether these workers are overpaid, underpaid, or paid perfectly. As the last paragraph of my post put it:
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.
Statistician and political scientist Andrew Gelman has a very interesting response to my post, in which he agrees that this conclusion “sounds about right,” but cautions that the study is not “completely useless either” because this kind of adjusted comparison is better than simply comparing raw averages between public and private sector workers. I agree with that entirely. But that is, of course, a very different thing than saying that these adjustments create sufficient precision to support the bald statement, made in the report, that the author has analytically established that there is a “penalty” for working in the public sector.
Megan McArdle:
It’s obvious that this study doesn’t control for everything we can imagine, because it doesn’t even control for the matters that are of central dispute in Wisconsin: protection from being fired. This is, as people on both sides keep noting, so extraordinarily valuable that workers are willing to give up quite a lot to get it. And of course, a job that offers this sort of protection is likely to attract workers who especially value it. All government jobs offer this perk, which is valuable to the workers and costly to the employers; ceteris paribus, I’d expect that other compensation would be lower to compensate.
Obviously, it also doesn’t control in any way for other job or worker characteristics that effect compensation; jobs working for state and local government are systematically different from other sorts of jobs, because so much of what the government does isn’t done by anyone else. Though, oddly, for the teachers at the heart of this dispute, we do have a good comparison: private school teachers. And as I understand it, public school teachers have higher wages, and much better benefits, than private school teachers.
To which I expect the union’s boosters will say, “But jobs in private school are much more enjoyable–they don’t have to teach the difficult kids!” Indeed, they’re right. Which is exactly the point: there’s huge unobserved variable bias here.
There’s also the fact that the EPI study seems to be looking at means, which are going to be dragged upwards by a small number of highly compensated workers, particularly in the educated group. But state and local wages are capped. Meanwhile, some of the highest paid jobs in the private sector are in areas like commission sales, which have no counterpart in government. That means that the median worker is probably making much more than the median worker in the private sector. This may not be true in some lucrative fields such as law and medicine–but even there, we tend to compare government lawyers to the highly paid people at white shoe firms or corporations, not the legions of struggling will-drafters and ambulance-chasers.
You can argue, of course, that this is an ideologically much more attractive income distribution. Which highlights, I think, the core difference between the way people like Manzi and I look at this, and the way that progressives do. I don’t think of state employment as a way to create, in miniature, my ideal labor utopia. I think of it as a way to procure services. I define people as being “overpaid” not if they are paid more than someone with a similar level of education, but if they are paid more than I need to entice to pay to attract adequate workers. To analyze that, looking at medians is probably somewhat more instructive than looking at means.
Of course I agree with Manzi that this still doesn’t really tell us whether state workers are overpaid, underpaid, or just-right-paid. I suspect that the answer is probably “both”–adjusting for worker quality, the median government worker is probably overpaid, while in skilled specialties, salaries are probably not attracting as much of the top-flight talent as we’d ideally like. (This is why I have been advocating, futilely, that we make it possible to pay SEC employees multiples of what the President of the United States makes.) But as Manzi, who does this stuff for a living, will undoubtedly tell you, setting compensation is a really hard problem that no one’s got a very good handle on. So that’s just a suspicion, based on my experience of state bureaucracies, and my best guess at the incentive effects of the current structure. I don’t have enough data to back me up. And neither does EPI.
Have I then set up a nihilistic position that we can never know anything tolerably well because I can just keep raising these points that might matter, but are not included in the model? In effect, have I put any analyst in the impossible position of proving a negative? Not really. Here’s how you measure the accuracy of a model like this without accepting its internal assumptions: use it to make predictions for future real world experiments, and then see if its predictions are right or not. The formal name for this is falsification testing. This is what’s lacking in all of the referenced arguments in support of these models.
Human capital models, fixed effects models, and other various pattern-finding analyses are useful to help build theories, but a metaphysical debate about the “worth” of various public versus private sector jobs based upon them is fundamentally unproductive. For one thing, it won’t ever end. And as Megan McArdle correctly put it, the practical question in front of us is whether we the taxpayers can procure the public work that we want at a lower cost (or more generally, though less euphoniously, whether we are at the practical optimum on the cost-quality trade-off). If you want an analytical answer to this question, here is what I would do: randomly select some jurisdictions, job classifications or other subsets of public workers, cut their compensation, and then see if we can observe a material reduction in net value of output in these areas versus the control areas. If not, cut deeper. And keep cutting deeper, until we find our indifference point.
There would be obvious limitations to this approach. First, generalizing the results of initial experiments is not straightforward. Second evaluating output is not straightforward for many areas of government. But at a minimum, and unlike the world of endlessly dueling regressions, this would at least let us see the real-world effects of various public compensation levels first-hand, and allow the public to make an informed decision about whether they prefer the net effect of a change to public sector compensation or not.
Around The Sphere 
A Month Ago Tunisia, Yesterday Egypt, Today Iran?
Via Andrew Sullivan, back to blogging.
Tehran Bureau liveblog
Scott Lucas at Enduring America liveblog
Alan Cowell at NYT:
Helle Dale at Heritage:
Abe Greenwald at Commentary:
Charles Johnson at Little Green Footballs
Weasel Zippers:
Doug Mataconis:
Wonkette:
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