Tag Archives: Jim Manzi

An Apple A Day, Yadda, Yadda, Yadda

Ezra Klein:

File this one under “health care doesn’t work nearly as well as we’d like to believe.” A group of researchers followed almost 15,000 initially healthy Canadians for more than 10 years to see whether universal access to health care meant that the rich and the poor were equally likely to stay healthy. The answer? Not even close.

The researchers ran the data two ways: High-income patients vs. low-income patients, and highly educated patients vs. less educated patients. Over the course of the study, the high-income patients were only 35 percent as likely to die as the low-income patients, and the highly educated patients only 26 percent as likely to die as the low-income patients. And the problem wasn’t that the low-income and low-education patients were hanging back from the health-care system. Because they were getting sick while their richer and better educated counterparts weren’t, they actually used considerable more in health-care services.

The problem, the researchers say, is that the medical system just isn’t that good at keeping people from dying. “Health care services use by itself had little explanatory effect on the income-mortality association (4.3 percent) and no explanatory effect on the education-mortality association,” they conclude.

You don’t want to over-interpret this data. It’s possible that in the absence of insurance, the gap would be much wider. Indeed, there’s good evidence suggesting that’s true. Nevertheless, this should make us very skeptical about a world in which we’re spending almost one out of every five dollars on health-care services. Universal insurance is crucial both for certain forms of health care and for economic security. But as I’ve argued before, it’s probably not the best way to make people healthier. Rather, the best way to make people healthier would be to get health-care costs under control so there’s more money in the budget for things like early-childhood education and efforts to strip lead out of walls, both of which seem to have very large impacts on health even though we don’t think of them as health-care expenditures.

Arnold Kling:

And that is from a study in Canada.3. The Washington Post reports,

A 2006 study by the U.S. Department of Education found that 36 percent of adults have only basic or below-basic skills for dealing with health material. This means that 90 million Americans can understand discharge instructions written only at a fifth-grade level or lower.

My guess is that if you want to improve health outcomes in the United States, ignore health insurance and focus on literacy. Even if it has nothing to do with whether or not they can follow a doctor’s written instructions, my guess is that better literacy has a positive impact on health outcomes. The question is whether educators know enough about how to improve literacy to be able to do so effectively. I hope that is the case.

Tim Carney at The Examiner:

During debate over the health-care debate, liberal blogger Ezra Klein wrote that blocking the legislation would “cause the deaths of hundreds of thousands of people.” The liberals were relying on a study from the Urban Institute saying 20,000 people die a year because they are uninsured. Free-market blogger Megan McArdle read the study and concluded:

when you probe that claim, its accuracy is open to question. Even a rough approximation of how many people die because of lack of health insurance is hard to reach. Quite possibly, lack of health insurance has no more impact on your health than lack of flood insurance.

Klein came back with this:

I don’t want to be too harsh, and I don’t want to imply that anyone is sitting around twirling their mustache thinking up ways to hurt poor people. But opposition to health-care reform (which is different than opposition to the people who would be helped by health-care reform) is leading to some very strange arguments about the worth of health-care insurance — arguments that don’t fit with previous opinions, revealed preferences, or even the evidence the skeptics are citing.

But today, with the fight over ObamaCare behind us, and the President dealing with expectations over what his bill can deliver, Klein has a blog post that goes much farther than McArdle ever did. Klein’s headline:

Health care doesn’t keep people healthy — even in Canada

The main thrust of Klein’s blog post:

The problem, the researchers say, is that the medical system just isn’t that good at keeping people from dying. “Health care services use by itself had little explanatory effect on the income-mortality association (4.3 percent) and no explanatory effect on the education-mortality association,” they conclude.

I don’t want to be too harsh, and I’ve got nothing against what Klein used to call “arguments that don’t fit with previous opinions,” so I’ll just recommend you spend more time reading Megan McArdle.

The same is true, I’ll bet, for folks like Tim Carney who like to argue that medical care is ineffective as a way to argue against subsidizing health insurance for poor people. But for the record, the best evidence we have suggests that health-care coverage does much more for the health of poorer people than it does for the health of well-compensated, highly educated people like Carney. That folks like Carney use that evidence to continue a status quo in which they have health insurance and the poor don’t is, I think, proof of how seriously they take their arguments on this score, and of what this discussion is really about — and the answer isn’t “improving the health of the population.”

Karl Smith at Modeled Behavior:

I suspect we have two things going on.First, education confers status and status is related to health outcomes. For example Oscar winners live longer than those simply nominated. How this link occurs is not totally clear. It seems that the hormones associated with stress and disappointment – cortisol for example – reduce long run health. However, this may not be the mechanism. No one really knows at this point.

Second, for a long list of reasons there is correlation between education and physical attractiveness. Physical attractiveness is by evolutionary design a proxy for health. Which to say, healthier folks are more likely to become well educated.

This makes me doubt that power of health improvements from increasing education.

In general it is just damn hard to improve health outcomes. Our bodies are the product of about 4 billion years of evolution. Just making sense of how they work is hard enough. Making them work better is a herculean task.

Jim Manzi at The American Scene:

There is a debate going on in the blogosphere between Ezra Klein, Arnold Kling, Karl Smith, Tim Carney and others about, to put it crudely, whether health care really affects health that much. This is, in part, a proxy debate for whether it is worth it for the U.S. government to provide generous universal health care financing for all of its citizens (or, I suppose, residents).

Either position can be caricatured. On one hand, no sane person would want to be without the advances of modern medicine. Recently, a little girl I know had scarlet fever. A century ago, this would very possibly have meant burying a small corpse; today, it implies a 10-day cycle of swallowing medicine at breakfast and dinner. There are few people on Earth who have as much reason to be proud of how they spend their work week as pharmaceutical researchers.

On the other hand, the link from alternative methods of health care finance, through the actual differences in provision of medical care these imply in the contemporary U.S., to the actual differences in health outcomes these treatment differences would cause, isn’t nearly so obvious. The net health effect of providing universal health care coverage versus some alternative financing system is an empirical question, not a philosophy debate.

I’ve written a lot about why randomized experiments are so critical to understanding cause-and-effect relationships in social policy. In the case of health care financing, the reason is that what system of health care financing you have (high-quality “go to any doctor” plan; good HMO; catastrophic-only plan; VA; go to an emergency room because you are uninsured, etc.) is bound up with a myriad of other factors that influence health. A randomized experiment allows us to isolate the impact of the system of health care financing.

To my knowledge, the only large-scale randomized experiment in the U.S. that has tested the actual effects on health of providing various kinds of healthcare financing was the RAND Health Insurance Experiment (HIE). In this experiment, thousands of families were randomly assigned to one of five different health insurance plans that ranged from something like a plan that provides free health care, to something like a pure catastrophic-only plan in which consumers pay out-of-pocket for day-to-day healthcare. The study tracked what exact health care services each group used, and how their health varied over a period of 3 – 5 years.

Ezra Klein describes this experiment as “the best evidence we have,” and writes that it “suggests that health-care coverage does much more for the health of poorer people than it does for the health of well-compensated, highly educated people.” His statement is correct, but as a summary of the results of this experiment, seems to me to be radically incomplete. In fact, the experimenters wrote of the findings that “cost sharing reduced the use of nearly all health services,” but “the reduction in services induced by cost sharing had no adverse effect on participants’ health.” Think about that. Providing people coverage of their medical costs caused no average improvement in health.

Klein is correct that there appeared to be a net health benefit for the poorest participants, but this was for a tiny proportion of the population, and for a small subset of medical conditions. According to the study, “The poorest and sickest 6 percent of the sample at the start of the experiment had better outcomes under the free plan for 4 of the 30 conditions measured.” There are technical reasons why conclusions from such a experiment are not reliable for post hoc subgroups in the way that they are for average comparison of a test group versus a control group; but even if we were to accept this finding as valid, it’s not obvious to me that we would want to devise a health care financing system for the United States around helping 6% of the population partially ameliorate about 10% of their potential health problems, as opposed to developing some specific supplementary programs for these issues, if they could be addressed feasibly.

Klein clearly has a very sophisticated take on the issue, and wrote in 2009 that health care reform is not primarily about improving health, but in reducing how much we spend on it. As he put it, “The purpose of health reform, in other words, is to pay for health care — not to improve the health of the population.” Fair enough. But the real debate, then, would be about whether market forces or bureaucratic control would be better at reducing costs, not about which would be better at promoting health for the “poorest and sickest” or anybody else. It wouldn’t be about getting better health outcomes.

A single experiment like the RAND HIE is not definitive. Among other things: it finished in 1982, and we live in a different world; any such experiment requires replication; it might be that the important health effects take much longer than 5 years to materialize, and so on. But as an observer of the health care debates, it always struck me as fascinating that the fact that the “best evidence we have” showed that providing health care coverage doesn’t actually improve average health wasn’t treated as more central.

Advertisements

Leave a comment

Filed under Health Care

All Your Best Blog Posts On That Economic Policy Institute’s Study

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.
More Manzi:

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.

Leave a comment

Filed under Education, Go Meta

Talkin’ About Adding The Value

Grace Snodgrass at Huffington Post:

One day soon, my name and performance evaluation could be printed in your morning newspaper. It will tell you that I’m a teacher who has clear strengths and weaknesses in helping my students advance academically.

But as valuable as my so-called “Teacher Data Report” is in helping me identify these areas, it really doesn’t say much about the overall quality of my teaching. And printing the results — as an NYC judge just gave the city the right to do — will do little to make me, or any of my colleagues, better teachers. At least, not right away. What will help is the Department of Education and the teachers’ union putting aside their differences and improving these reports so that teachers like me receive good information about our performance and clear steps towards achieving our classroom goals.

As an educator, I want to be evaluated. I know that my students’ success hinges on the quality of my teaching. The Department of Education is actually on the right track with the “value-added” method it uses to calculate the impact teachers have on their students’ academic growth. Value-added compares a student’s predicted performance on standardized assessments with how he or she actually performs.

Dana Goldstein and Megan McArdle on Bloggingheads

Jim Manzi at The Corner:

Recently, Megan McArdle and Dana Goldstein had a very interesting Bloggingheads discussion that was mostly about teacher evaluations. They referenced some widely discussed attempts to evaluate teacher performance using what is called “value-added.” This is a very hot topic in education right now. Roughly speaking, it refers to evaluating teacher performance by measuring the average change in standardized test scores for the students in a given teacher’s class from the beginning of the year to the end of the year, rather than simply measuring their scores. The rationale is that this is an effective way to adjust for different teachers being confronted with students of differing abilities and environments.

This seems like a broadly sensible idea as far as it goes, but consider that the real formula for calculating such a score in a typical teacher value-added evaluation system is not “Average math + reading score at end of year – average math reading score at beginning of year,” but rather a very involved regression equation. What this reflects is real complexity, which has a number of sources. First, at the most basic level, teaching is an inherently complex activity. Second, differences between students are not unvarying across time and subject matter. How do we know that Johnny, who was 20 percent better at learning math than Betty in 3rd grade is not relatively more or less advantaged in learning reading in fourth grade? Third, an individual person-year of classroom education is executed as part of a collective enterprise with shared contributions. Teacher X had special needs assistant 1 work with her class, and teacher Y had special needs assistant 2 working with his class — how do we disentangle the effects of the teacher versus the special ed assistant? Fourth, teaching has effects that continue beyond that school year. For example, how do we know if teacher X got a great gain in scores for students in third grade by using techniques that made them less prepared for fourth grade, or vice versa for teacher Y? The argument behind complicated evaluation scoring systems is that they untangle this complexity sufficiently to measure teacher performance with imperfect but tolerable accuracy.

Any successful company that I have ever seen employs some kind of a serious system for evaluating and rewarding / punishing employee performance. But if we think of teaching in these terms — as a job like many others, rather than some sui generis activity — then I think that the hopes put forward for such a system by its advocates are somewhat overblown.

There are some job categories that have a set of characteristics that lend themselves to these kinds of quantitative “value added” evaluations. Typically, they have hundreds or thousands of employees in a common job classification operating in separated local environments without moment-to-moment supervision; the differences in these environments make simple output comparisons unfair; the job is reasonably complex; and, often the performance of any one person will have some indirect, but material, influence on the performance of others over time. Think of trying to manage an industrial sales force of 2,000 salespeople, or the store managers for a chain of 1,000 retail outlets. There is a natural tendency in such situations for analytical headquarters types to say “Look, we need some way to measure performance in each store / territory / office, so let’s build a model that adjusts for inherent differences, and then do evaluations on these adjusted scores.”

I’ve seen a number of such analytically-driven evaluation efforts up close. They usually fail. By far the most common result that I have seen is that operational managers muscle through use of this tool in the first year of evaluations, and then give up on it by year two in the face of open revolt by the evaluated employees. This revolt is based partially on veiled self-interest (no matter what they say in response to surveys, most people resist being held objectively accountable for results), but is also partially based on the inability of the system designers to meet the legitimate challenges raised by the employees.

Noah Millman at The American Scene:

I do want to add a few additional points of my own:

1. Evaluations establish the principle that there is such a thing as performance in the first place. A great deal of discussion nowadays in education revolves around the idea that what we need to “fix the schools” is great teachers. But if that’s what we need, we’ll never do it. What we need, instead, are mechanisms for getting marginally better performance, year after year, from a teaching pool that remains merely adequate.

One bit of low-hanging fruit for achieving that goal, meanwhile, is the ability to dismiss the bottom 5% of teachers in terms of performance. Not only are these teachers failing comprehensively in their own classrooms, but their mere presence has a corrosive effect on an entire organization – on the teachers, on the students, on the management of the school. But right now, firing these teachers is essentially impossible. For all the difficulty of doing a rigorous evaluation in order to improve teaching performance across the board, I suspect it is a whole lot easier to identify the worst teachers in the school. If that could be done, the pressure to be able to terminate them would be significant, and that could do a lot to improve school performance right there.

2. Value-added metrics wind up punishing perfectly good but not spectacular schools with above-average student bodies. It may be that these schools should suffer reputationally, because the staff is not actually delivering as much value as they should. But high-stakes standardized testing actually pushes these schools to destroy themselves, wiping out the programs that actually do deliver value to these high-aptitude students and instead focusing on teaching to the tests.

That’s not an argument against using value-added metrics as such. It’s an argument that they need to be used intelligently, with some understanding of what “value-added” means at different points on the performance spectrum. But that, in turn, would require admitting that different standards are needed for students with different aptitude, which, in turn, is extremely difficult for our education system to admit. (And, admittedly, it’s a problem in corporate cultures that cross widely different customer bases as well. How well would Wal-Mart manage Tiffany?)

3. Nobody goes into teaching “for the money” – that is to say, teachers in aggregate make significantly less than people with their educational credentials and academic aptitude could make in other professions. So monetary rewards are useful primarily going to prove useful as signaling devices. There’s a lot of evidence coming in from high-performance charter schools suggesting that a monetary reward system tied too closely to evaluations actually degrades performance, because it gets teachers focused on the evaluations rather than on the performance. The evaluations should primarily be used as a diagnostic, to identify correctable deficiencies in teacher performance so they can be corrected through staff development, and to identify gross deficiencies in teacher performance so the teachers in question can be dismissed.

4. Similarly, across a system, what evaluations are useful is for research purposes and to drive market discipline. Evaluations of a school should be very useful to parents seeking to select a school for their child. Schools that consistently achieve high valuations (particularly for value-added metrics) should be objects of study by administrators and others looking to replicate that performance in lower-performing but still basically well-run schools. The least-important use of the evaluation is to directly “reward” or “punish” a school bureaucratically – and, indeed, if that becomes the primary use then the school is likely to start focusing overwhelmingly on the evaluation process and lose sight of actual performance. I’ve seen this happen over and over in New York City schools; it’s not a theoretical question.

Conor Friedersdorf at Sullivan’s place:

And it helps explain the inherent tension between teachers unions and the rest of us. Unions exist to protect the interests of their members. Even in the best case scenario, that means lobbying for an evaluation system that maximizes fairness to the people being evaluated. As citizens, our primary goal should be creating the best education system possible, even if doing so sometimes means (for example) that the teacher most desserving of a bonus doesn’t get one. Saying that there is a conflict between the common good and the ends of teachers unions isn’t a condemnation of the latter. It’s just a fact. And everyone seems to understand the basic concept if you talk about prison guard unions.

Reihan Salam:

Part of what makes me nervous is that productivity varies dramatically within industries. It is very common for comparable factories at the 90th percentile produce four times as much as factories at the 10th percentile. Moreover, the scorecards and shortcuts used by factories at the 90th percentile wouldn’t necessarily work for those at the 10th percentile. Managerial insights are usually embedded in a complex tangle on personalities and practices that can’t easily be replicated. This is natural, and I’d say that I’d much rather see a few firms race ahead than allow all firms to remain mired at the low end of the productivity spectrum.  Suffice it to say, this is not the ethic that governs how we generally think about public schools.

In a time when at least half of the political spectrum is deeply troubled by inequality, i.e., by the fact that some firms, individuals, and households are racing far ahead of others, what at least some education reformers are saying is that we want to unleash a few inventive, well-managed schools to start deploying the same per pupil resources to much greater effect. That is, we want to, in the short run at least, make the K-12 educational landscape more unequal, in the hope that leading schools will identify instructional methods, e.g., effective virtual instruction, that will prove scalable.

Much depends on how one interprets the fact that some firms, individuals, and households are racing ahead of the others. I take what I think of as a nuanced view. Generally speaking, some firms, individuals, and households race ahead of others due to a combination of luck, opportunity, and smart investments in organizational capital. In some cases, we see rent-seeking, tax and regulatory arbitrage, etc. But whereas Simon Johnson and many of my friends on the left see this as the dominant narrative, I see it as a significant but nevertheless relatively small part of the wage dispersion story.

Nicholas Bloom and John Van Reenen have written a neat essay in the Journal of Economic Perspectives on how effective management practices spread. I was struck by many of their observations, including some that will be familiar to those of you who see organizational capital as very important (“firms that more intensively use human capital, as measured by more educated workers, tend to have much better management practices”).

The United States has a commanding lead in terms of the quality of management in firms. This is very interesting considering our relative weakness in terms of educational attainment at the median in the prime-age cohorts. And I suspect that this feeds back into wage dispersion as well as assortative mating, family breakdown, and other sources of “stickiness” at the low end of the income distribution. For a variety of reasons, our economy is rewarding people with managerial skills, and, in a crude sense, one might be able to extrapolate the ability to manage a wide range of tasks in the workplace to the ability to maintain constructive relationships in other domains. The obvious objection is that many hard-charging executives neglect their families and personal lives, etc. But it could also be true that the that neglect of parental responsibilities is somewhat more common among those marginally attached to the labor force, due to the greater prevalence of substance abuse and other risky behaviors.

Jonathan Chait at TNR on Manzi:

That’s an interesting insight into the general problem with quantitative measures. Here are a few points in response:

1. You need some system for deciding how to compensate teachers. Merit pay may not be perfect, but tenure plus single-track longevity-based pay is really, really imperfect. Manzi doesn’t say that better systems for measuring teachers are futile, but he’s a little too fatalistic about their potential to improve upon a very badly designed status quo.

2. Manzi’s description…

evaluating teacher performance by measuring the average change in standardized test scores for the students in a given teacher’s class from the beginning of the year to the end of the year, rather than simply measuring their scores. The rationale is that this is an effective way to adjust for different teachers being confronted with students of differing abilities and environments.

..implies that quantitative measures are being used as the entire system to evaluate teachers. In fact, no state uses such measures for any more than half of the evaluation. The other half involves subjective human evaluations.

3. In general, he’s fitting this issue into his “progressives are too optimistic about the potential to rationalize policy” frame. I think that frame is useful — indeed, of all the conservative perspectives on public policy, it’s probably the one liberals should take most seriously. But when you combine the fact that the status quo system is demonstrably terrible, that nobody is trying to devise a formula to control the entire teacher evaluation process, and that nobody is promising the “silver bullet” he assures us doesn’t exist, his argument has a bit of a straw man quality.

Manzi responds to Chait:

My post wasn’t about if we should use quantitative measures of improvement in their students’ standardized test scores as an element of how we evaluate, compensate, manage and retain teachers, but rather about how to do this.

Two of the key points that I tried to make are that the metrics themselves should likely be much simpler than those currently developed by economics PhDs, and that such an evaluation system is only likely to work if embedded within a program of management reform for schools and school systems. The bulk of the post was trying to explain why I believe these assertions to be true.

An additional point that I mentioned in passing is my skepticism that such management reform will really happen in the absence of market pressures on schools. Continuous management reform, sustained over decades, that gets organizations to take difficult and unpleasant actions with employees is very hard to achieve without them. There’s nothing magic about teachers or schools. The same problems with evaluation and other management issues that plague them arise in big companies all the time. It’s only the ugly reality of market discipline that keeps them in check.

Leave a comment

Filed under Education

We Now Return You To This 24,536th Episode Of “Bloggers Debating Whether The Stimulus Worked”

Megan McArdle:

Today’s earlier post has naturally aroused suspicions that I am simply a knee-jerk stimulus opponent.  This is not true.  I tepidly supported the notion of stimulus, though I also thought that the stimulus we did was not well executed, because Democrats wanted to use it to execute their policy priorities, rather than to provide maximal stimulus.  I said at the time that “shovel-ready” infrastructure projects really weren’t; that’s not how the government procurement process works, and the federal government tends to slow things down, not speed them up.  As it was under George Bush, politicians seemed more interested in using stimulus as an excuse for stuff they already wanted to do, than in actually figuring out what was most stimulative.  (My candidates:  payroll tax cut, more lavish unemployment benefits).

And what do I think now?  Well, protestations aside, the stimulus we ended up doing was huge.  Maybe it wasn’t as huge as some would have liked, but $800 billion dollars is almost 6% of GDP. (2% if you spread it over 3 years, as the stimulus was).  All told, running a deficit of 10+% of GDP ought to have some pretty powerful stimulative effect.

So far, I’ve been underwhelmed.  Maybe we were going to end up so far in a ditch that we wouldn’t even be able to see sky when we looked up, only mud.  On the other hand, maybe simply not repeating the massive, massive monetary mistakes of the 1930s was enough to keep us out of the Great Depression, and the stimulus merely tinkered around the edges.  I find the latter at least as plausible as the former.

When you combine middling and hard-to-prove results with the fact that the stimulus we got was so obviously wrapped up in the political agenda of the Democratic Party, I think that the case for stimulus has gotten weaker.  Stimulus is always going to get wrapped up in the agenda of whatever party is in power–it will concentrate too much on long-term strategic attempts to change the aggregate level of government expenditure; it will be deployed inefficiently; it will be stretched out to maximize electoral rather than economic effectiveness.

I’d much rather see people talking about how best to ease the economic transition.  One way to think of recessions is that they always represent the transition point between two states of the economy:  high inflation to low inflation, overleveraged to under, or what have you.  Those transitions involve a great deal of human suffering, and contra the “work the rot out” school of economic policy, I do not think that this suffering is necessary.

Stephen Stromberg at WaPo:

But the bigger problem is that the argument about the stimulus is basically unwinnable, for now. That’s because, when you look past the gotcha quotes, much of the Obama administration’s justification for the Recovery Act relies on a difficult-to-prove counterfactual — that it created or saved jobs.

So, unemployment could even be going up, and the president could still claim the stimulus was a success, since it could have been worse. Here, the GOP conference ignores this argument entirely, as it so often does, by pointing to negative raw data and ignoring the Democrats’ argument that you have to compare them to a far more catastrophic baseline. Obama’s critics on the left often do the same to conclude that the stimulus was much too small.

I tend to sympathize with the administration on this. It’s shocking how quickly people have forgotten the rank fear that pervaded the country in late 2008 and early 2009. As with the Troubled Assets Relief Program, approving the stimulus was important if only to prove that the government would not let the economy fall off a cliff. At the same time, policymakers had to pay attention to folks worried — without much reason in the short-term, it turned out, but it was hard to know that then — about inflation and the willingness of private capital to finance American government debt at low interest rates. How do you quantify the number of jobs saved from ministering to such psychological preoccupations? It’s hard, but it doesn’t mean they weren’t saved.

Tim Cavanaugh at Reason:

Where do Keynesians go now that even public radio is talking about the failure of one of history’s costliest Keynesian stimulus efforts?

At City Journal, Guy Sorman notes how quickly the managed-market winds have shifted. When the credit unwind started, the papers, the TV and the newsweaklies declared capitalism dead in just a little less time than it took for Kent Brockman to declare his loyalty to the Space Ants. Less than two years later, you can’t buy good press for the stimulus; the economy is frozen solid in August; the nation is rediscovering — despite the herniated efforts of local, state and federal government — the virtues of thrift; and if you search for Keynes on the interwebs, all you turn up are headlines like “How Dr. Keynes killed the patient.”

But here’s the tell: We’re already starting to see the first of the “Today’s Keynesians are misreading Keynes” walk-back arguments.

As an idea, neo-Keynesianism is dead. (As public policy, of course, it will live forever.)

Josef Joffe at TNR:

As the joke goes, this is the reason why there are no one-handed economists; they are always saying: “on the one hand, on the other…” But, in the second year of the stimulus, it has become a lot harder to argue that Keynes is cool, and it is a lot easier to contend that tightfisted Angela Merkel, though a physicist by training, has a better knack for economic management than the Bloomsbury Sage—at least 74 years after he published his General Theory.

OK, it is silly to draw so much conclusion from so little evidence, and, whatever the gainsayers argue, Obama will throw more money at the economy as the midterms draw closer. But think of the issue in the simplest of terms: As a businessperson or consumer, would you now spend your money in the face of a rising deficit that is guaranteed to bring on either inflation or tax hikes or both? Maybe you can find the answer in the Holy Writ that is the General Theory. Confidence matters, and this is what the great man had to say in Book III: “The government program may, through its effect on ‘confidence’, increase liquidity-preference or diminish the marginal efficiency of capital, which may retard other investment…” Translation by Joffe: “The stimulus may lead to cash-hoarding and, by depressing the return on capital, diminish private investment.” Keynes may have been wiser than his disciples.

Jonathan Chait at TNR:

The truth is that you can’t prove whether the stimulus worked or not. You can try to reconstruct the effects of the stimulus (and other government interventions) as Alan Blinder and Mark Zandi did. But you’re still making assumptions on the basis of economic models — mainstream assumptions shared by most economists, but assumptions nonetheless. Actually proving the case would require going back to 2009 and re-running history with everything the same but no stimulus. Since we can’t do that, all we can do is guess.

Of course, Republicans aren’t making a good faith effort to gauge the effects of the stimulus. They’re simply looking for a pseudo-economic argument that allows them to blame Obama for everything that has happened since the economic crisis of 2008. Lindsey’s article is a rationalization for that political strategy.

Jim Manzi at TNR:

Chait is right. The reason we don’t know whether the stimulus has worked in the United States is fundamental. And I believe it has significant implications for how we should approach public policy in the recession.

[…]

I believe that recognition of our ignorance should lead us to two important, though tentative and imprecise, conclusions.

First, we should treat anybody who states definitively that the result of stimulus policy X will be economic outcome Y with extreme skepticism. And weaseling about the magnitude of the predicted impact such that all outcomes within the purported range of uncertainty still magically lead to the same policy conclusion doesn’t count; we should recognize that we don’t even know at the most basic level whether stimulus works or not.

Second, “boldness” in the face of ignorance should not be seen in heroic terms. It is a desperate move taken only when other options are exhausted, and with our eyes open to the fact that we are taking a wild risk. Actual science can allow us to act on counterintuitive predictions with confidence–who would think intuitively that it’s a smart idea to get into a heavy metal tube and then go 30,000 feet up into the air? But we don’t have this kind of knowledge about a stimulus policy. We are walking into a casino and putting $800 billion dollars down on a single bet in a game where we don’t even know the rules. In general, in the face of this kind of uncertainty, we ought to seek policy interventions that are as narrowly targeted as is consistent with addressing the problem; tested prior to implementation to whatever extent possible; hedged on multiple dimensions; and designed to be as reversible as is practicable.

What I am trying to describe here is not a policy per se, but an attitude of epistemic humility.

Chait responds to Manzi:

Manzi is a much nicer person then I am, so it’s no surprise that I will return the favor of him saying that I’m right by replying that he’s wrong. Here are a few of the problems with his case. First, and more importantly, I was arguing that the precise effect of the stimulus can’t be measured. That doesn’t mean we have no idea whether it worked. There is a general, though not unanimous, consensus within the economic field that increasing spending or reducing taxes temporarily increases economic growth. Basically, we do know the rules — increasing the deficit in order to pave some roads and cut taxes for middle-income people will increase the size of the economy; the primary debate is just how much.

Now, it’s true that the conservative movement has invested a great deal of time into throwing cold water on this basic consensus. I think this campaign should be viewed as largely political. Private forecasters unanimously believe that fiscal stimulus can temporarily boost growth. They give no credence whatsoever to the various right-wing alternative models in which fiscal stimulus does not boost growth. Moreover, in 2001, when the objective case for fiscal stimulus was much weaker, there was no real debate about the efficacy of fiscal stimulus. The fact that Republicans are fiercely contesting the merits of fiscal stimulus now, while almost nobody was doing so when the case was much weaker in 2001, suggests that the right’s skepticism is a political phenomenon.

Second, we are not really taking a “wild risk” by devoting $800 billion to mitigating the deepest economic crisis since the Great Depression. The long term fiscal cost of the stimulus is quite minimal:

The opposing risk, of allowing an economic free-fall, seems much greater. The risks of a depression are enormous. Of course, one side effect of such an outcome would be massive political gains for the opposition party. No doubt this helps explains the more sanguine attitude Republican elected officials — I am not implicating Manzi here — took toward the 2008 crisis, as opposed to their urgency in the face of the far more shallow 2001 recession.

Third, Manzi suggests that remedies be as narrowly targeted as possible, reversible, and tested prior to implementation. The stimulus was pretty narrowly targetted. It consisted of spending and tax cuts designed to increase consumption. It is completely reversible in the sense that the spending and tax cuts are temporary.

Being “tested,” as I noted, is not possible. But it’s not possible to test very much in macro-economics. We can’t run natural experiments with whole economies without the aid of time travel. Manzi’s analogies of flying in an airplane assume is that there’s some safe, default option — staying on the ground, keeping away from the casino. That isn’t a realistic way to think about economics. Doing nothing in the face of economic catastrophe is a policy choice. To the extent that it’s been “tested,” it’s been shown to produce terrible results. The better attitude than trying to imagine some safe default course of action, I’d suggest, is to hew to precepts generally accepted within the economics field.

Manzi responds to Chait:

Chait begins his reply by claiming that I “oppose any stimulus at all.” This is a position which I did not present in the post, and which I do not hold. In fact, I have consistently advocated stimulus in the face of the current crisis, and generally in venues that are not as hospitable to this idea as The New Republic.

I was arguing in my post that we should approach stimulus with appropriate humility about our knowledge, not that we should never execute such a policy. That’s why the sentence in my post that immediately follows those Chait excerpted, is: “What I am trying to describe here is not a policy per se, but an attitude of epistemic humility.”

Chait then moves on to criticize the reasoning behind my imagined position against any stimulus spending.

His first argument is that he was only saying we can’t measure stimulus precisely, but that we still know enough to act with confidence:

First, and more importantly, I was arguing that the precise effect of the stimulus can’t be measured. That doesn’t mean we have no idea whether it worked. There is a general, though not unanimous, consensus within the economic field that increasing spending or reducing taxes temporarily increases economic growth. Basically, we do know the rules — increasing the deficit in order to pave some roads and cut taxes for middle-income people will increase the size of the economy; the primary debate is just how much.

Now, it’s true that the conservative movement has invested a great deal of time into throwing cold water on this basic consensus. I think this campaign should be viewed as largely political.

Chait correctly identifies this as the most important of his arguments, so I’ll spend the most time replying to it. The problems with this criticism are that: (1) it is false, (2) it is a straw man, and (3) by far most important, it doesn’t address my point.

1. It is false.

Chait is trying to define the position that stimulus will not increase output as intellectually illegitimate. (Though, again, this is not a claim that I have made.)

It is certainly true that a large majority of professional economists accept the view that “increasing spending or reducing taxes temporarily increases economic growth”—but that is very far from claiming that disputing it is largely a political campaign. Robert Barro, Professor of Economics at Harvard, John Cochrane, Professor of Finance at the University of Chicago, and Casey Mulligan, Professor of Economics at the University of Chicago, have each separately argued that it is somewhere between plausible and likely that the multiplier for stimulus spending under relevant conditions is indistinguishable from zero (i.e., that stimulative spending will not materially increase economic output). According to surveys of professional economists reported by Greg Mankiw, about 10 percent of economists do not agree with the statement that “Fiscal policy (e.g., tax cut and/or government expenditure increase) has a significant stimulative impact on a less than fully employed economy.” Both the Wall Street Journal and the Financial Times have run opinion columns expressing the view that a multiplier of zero is a plausible to likely theory.

I have not been afraid to call out influential conservative activists when I believe they are engaging in crank refusal to accept a scientific finding. But in a genuinely scientific field which has accepted a predictive rule as valid to the point that there is a true consensus—such that the only reason for refusal to accept it is crankery or, in Chait’s terms, “politics”—you don’t usually see: several full professors at the top two departments in the subject, when speaking directly in their area of research expertise, challenge it; 10 percent of all practitioners in the field refuse to accept it; and the two leading global general circulation publications in field running op-eds questioning it.

2. It is a straw man

If the U.S. government were to borrow and spend $1 trillion with the sole result of increasing U.S. GDP in Q4 2010 by $1, it would have “temporarily increased economic growth”—but no sane person would advocate such a policy. It would not be, in either the common-sense meaning of words, or in the terms of my post, a stimulus policy that “worked.” The relevant policy question is whether stimulus spending “temporarily increases economic growth” enough to make such a policy rationally advisable . Economists are all over the place on their estimates for impact of stimulus policy across the range that is relevant to the policy decision.

A great many leading economists may accept the proposition that enough stimulus spending will probably cause at least some increase in output for a short period of time in some circumstances, yet are still uncomfortable with the kind of stimulus spending strategy that is the actual subject of current political debate. In 2009, James Buchanan (1986 Nobel Laureate in Economics), Edward Prescott (2004 Nobel Laureate in Economics), and Vernon Smith (2002 Nobel Laureate in Economics) promulgated this statement:

“Notwithstanding reports that all economists are now Keynesians and that we all support a big increase in the burden of government, we do not believe that more government spending is a way to improve economic performance.”

3. It doesn’t address my point

It is nerdy-sounding, but I believe critical to this discussion, to distinguish between measurement and knowledge. I made a very strong claim about measurement, and a very specific claim about knowledge.

I claim that we cannot usefully measure the effect of the stimulus program launched in 2009 at all. We can call this a “natural experiment” all day long, but in the absence of a control case, we cannot know what output would have been had we not executed the policy. Econometric models are not sufficient to estimate this counterfactual. Therefore, there is no achievable level of output in the United States in 2010, 2011, and so on that would enable a definitive answer to the question, “What was the effect of stimulus spending on output?” See, for example, in my original post, the response of leading economists when confronted by unemployment with stimulus that turned out to be higher than they projected unemployment would be without stimulus:

Ms. Romer famously projected in January 2009 that without government support, the unemployment rate would reach 9%, but with support the government could keep it under 8%. It’s 9.5% today.

Some Obama administration officials privately acknowledge they set job-creation expectations too high. The economy, they argue, was in fact sicker in 2009 than they and most others realized at the time. But they insist unemployment would have been worse without the stimulus.

All potentially useful predictions made about the output impact of the stimulus program are non-falsifiable. Failure of predictions can be simply justified by this sort of ad hoc explanation after the fact.

Adam Ozimek at Modeled Behavior on Manzi:

Specifically, he cites the fact that the University of Chicago’s Barro, Fama, and Mulligan are stimulus skeptics, and according a survey from Mankiw, so are 10% of all economists. But I don’t think 10% of economists and a handful of high-profile experts disagreeing is sufficient to say there is not a strong consensus.

For economics 90% agreement is a pretty high level of agreement, and I would be surprised to find a consensus much stronger on that on most issues. From a survey of economists by Whaples we can see that ”only” 87.5% of economists agree that the U.S. should remove all remaining tariffs and trade barriers, 90.1% believe that employers should not be restricted from outsourcing jobs, 85% agree that subsidies to agriculture should be removed, and the same percent say it about sports subsidies as well. From another survey of economists, 87.5% agree that the U.S. trade deficit is not primarily due to other nations’ nontariff trade barriers, 83.5% agree or agree with provisos that tax policy can affect the long-run rate of capital formation, 93% agree that pollution taxes or tradeable permits are more efficient than emissions standards, 92.9% agree or agree with provisos that flexible exchange rates are effective, and 92.6% agree that tariffs or import quotes reduce the general welfare of society.

Despite the disagreement by 7% to 17% of economists on these issues I would argue that are all accurately characterized as representing as a strong consensus. Whaples calls the agreement in those examples a “consensus” and “an overwhelming majority”, and Fuller and Geide-Stevenson, the authors of the other paper, explicitly refer to those examples as representing a “strong consensus”.

Yet I’m certain that on each of these issues you could find experts at the top 10 economics departments that agree with the minority position. Stiglitz alone will probably disagree with more than half of them, and you won’t have to look hard to find a half a dozen other Ivy League dissenters.

My point is not to disagree with Manzi that a strong consensus means it is okay to call anyone who disagrees with the consensus a “crank” or “politically motivated”, but just to point out that the bar he’s set for a “true consensus” pretty much means that there’s is no “true consensus” on important issues in economics. Then again, he may very well agree with that point.

Karl Smith at Modeled Behavior:

Jim Manzi and I are kindred spirits on the issue of epistemic humility. Out in the real world – as opposed to the whiteboard – only one thing is for sure and that is that this is all going to end very, very badly. The long run is not your friend.

In the mean time, little is for certain. In particular, we are not clear on exactly what the consequences of economic stimulus were. However, it is important to clarify what some economists may have meant by stimulus skepticism.

I wrote frequently in the weeks leading up to the passage of the stimulus that I was a stimulus skeptic. I signed a letter offered by John Boehner for economists who believe that IIRC, stimulus is not the best way to revive our economy.

At no time, however, did I believe that stimulus would have no effect on output. That is, unlike what I believe to be Mulligan and Fama’s stance, I did not believe that labor markets always clear.

What I did think is that I wanted to take what, even then, seemed like enormous monetary risks. It has been rumored that Tim Geithner suggested securing the assets of all major banks in the United States. While I didn’t formally support that, it did not seem absurd to me. Nor, did massive nationalization of the banking system and certainly not aggressive purchases of government securities.

While taking on all of these risks I didn’t see the need to add the confusion and inevitable political food fight of stimulus on top of it. Moreover, if one was going to do a stimulus it seemed much more sensible to simply slash the payroll tax. The bang for the buck would have been less but you can cram a whole lot more bucks through the payroll tax system than you can through the appropriations mechanism. Additionally, the public choice issues in cutting the payroll tax were much more manageable.

The point of all of this is that I listed myself as a stimulus skeptic but I wasn’t at all skeptical about the stimulating powers of government spending. I was skeptical as to whether that was the ideal course of action. That skepticism was as much rooted in my understanding of American political dynamics and my own tolerance for risk as in any scientific claims about macroeconomics.

Leave a comment

Filed under Economics, The Crisis

“Don’t Trust One-Offs”

Jim Manzi in City Journal:

[…]

Another way of putting the problem is that we have no reliable way to measure counterfactuals—that is, to know what would have happened had we not executed some policy—because so many other factors influence the outcome. This seemingly narrow problem is central to our continuing inability to transform social sciences into actual sciences. Unlike physics or biology, the social sciences have not demonstrated the capacity to produce a substantial body of useful, nonobvious, and reliable predictive rules about what they study—that is, human social behavior, including the impact of proposed government programs.

The missing ingredient is controlled experimentation, which is what allows science positively to settle certain kinds of debates. How do we know that our physical theories concerning the wing are true? In the end, not because of equations on blackboards or compelling speeches by famous physicists but because airplanes stay up. Social scientists may make claims as fascinating and counterintuitive as the proposition that a heavy piece of machinery can fly, but these claims are frequently untested by experiment, which means that debates like the one in 2009 will never be settled. For decades to come, we will continue to be lectured by what are, in effect, Keynesian and non-Keynesian economists.

Over many decades, social science has groped toward the goal of applying the experimental method to evaluate its theories for social improvement. Recent developments have made this much more practical, and the experimental revolution is finally reaching social science. The most fundamental lesson that emerges from such experimentation to date is that our scientific ignorance of the human condition remains profound. Despite confidently asserted empirical analysis, persuasive rhetoric, and claims to expertise, very few social-program interventions can be shown in controlled experiments to create real improvement in outcomes of interest.

[…]

After reviewing experiments not just in criminology but also in welfare-program design, education, and other fields, I propose that three lessons emerge consistently from them.

First, few programs can be shown to work in properly randomized and replicated trials. Despite complex and impressive-sounding empirical arguments by advocates and analysts, we should be very skeptical of claims for the effectiveness of new, counterintuitive programs and policies, and we should be reluctant to trump the trial-and-error process of social evolution in matters of economics or social policy.

Second, within this universe of programs that are far more likely to fail than succeed, programs that try to change people are even more likely to fail than those that try to change incentives. A litany of program ideas designed to push welfare recipients into the workforce failed when tested in those randomized experiments of the welfare-reform era; only adding mandatory work requirements succeeded in moving people from welfare to work in a humane fashion. And mandatory work-requirement programs that emphasize just getting a job are far more effective than those that emphasize skills-building. Similarly, the list of failed attempts to change people to make them less likely to commit crimes is almost endless—prisoner counseling, transitional aid to prisoners, intensive probation, juvenile boot camps—but the only program concept that tentatively demonstrated reductions in crime rates in replicated RFTs was nuisance abatement, which changes the environment in which criminals operate. (This isn’t to say that direct behavior-improvement programs can never work; one well-known program that sends nurses to visit new or expectant mothers seems to have succeeded in improving various social outcomes in replicated independent RFTs.)

And third, there is no magic. Those rare programs that do work usually lead to improvements that are quite modest, compared with the size of the problems they are meant to address or the dreams of advocates.

Razib Khan at Discover Magazine:

A friend once observed that you can’t have engineering without science, making the whole concept of “social engineering” somewhat farcical. Jim Manzi has an article in City Journal which reviews the checkered history of scientific methods as applied to humanity, What Social Science Does—and Doesn’t—Know: Our scientific ignorance of the human condition remains profound.

The criticisms of a scientific program as applied to humanity are deep, and two pronged. As Manzi notes the “causal density” of human phenomena make teasing causation from correlation very difficult. Additionally, the large scale and humanistic nature of social phenomena make them ethically and practically impossible to apply methods of scientific experimentation. This is why social scientists look for “natural experiments,” or involve extrapolation from “WEIRD” subject pools. But as Manzi notes many of the correlations themselves are highly context sensitive and not amenable to replication.

Arnold Kling:

If David Brooks is going to give out his annual awards for most important essays, I would nominate this one.

One of the lessons that is implicit in the essay (and that I think that Manzi ought to make explicit) is, “Don’t trust one-offs.” That is, do not draw strong conclusions based on a single experiment, no matter how well constructed. Instead, wait until many experiments have been conducted, in a variety of settings and using a variety of techniques. An example of a one-off that generated a lot of recent excitement is the $320,000 kindergarten teacher study.

Mark Kleiman:

I’m sorry, but this is incoherent. What is this magical “trial-and-error process” that does what scientific inquiry can’t do? On what basis are we to determine whether a given trial led to successful or unsuccessful results? Uncontrolled before-and-after analysis, with its vulnerability to regression toward the mean? And where is the mystical “social evolution” that somehow leads fit policies to survive while killing off the unfit?

Without any social-scientific basis at all (unless you count Gary Becker’s speculations) we managed to expand incarceration by 500 percent between 1975 and the present. Is that fact – the resultant of a complicated interplay of political, bureaucratic, and professional forces – to be accepted as evidence that mass incarceration is a good policy, and the “counter-intuitive” finding that, past a given point, expanding incarceration tends, on balance, to increase crime be ignored because it’s merely social science? Should the widespread belief, implemented in policy, that only formal treatment cures substance abuse cause us to ignore the evidence to the contrary provided by both naturalistic studies and the finding of the HOPE randomized controlled trial that consistent sanctions can reliably extinguish drug-using behavior even among chronic criminally-active substance abusers?

For some reason he doesn’t specify, Manzi regards negative trial results as dispositive evidence that social innovators are silly people who don’t understand “causal density.” So he accepts – as well he should – the “counter-intuitive” result that juvenile boot camps were a bad idea. But why are those negative results so much more impressive than the finding that raising offenders’ reading scores tends to reduce their future criminality?

Surely Manzi is right to call for metholological humility and catholicism; social knowledge does not begin and end with regressions and controlled trials. But the notion that prejudices embedded in policies reflect some sort of evolutionary result, and therefore deserve our respect when they conflict with the results of careful study, really can’t be taken seriously.

Manzi responds at The American Scene:

This leads Kleiman to ask:

What is this magical “trial-and-error process” that does what scientific inquiry can’t do? On what basis are we to determine whether a given trial led to successful or unsuccessful results? Uncontrolled before-and-after analysis, with its vulnerability to regression toward the mean? And where is the mystical “social evolution” that somehow leads fit policies to survive while killing off the unfit?

I devoted a lot of time to this related group of questions in the forthcoming book. The shortest answer is that social evolution does not allow us to draw rational conclusions with scientific provenance about the effectiveness of various interventions, for methodological reasons including those that Kleiman cites. Social evolution merely renders (metaphorical) judgments about packages of policy decisions as embedded in actual institutions. This process is glacial, statistical and crude, and we live in the midst of an evolutionary stream that we don’t comprehend. But recognition of ignorance is superior to the unfounded assertion of scientific knowledge.

Kleiman then goes on to ask this:

Without any social-scientific basis at all (unless you count Gary Becker’s speculations) we managed to expand incarceration by 500 percent between 1975 and the present. Is that fact – the resultant of a complicated interplay of political, bureaucratic, and professional forces – to be accepted as evidence that mass incarceration is a good policy, and the “counter-intuitive” finding that, past a given point, expanding incarceration tends, on balance, to increase crime be ignored because it’s merely social science?

My answer is yes, it should be counted as evidence, but that it is not close to dispositive. We can not glibly conclude that we now live in the best of all possible worlds. I devoted several chapters to trying to lay out some principles for evaluating when, why and how we should consider, initiate and retrospectively evaluate reforms to our social institutions.

Kleiman’s last question is:

Should the widespread belief, implemented in policy, that only formal treatment cures substance abuse cause us to ignore the evidence to the contrary provided by both naturalistic studies and the finding of the HOPE RCT that consistent sanctions can reliably extinguish drug-using behavior even among chronic criminally-active substance abusers?

My answer to this is no, and a large fraction of the article (and the book) is devoted to making the case that exactly such randomized trials really are the gold standard for the kind of knowledge that is required to make reliable, non-obvious predictions that rationally outweigh settled practice and even common sense. The major caveat to the evaluation of this specific program (about which Kleiman is deeply expert) is whether or not the experiment has been replicated, as I also make the argument that replication is essential to drawing valid conclusions from such experiments – the principle that Arnold Kling called in a review of the article, “Don’t trust one-offs.”

Steven Pearlstein at WaPo

Steve Sailer:

That all sounds plausible, but I’ve been a social science stats geek since 1972, when the high school debate topic that year was education, so I’m aware that Manzi’s implications are misleading.

First, while experiments are great, correlation studies of naturally occurring data can be extremely useful. Second, a huge number of experiments have been done in the social sciences.

Third, the social sciences have come up with a vast amount of knowledge that is useful, reliable, and nonobvious, at least to our elites.

For example, a few years, Mayor Bloomberg and NYC schools supremo Joel Klein decided to fix the ramshackle admissions process to the gifted schools by imposing a standardized test on all applicants. Blogger Half Sigma immediately predicted that the percentage of Asians and whites admitted would rise at the expense of blacks and Hispanics, which would cause a sizable unexpected political problem for Bloomberg and Klein. All that has come to pass.

This inevitable outcome should have been obvious to Bloomberg and Klein from a century of social science data accumulation, but it clearly was not obvious to them.

No, the biggest problem with social science research is not methodological; it’s that we just don’t like the findings. The elites of America don’t like what the social sciences have uncovered about, say, crime, education, discrimination, immigration, and so forth.

Andrew Sullivan:

But there is a concept in this crucial conservative distinction between theoretical and practical wisdom that has been missing so far: individual judgment. A social change can never be proven in advance to be the right answer to a pressing problem. We can try to understand previous examples; we can examine large randomized trials; but in the end, we have to make a judgment about the timeliness and effectiveness of certain changes. It is the ability to sense when such a moment is ripe that we used to call statesmanship. It is that quality that no wonkery can ever replace.

It is why we elect people and not algorithms.

Will Wilkinson:

In my thinking about the contrasts between Rawlsian and Hayekian liberalism, I’ve begun to think about the former as the “liberalism of respect” and the latter as the “liberalism of discovery.” The liberalism of discovery recognizes the pervasiveness of our ignorance and the necessity of liberty for the emergence of useful knowledge. I would argue that the ideal of a social order embodying respect for persons as free and equal–the ideal of the liberalism of respect–comes to seem appealing only after a society has attained a certain level of economic development and general education, and these are largely consequences of a prior history of the relatively free play of the mechanisms of discovery celebrated by liberals like Hayek and Jim. But liberals of respect have tended to overlook the conditions under which people come to find the their favored ideal worth aspiring to, and so have tended to fail to acknowledge in their theories of justice the role of the institutions of discovery in creating and maintaining a society of mutual respect and fair reciprocity.

Via Sullivan, Kleiman responds to Manzi:

I suppose I’ll have to read Manzi’s book to find out how existing practices constitute “(metaphorical) judgments about packages of policy decisions;” I’m inclined to regard them as mostly mere resultants-of-forces, with little claim to deference. (Thinking that existing arrangements somehow embody tacit knowledge is a different matter from thinking that big changes are likely to have unexpected consequences, mostly bad, though both are arguments for caution about grand projects.)

I’m also less unimpressed than Manzi is with how much non-obvious stuff about humans living together the social sciences have already taught us. That supply and demand will, without regulation, come into equilibrium at some price was a dazzling and radical social-scientific claim when Adam Smith and his friends suggested it. So too for Ricardo’s analysis of comparative advantage, which, while it doesn’t fully support the free-trade religion that has grown up around it, at least creates a reasonable presumption that trade is welfare-increasing.

The superiority of reward to punishment in changing behavior; the importance of cognitive-dissonance and mean-regression effects in (mis)shaping individual and social judgments; the intractable problem of public-goods contributions; the importance of social capital; the problems created by asymmetric information and the signaling processes it supports; the crucial importance of focal points; the distinction between positive-feedback and negative-feedback processes; the distinction between zero-sum and variable-sum games; the pervasiveness of imperfect rationality in the treatment of risk and of time-value, and the consequent possibility that people will, indeed, damage themselves voluntarily: none of these was obvious when proposed, and all of them are now, I claim, sufficiently well-established to allow us to make policy choices based on them, with some confidence about likely results. (So, for that matter, is the Keynesian analysis of insufficient demand and what to do about it.)

But, if I read Manzi’s response correctly, my original comment allowed a merely verbal disagreement to exaggerate the extent of the underlying substantive disagreement. If indeed Manzi can offer some systematic analysis of how to look at existing institutions, figure out which ones might profitably be changed, try out a range of plausible changes, gather careful evidence about the results of those changes, and modify further in light of those results, then Manzi proposes what I would call a “scientific” approach to making public policy.

Manzi responds to Kleiman:

I think that he is reading my response correctly. While I don’t think that “all I meant” was that “you shouldn’t read some random paper in an economics or social-pysch journal” and propose X, I certainly believe that. Most important, I acknowledge enthusiastically his “sauce for the goose is sauce for the gander” point that the recognition of our ignorance should apply to things that I theorize are good ideas, as much as it does to anything else. The law of unintended consequences does not only apply to Democratic proposals.

In fact, I have argued for supporting charter schools instead of school vouchers for exactly this reason. Even if one has the theory (as I do) that we ought to have a much more deregulated market for education, I more strongly hold the view that it is extremely difficult to predict the impacts of such drastic change, and that we should go one step at a time (even if on an experimental basis we are also testing more radical reforms at very small scale). I go into this in detail for the cases of school choice and social security privatization in the book.

Megan McArdle:

I have been reading with great interest the back-and-forth between Mark Kleiman and Jim Manzi on how much more humble we ought to be about new policy changes.  I know and like both men personally, as well as having a healthy respect for two formidable intellects, so I’ve greatly enjoyed the exchange.

Naturally, this has put me in mind of just how hard it is to predict policy outcomes–how easy it is to settle on some intuitively plausible outcome, without considering some harder-to-imagine countervailing force.

Consider the supply-siders.  The thing is intuitively appealling; when we get more money from working, we ought to be willing to.  And it is a mathematical truism that revenue must maximize at some point.  Why couldn’t we be on the right-hand side of the Laffer Curve?

It was entirely possible that we were; unfortunately, it wasn’t true.  And one of the reasons that supply-siders failed was that they were captivated by that one appealing intuition.  In economics, it’s known as the “substitution effect”–as your wages go up, leisure becomes relatively more expensive relative to work, so you tend to do less of the former, more of the latter.

Unfortunately, the supply-siders missed another important effect, known as the “income effect”.  Which is to say that as you get richer, you demand more of some goods, and less of others.  And one of the goods you demand more of as you get richer–a class of goods known as “superior goods”–is leisure.

Of course, some people are so driven that they will simply work until they drop in the traces.  But most people like leisure.  So say you raise the average wage by 10%.  Suddenly people are bringing home 10% more income every hour.  Now, maybe this makes them all excited so they decide to work more.  On the other hand, maybe they decide they were happy at their old income, and now they can enjoy their old income while working 9% fewer hours.  Cutting taxes could actually reduce total output.

(We will not go into the question of how much most people can control their hours–on the one hand, most people can’t, very well, but on the other hand, those who can tend to be the high-earning types who pay most of your taxes.)

Which happens depends on which effect is stronger.  In practice, apparently neither was strong enough to thoroughly dominate, at least not when combined with employers who still demanded 40 hour weeks.  You do probably get a modest boost to GDP from tax cuts.  But you also get falling tax revenue.

Naturally, even-handedness demands that I here expose the wrong-headedness of some liberal scheme.  And as it happens, I have one all ready in the oven here:  the chimera of reducing emergency room use.  The argument that health care reform could somehow at least partially pay for itself by keeping people from using the emergency room was always dubious.  As I, and others argued, there’s not actually that much evidence that people use the emergency room because they are uninsured–rather than because they have to work during normal business hours, are poor planners, or are afraid that immigration may somehow find them at a free clinic.

Moreover, we argued, non-emergent visits to the emergency room mostly use the spare capacity of trauma doctors; the average cost may be hundreds of dollars, but the marginal cost of slotting ear infections in when you don’t happen to have a sucking chest wound, is probably pretty minimal.

But even I was not skeptical enough to predict what actually happened in Massachusetts, which is that emergency room usage went up after they implemented health care reform.

Leave a comment

Filed under Go Meta

Duelling Banjos Or Duelling New York Times Columnists

Ross Douthat at NYT:

Cap-and-trade’s backers are correct to point the finger rightward. If their bill is dead, it was the American conservative movement that ultimately killed it. Climate legislation wasn’t like health care, with Democrats voting “yes” in lockstep. There was no way to get a bill through without some support from conservative lawmakers. And in the global warming debate, there’s a seemingly unbridgeable gulf between the conservative movement and the environmentalist cause.

To understand why, it’s worth going back to the 1970s, the crucible in which modern right-wing politics was forged.

The Seventies were a great decade for apocalyptic enthusiasms, and none was more potent than the fear that human population growth had outstripped the earth’s carrying capacity. According to a chorus of credentialed alarmists, the world was entering an age of sweeping famines, crippling energy shortages, and looming civilizational collapse.

It was not lost on conservatives that this analysis led inexorably to left-wing policy prescriptions — a government-run energy sector at home, and population control for the teeming masses overseas.

Social conservatives and libertarians, the two wings of the American right, found common ground resisting these prescriptions. And time was unkind to the alarmists. The catastrophes never materialized, and global living standards soared. By the turn of the millennium, the developed world was worrying about a birth dearth.

This is the lens through which most conservatives view the global warming debate. Again, a doomsday scenario has generated a crisis atmosphere, which is being invoked to justify taxes and regulations that many left-wingers would support anyway. (Some of the players have even been recycled. John Holdren, Barack Obama’s science adviser, was a friend and ally of Paul Ehrlich, whose tract “The Population Bomb” helped kick off the overpopulation panic.)

History, however, rarely repeats itself exactly — and conservatives who treat global warming as just another scare story are almost certainly mistaken.

Rising temperatures won’t “destroy” the planet, as fearmongers and celebrities like to say. But the evidence that carbon emissions are altering the planet’s ecology is too convincing to ignore. Conservatives who dismiss climate change as a hoax are making a spectacle of their ignorance.

But this doesn’t mean that we should mourn the death of cap-and-trade. It’s possible that the best thing to do about a warming earth — for now, at least — is relatively little. This is the view advanced by famous global-warming heretics like Bjorn Lomborg and Freeman Dyson; in recent online debates, it has been championed by Jim Manzi, the American right’s most persuasive critic of climate-change legislation.

Their perspective is grounded, in part, on the assumption that a warmer world will also be a richer world — and that economic development is likely to do more for the wretched of the earth than a growth-slowing regulatory regime.

But it’s also grounded in skepticism that such a regime is possible. Any attempt to legislate our way to a cooler earth, the argument goes, will inevitably resemble the package of cap-and-trade emission restrictions that passed the House last year: a Rube Goldberg contraption whose buy-offs and giveaways swamped its original purpose.

Jim Manzi at The American Scene:

Ross Douthat has a column in today’s New York Times in which he kindly mentions me, but far more important, manages to make a multi-layered argument for why an informed rational observer should oppose cap-and-trade legislation within the length restrictions of an op-ed. In my view, the position that Ross presents – basically, that the cure is worse than the disease – is the rationally persuasive argument that won the day in recent legislative debates in the Congress.

I believe the debate and politics of this issue have, so far, played out along lines I set forth a couple of years ago. That doesn’t mean, however, that the debate is permanently settled. Nothing in American politics ever is, and the attempt to introduce cap-and-trade through legislation, regulation and/or judicial rulings is likely to continue for many years.

David Leonhardt at NYT:

Mr. Douthat mentions Mr. Ehrlich in his column today, to explain why Republicans have blocked action on global warming:

The Seventies were a great decade for apocalyptic enthusiasms, and none was more potent than the fear that human population growth had outstripped the earth’s carrying capacity. According to a chorus of credentialed alarmists [including Paul Ehrlich], the world was entering an age of sweeping famines, crippling energy shortages, and looming civilizational collapse.

It was not lost on conservatives that this analysis led inexorably to left-wing policy prescriptions — a government-run energy sector at home, and population control for the teeming masses overseas.

The analogy to global warming is obvious. Just as ingenuity came to the rescue in the past, allowing people to use resources more efficiently than they ever had before, it could do so again — providing us with ways to emit far less carbon for every dollar of gross domestic product.

And I — like many others, I imagine — would be thrilled if that were what the future held. But I think there are two big reasons to doubt that we’re on another Ehrlich-Simon path when it comes to global warming.

The first is basic economics. When the problem is resource scarcity, companies and individuals have a powerful incentive to become more efficient. It keeps their costs down. Mr. Simon understood this, and it’s the fundamental reason he won the bet.

But global warming is different. The fact that carbon emissions are warming the planet doesn’t make it more expensive to produce those emissions. So companies do not have an ever-increasing incentive to emit less — the way they would if the problem were, say, a lack of oil. Global warming doesn’t solve itself the way that resource scarcity does.

The second reason is the accumulation of evidence. Almost as soon as Mr. Ehrlich and Mr. Simon made their bet in 1980, Mr. Simon’s prediction started looking good. In 1981, as Mr. Tierney wrote, “grain prices promptly fell and reached historic lows during the 1980s, continuing a long-term decline.” (Mr. Tierney noted that an ally of Mr. Ehrlich ignored this trend at the time and focused instead on “blips in the graph.”)

In recent years, though, anyone who had bet against global warming would look as wrong as Mr. Ehrlich did. The Greenland and Antarctic ice sheets are shrinking at an accelerating rate. Scientists have recently revised upwards their predictions of sea-level rises. The planet’s 10 hottest years on record, according to NASA, are: 2005, 2007, 2009, 1998, 2002, 2003, 2006, 2004, 2001 and 2008. This year is on pace to displace 2005 as No. 1.

Matthew Yglesias:

[…] I’ll have a go at this one:

[Conservative opposition to carbon pricing legislation] is also grounded in skepticism that such a regime is possible. Any attempt to legislate our way to a cooler earth, the argument goes, will inevitably resemble the package of cap-and-trade emission restrictions that passed the House last year: a Rube Goldberg contraption whose buy-offs and giveaways swamped its original purpose.

Two objections. One—ACES certainly had its Rube Goldberg qualities, but it hardly “swamped its original purpose” of reducing the risk of climate catastrophe at small economic cost.

Two—if Republican members of congress looked at ACES and thought “nice try, but too many side deals” they were, of course, free at any time to introduce an alternative piece of legislation. They did not. And you can tell by the rhetoric of the broader conservative movement (”cap and tax,” “job-killing energy tax,” etc.) that there was no openness to this kind of effort to find more optimal ways of pursuing environmental goals. On the contrary, every move congressional Republicans have made—from adopting a House posture that made it necessary to forge costly side-deals with coal belt Democrats to adopting a Senate posture that ensures carbon regulation will be left primarily to the EPA—has tended to simultaneously undermine the goal of reducing greenhouse gas emissions while also making the economic impact of the regulations more costly.

The reality is that I don’t think American conservatives need a reason, as such, to oppose effective policies to reduce carbon dioxide emissions. Siding with the Chamber of Commerce against proposed new environmental regulation is just what the conservative movement does. Insofar as any particular person wants to dissent from that judgment in a vocal and persistent way, that person would simply be read out of the movement. The extent to which the conservative movement has its grip on any particular politician (or, indeed, newspaper columnist) can change from year-to-year or day-to-day but there’s no real opening for a conservative person or institution to make a genuine effort to help environmentalists without turning apostate. Things are different in Denmark, but that’s true of many subjects.

Brad DeLong

Douthat responds to Leonhardt and Yglesias:

There are important lessons to be drawn from the doomsday scenarios of the 1970s, but conservatives who expect the warming trend to suddenly reverse itself have almost certainly overlearned them. I would offer two caveats, though. One is that while the economics of resource scarcity did militate in favor of conservation in a way they don’t with carbon emissions, the same wasn’t obviously true of population growth, where many serious people were convinced that the economic incentives were leading the whole world straight into a disastrous Malthusian trap. In hindsight, what we know about demographic transitions suggests otherwise — but that was much less clear in, say, 1969 or so than it is today. (Which explains, in turn, why that era was marked by various proposals and policies that effectively treated “excess” children the way cap-and-trade treats carbon emissions: As something to be regulated or taxed or otherwise coerced out out of existence.)

The second is that the Simon-Ehrlich bet that Leonhardt references took place in 1980, after more than two decades of exponential population growth and population alarmism (and, of course, various disastrous and inhumane policy experiments). So Paul Ehrlich probably thought he had a fair amount of historical evidence on his side when he made it. And if there were an equivalent bet on climate — which, to be clear, I wouldn’t make, since I expect temperatures to continue to rise — it would be taking place now, or a couple of years ago, rather than in 2000 or 1990.

Elsewhere, meanwhile, Matt Yglesias criticizes me for saying that the cap-and-trade bill’s various buy-offs and giveaways “swamp its original purpose.” It’s a good point: I should have said threaten to swamp its original purpose. We know that the buy-offs and giveaways ended up swamping the bill’s secondary purpose (raising revenue, that is), but we don’t know how they’ll effect the primary purpose of reducing emissions: That depends, among other things, on just how imperfect (or corrupt, or easily gamed) the system of “carbon offsets” ends up being. (After several years of implementation, it’s still unclear how well Europe’s emission-trading system works.) In theory, though, Yglesias is right: The legislation as passed by the House could achieve reductions in American emissions in spite of all the side deals and horse-trading. These projected reductions are woefully small in the global scheme of things (if there’s a more optimistic estimate than the one Jim Manzi cites here, please let me know), but they’re substantial in the domestic context.

Yglesias goes on to argue that Republicans are to blame for the giveaways and buy-offs anyway, because it was their intransigence that “made it necessary to forge costly side-deals with coal belt Democrats.” I’m not sure I agree with this: A world where a bloc of Republicans had come on board would probably have been a world where even more Democrats jumped ship (this was not an obviously popular piece of legislation), and you might have just ended up with a slightly different set of side-deals.

Paul Krugman at NYT:

Never say that the gods lack a sense of humor. I bet they’re still chuckling on Olympus over the decision to make the first half of 2010 — the year in which all hope of action to limit climate change died — the hottest such stretch on record.

Of course, you can’t infer trends in global temperatures from one year’s experience. But ignoring that fact has long been one of the favorite tricks of climate-change deniers: they point to an unusually warm year in the past, and say “See, the planet has been cooling, not warming, since 1998!” Actually, 2005, not 1998, was the warmest year to date — but the point is that the record-breaking temperatures we’re currently experiencing have made a nonsense argument even more nonsensical; at this point it doesn’t work even on its own terms.

But will any of the deniers say “O.K., I guess I was wrong,” and support climate action? No. And the planet will continue to cook.

So why didn’t climate-change legislation get through the Senate? Let’s talk first about what didn’t cause the failure, because there have been many attempts to blame the wrong people.

First of all, we didn’t fail to act because of legitimate doubts about the science. Every piece of valid evidence — long-term temperature averages that smooth out year-to-year fluctuations, Arctic sea ice volume, melting of glaciers, the ratio of record highs to record lows — points to a continuing, and quite possibly accelerating, rise in global temperatures.

Nor is this evidence tainted by scientific misbehavior. You’ve probably heard about the accusations leveled against climate researchers — allegations of fabricated data, the supposedly damning e-mail messages of “Climategate,” and so on. What you may not have heard, because it has received much less publicity, is that every one of these supposed scandals was eventually unmasked as a fraud concocted by opponents of climate action, then bought into by many in the news media. You don’t believe such things can happen? Think Shirley Sherrod.

Did reasonable concerns about the economic impact of climate legislation block action? No. It has always been funny, in a gallows humor sort of way, to watch conservatives who laud the limitless power and flexibility of markets turn around and insist that the economy would collapse if we were to put a price on carbon. All serious estimates suggest that we could phase in limits on greenhouse gas emissions with at most a small impact on the economy’s growth rate.

So it wasn’t the science, the scientists, or the economics that killed action on climate change. What was it?

The answer is, the usual suspects: greed and cowardice.

Jonathan Chait at TNR:

But the truth is that public opinion played a major role as well. It’s not that Americans oppose action on greenhouse gas emissions — most polls show they favor it. It’s that they lack strong enough convictions to support the dislocations that any meaningful bill would impose. An AP poll, for instance, found that 59% of Americans would oppose any climate bill if it would cause their electricity bill to rise by even $10 a month. In an environment like this, opponents have a huge advantage in the battle for public opinion.

None of this is to say that a climate bill would be impossible without stronger public support. It’s the kind of issue that requires responsible elites. You would need Republicans to decide that the issue was vital and work with Democrats to craft a mutually-acceptable solution. Instead they positioned themselves to fan the flames of public opposition to any sacrifice or dislocation. The combination of a public with soft views on the issue and an opportunistic GOP made a bill impossible.

My other difference with Krugman is that I don’t think the failure of a bill means the planet will burn. I think it means that the Environmental Protection Agency will take over the issue. This isn’t ideal from an economic point of view. But it is ideal from Congress’s point of view — or, at least, the conservative Democrats and moderate Republicans who hold the deciding votes in Congress. Decreasing economic efficiency by limiting carbon emissions through regulation, rather then a more efficient cap and trade bill, in order to let the Senate avoid voting on the issue is a win for Ben Nelson and Olympia Snowe.

If Obama can hang tough on carbon emissions, he can force the energy industry to put real pressure on Congress to pass a climate bill. Obviously the threat is too abstract right now. But liberals need to get used to the idea that the EPA is the short-term solution and start figuring out how to make that work. the death of legislation in 2010 is not the death of a solution.

David Roberts at Grist:

With the climate bill officially dead, there’s already a trickle of “who’s to blame and what they should have done differently” pieces. I expect it will soon become a flood.

Most of these pieces will focus in the wrong places. Take Lee Wasserman’s new op-ed, “Four Ways to Kill a Climate Bill,” an instant classic of the genre. Wasserman doesn’t like the way Dems talked about the issue and he doesn’t like the policy framework they put forward, which is of course his right. But the implication of the piece is that if Dems had talked the way he wanted them to talk, and put forward the bill he wanted them to put forward, the outcome would have been different. There’s just no reason at all to think that’s true.

Expect to see all sorts of pieces arguing that better “messaging” could have saved the day, e.g., this piece on Daily Kos. Others will argue that their particular policy pony — carbon tax, or cap-and-dividend, or massive R&D money — would have been victorious. Others will argue that demonizing energy incumbents to fire up the base would have worked. Others will blame Obama for not riding to the rescue (Randy’s got a roundup of these).

All this is well-meaning, but it misses the biggest impediments. I don’t think messaging, policy design, or base mobilization are irrelevant — I’ve written plenty about all of them — but their effects were marginal relative to other structural factors. Were I doing an autopsy on the death of the bill, here are the causal factors I’d single out, listed in order of significance:

1. The broken Senate

The U.S. Senate is already an unrepresentative institution: Wyoming’s two senators each represent 272,000 people; California’s two senators each represent 18,481,000 people. On top of this undemocratic structure is a series of rules that have been abused with increasing frequency.

The main one, of course, is the default supermajority requirement that’s been imposed by abuse of the filibuster. I’ll have much more to say on this soon, but suffice to say, the supermajority requirement has perverse, deleterious consequences that extend much farther than most progressives seem to understand.

For a complex, contentious, and regionally charged issue like climate change, the supermajority requirement presents a virtually insuperable barrier to action. I don’t think we would have the climate bill of our dreams if only 51 votes were required, but I’m fairly sure something along the lines of Waxman-Markey or stronger could have made it over the finish line.

2. The economy

You may have noticed that Americans aren’t in a very good mood right now. Unemployment is high and people are suffering. Given that most people don’t follow politics very closely, or at all, that translates to anger and suspicion toward whoever’s in power (despite the fact that, yes, it’s Bush and the Republicans who are responsible for both the economic downturn and the deficit).

Yes, the left could have done a better job of framing a climate/energy bill as an economic boost — mainly by starting earlier and being much more consistent — but the fact is, the environment-vs.-economy frame has been established by a well-funded 40-year campaign on the right. It can’t be overturned in two years. The American people were just bound to be indifferent and/or suspicious of grand environmental initiatives during a time of economic pain.

Those two are the biggies

Leave a comment

Filed under Environment

All This Presupposes That Elvis Is Actually Dead

Al Gore at The New Republic:

The continuing undersea gusher of oil 50 miles off the shores of Louisiana is not the only source of dangerous uncontrolled pollution spewing into the environment. Worldwide, the amount of man-made CO2 being spilled every three seconds into the thin shell of atmosphere surrounding the planet equals the highest current estimate of the amount of oil spilling from the Macondo well every day. Indeed, the average American coal-fired power generating plant gushes more than three times as much global-warming pollution into the atmosphere each day—and there are over 1,400 of them.

Just as the oil companies told us that deep-water drilling was safe, they tell us that it’s perfectly all right to dump 90 million tons of CO2 into the air of the world every 24 hours. Even as the oil spill continues to grow—even as BP warns that the flow could increase multi-fold, to 60,000 barrels per day, and that it may continue for months—the head of the American Petroleum Institute, Jack Gerard, says, “Nothing has changed. When we get back to the politics of energy, oil and natural gas are essential to the economy and our way of life.” His reaction reminds me of the day Elvis Presley died. Upon hearing the tragic news, Presley’s manager, Colonel Tom Parker, said, “This changes nothing.”

Jim Manzi at TNR:

For years, much of the political right has claimed that global warming is a scientific hoax perpetrated by statists in order to justify further government control over the economy. I have repeatedly pointed out that this is more or less nonsense, usually to audiences that are far less amenable to this message than the readership of The New Republic, with predictable results. It is certainly true, of course, that there are political actors for whom climate change is a convenient excuse for amassing power, and scientific researchers, bankers, and businesspeople who are just jumping onto a funding gravy train; but this doesn’t mean that the underlying technical risk assessment is invalid.

The political left has its own conspiracy theory on the issue. It was on almost perfect display in Al Gore’s article (“The Crisis Comes Ashore”) in the June 10 TNR. Gore argues that public confidence in the warnings of “looming catastrophe” presented in “the most elaborate and impressive scientific assessment in the history of our civilization” is being undermined by a “cynical and lavishly funded disinformation campaign” paid for by “carbon polluters.” It is certainly true, of course, that some oil companies and other interest groups have funded PR campaigns in pursuit of their narrowly-defined self-interest; but once again, this shouldn’t change our rational evaluation of the environmental impact of greenhouse gas accumulations one way or the other.

Gore agrees in his article that the proper response to this issue is not to be found in the political sound and light show, but in a rational assessment of risks, saying that “rather than relying on visceral responses, we have to draw upon our capacity for reasoning, communicating clearly with one another, forming a global consensus on the basis of science…”. Gore goes on to suggest a technical foundation for this reasoning process:

Over the last 22 years, the Intergovernmental Panel on Climate Change has produced four massive studies warning the world of the looming catastrophe that is being caused by the massive dumping of global-warming pollution into the atmosphere.

So, what does the IPCC actually have to say about what we should expect to happen as a result of our “massive dumping of global-warming pollution into the environment”

According to the IPCC’s currently-governing Fourth Assessment Report, under a reasonable set of assumptions for global economic and population growth (Scenario A1B), the world should expect to warm by about 3°C over roughly the next century (Table SPM.3). Even in the most extreme IPCC marker scenario (A1F1), the best estimate is that we should expect warming of about 4°C over roughly the next century. How bad would that be? Also according to the IPCC (page 17), a global increase in temperature of 4°C should cause the world to have about 1 to 5 percent lower economic output than it would otherwise have. So if we do not take measures to ameliorate global warming, the world should expect sometime in the 22nd century to be about 3 percent poorer than it otherwise would be (though still much richer per capita than today).

Prior to consideration of the more detailed economic issues—e.g., costs versus benefits of attempts to forestall the problem; the danger of worse-than-expected outcomes, etc.—pause to recognize that according to the IPCC the expected economic costs of global warming under the plausible scenarios for future economic growth are likely to be about 3 percent of GDP more than 100 years from now. This is pretty far from the rhetoric of global destruction and Manhattan as an underwater theme park.

[…]

The only real argument for rapid, aggressive emissions abatement, then, boils down to the weaker form of the uncertainty argument: that you can’t prove a negative. The problem with using this rationale to justify large economic costs can be illustrated by trying to find a non-arbitrary stopping condition for emissions limitations. Any level of emissions imposes some risk. Unless you advocate confiscating all cars and shutting down every coal-fired power plant on earth literally tomorrow morning, you are accepting some danger of catastrophic warming. You must make some decision about what level of risk is acceptable versus the costs of avoiding this risk. Once we leave the world of odds and handicapping and enter the world of the Precautionary Principle—the Pascal’s Wager-like argument that the downside risks of climate change are so severe that we should bear almost any cost to avoid this risk, no matter how small—there is really no principled stopping point derivable from our understanding of this threat.

Think about this quantitatively for a moment. Suspend disbelief about the real world politics, and assume that we could have a perfectly implemented global carbon tax. If we introduced a tax high enough to keep atmospheric carbon concentration to no more than 420 ppm (assuming we could get the whole world to go along), we would expect, using the Nordhaus analysis as a reference point, to spend about $14 trillion more than the benefits that we would achieve in the expected case. To put that in context, that is on the order of the annual GDP of the United States of America. That’s a heck of an insurance premium for an event so low-probability that it is literally outside of a probability distribution. Gore has a more aggressive proposal that if implemented through an optimal carbon tax (again, assuming we can get the whole word to go along) would cost more like $20 trillion in excess of benefits in the expected case. Of course, this wouldn’t eliminate all uncertainty, and I can find credentialed scientists who say we need to reduce emissions even faster. Without the recognition that the costs we would pay to avoid this risk have some value, we would be chasing an endlessly receding horizon of zero risk.

So then, how should we confront this lack of certainty in our decision logic? At some intuitive level, it is clear that rational doubt about our probability distribution of forecasts for climate change over a century should be greater than our doubt our forecasts for whether we will get very close to 500 heads if we flip a fair quarter 1,000 times. This is true uncertainty, rather than mere risk, and ought to be incorporated into our decision somehow. But if we can’t translate this doubt into an alternative probability distribution that we should accept as our best available estimate, and if we can’t simply accept “whatever it takes” as a rational decision logic for determining emissions limits, then how can we use this intuition to weigh the uncertainty-based fears of climate change damage rationally? The only way I can think of is to attempt to find other risks that we believe present potential unquantifiable dangers that are of intuitively comparable realism and severity to that of outside-of-distribution climate change, and compare our economic expenditure against each.

Unfortunately for humanity, we face many dimly-understood dangers. Weitzman explicitly considers an asteroid impact and bioengineering technology gone haywire. It is straightforward to identify others. A regional nuclear war in central Asia kicking off massive global climate change (in addition to its horrific direct effects), a global pandemic triggered by a modified version of the HIV or Avian Flu virus, or a rogue state weaponizing genetic-engineering technology are all other obvious examples. Any of these could kill hundreds of millions to billions of people.

Consider the comparison of a few of these dangers to that of outside-of-distribution climate change dangers. The consensus scientific estimate is that there is a 1-in-10,000 chance of an asteroid large enough to kill a large fraction of the world’s population impacting the earth in the next 100 years. That is, we face a 0.01% chance of sudden death of a good chunk of people in the world, likely followed by massive climate change on the scale of that which killed off the non-avian dinosaurs. Or consider that Weitzman argues that we can distinguish between unquantifiable extreme climate change risk and unquantifiable dangers from runaway genetic crop modification because “there exists at least some inkling of a prior argument making it fundamentally implausible that Frankenfood artificially selected for traits that humans and desirable will compete with or genetically alter the wild types that nature has selected via Darwinian survival of the fittest.” That does not seem exactly definitive. What is the realism of a limited nuclear war over the next century—with plausible scenarios ranging from Pakistan losing control of its nuclear arsenal and inducing a limited nuclear exchange with India, to a war between a nuclearized Iran and Israel?

Brad Plumer at TNR:

Let me start by saying that Manzi is easily one of the smartest, most interesting conservative writers out there when it comes to global warming. Many people on the right, unfortunately, still stick to the crazed view that climate science is all a hoax. Manzi wants nothing to do with those folks. He agrees with the mainstream scientific consensus that human activities are heating up the planet and that this poses a problem (and he’s taken a lot of flak from conservatives like Rush Limbaugh for staking out this position). Where he parts ways with most liberals is on just how big a problem a hotter planet will be.

Manzi bases his argument on his reading of the IPCC’s 2007 Fourth Assessment Report. According to the IPCC’s own estimates, he points out, a temperature rise of 4°C can be expected to reduce global GDP by about 3 percent in 2100. And on the flip side, the IPCC pegs the cost of keeping carbon concentrations in the atmosphere below a “safe” level of 450 parts per million at around 6 percent of GDP. And so, Manzi concludes, mitigation probably isn’t worth it. (To be fair, he has elsewhere expressed interest in a small carbon price to fund clean-technology research, so he’s not in the “do-nothing” camp.)

I see a couple problems with this argument. The first is that Manzi is clinging way too tightly to the IPCC report. Yes, the IPCC puts out the best summary of scientific knowledge about our climate system. I rely on it all the time. But the 2007 report is also dated. Climate science is a rapidly moving field, and more recent research has suggested that things may be bleaker than was projected three years ago. What’s more, the 2007 report had some glaring holes in it. The panel avoided making predictions about how melting ice sheets would affect sea levels because, at the time, ice-sheet dynamics were too difficult to model. This isn’t me offering up a strained reading of the IPCC’s work—the 2007 report was explicit on this point. Given that sea-level rise is likely to be one of the costliest consequences of global warming by 2100 and (especially) beyond, this is a huge omission for any sort of cost-benefit analysis.

Second, it’s a bit too simplistic to use a single global GDP figure when talking about the effects of climate change. True, a 3 percent drop in global GDP may not sound so bad. We’ll all be much richer in 2100, we can take a hit. But that top-line figure can obscure some serious distributional issues. Climate change, after all, is expected to hit developing countries much harder than wealthier ones. And as Nate Silver once noted, you could completely wipe out the poorest 81 nations in the world, with a total population of 2.8 billion, and the blow to global GDP would “only” be about 5 percent:

From a cynical utilitarian perspective, sure, maybe it would be worth it to devastate a bunch of impoverished African countries if it makes the rest of the world richer on balance. But that raises quite a few glaring ethical questions, and I’ll just note that most conservatives wouldn’t leap at this trade-off in other contexts (very few on the right would support seizing property through eminent domain for the greater good of economic development, for instance).

Third point: Harvard economist Marty Weitzman has recently been arguing that there’s plenty of uncertainty in climate projections, and the worst-case scenarios could be really freaking bad. Like, civilization-destroying bad. And that prospect, even if it’s slim, is a great reason to cut emissions—think of pollution curbs as an insurance policy against total annihilation. In reply, Manzi accuses Weitzman of doing “armchair climate science.” But that’s unfair. There are plenty of actual climate scientists who are exploring these worst-case scenarios, too. A recent paper in the Proceedings of the National Academy of Sciences concluded that there’s a roughly 5 percent chance that rising temperatures could render vast regions of the planet—like the eastern United States or most of India—simply uninhabitable. An insurance policy against that doesn’t sound too shabby.

Jonathan Chait at TNR:

I’ve been waiting for Brad Plumer to write a response to Jim Manzi’s argument, which he’s been making for several years, that preventing climate change is not worth the cost. Now that he’s done it, I urge you to check it out. Like Brad says, Manzi’s argument is probably the most persuasive case you can find against reducing carbon emissions. But it’s still not very persuasive.

Mori Dinauer at Tapped:

Bradford Plumer‘s response to Jim Manzi on climate change addresses my No. 1 complaint about conservatives who, while not denying climate change is real, think the threat is exaggerated. The do-nothing analysis is that the economic impact of pricing carbon or curbing emissions will be so great that it will be worse than doing nothing. Plumer goes into the technical reasons why we should be skeptical about this position, but I want to note that Manzi shows little interest in the non-economic consequences of climate change — it’s just one big Econ 101 puzzle to be solved.

Heather Horn at The Atlantic

Joe Romm at Climate Progress

Why would you trust a magazine that doesn’t trust itself?  In a baffling display of ‘balance as bias’ — or perhaps ‘balance as baloney‘ — The New Republic has hired right-wing misinformer Jim Manzi to spread confusion about their articles.

Maybe magazines don’t bother employing fact checkers anymore, but when I coauthored the cover story for the Atlantic Monthly in 1996, “MidEast Oil Forever?” Drifting Toward Disaster, the magazine not only edited the piece, they made me provide a credible published source for every claim.  Even today, I know magazines like Wired fact-check every article.

But TNR appears to have proudly hired Manzi to un-fact-check their articles — at least in the area of energy and the environment, Manzi mostly spreads misinformation.   Indeed, as I will show, Manzi utterly misrepresents the important work of Harvard economist Martin Weitzman, which he discusses at length but doesn’t appear to know the first thing about.

I say TNR “proudly” hired Manzi because editor Franklin Foer has a June 22 column bizarrely titled, “The In-House Critics: Keeping TNR Honest” touting this self-inflicted wound to its credibility:  “it is an honor to be the subject of their criticism.”

I know, you probably thought that the “center-left” magazine paid Foer and Martin Peretz and a slew of other editors (and, one hopes, fact checkers) to keep them honest.  How wrong you are!

As an aside, what’s doubly annoying is that you can read Manzi’s full on misinformation, “Why the Decision to Tackle Climate Change Isn’t as Simple as Al Gore Says,” in full here, but the piece he is nominally debunking, Al Gore’s, “The Crisis Comes Ashore,” from the June 10 TNR is behind their firewall.  You can read extended excerpts of Gore’s accurate piece here.

Manzi’s debunking has already been partly debunked by Time’s Bryan Walsh and TNR’s own Bradford Plumer.

Joseph Lawler at The American Spectator, responding to Romm:

It seems as if it is because of Manzi’s track record of being honest, open, and accommodating that Romm is unable to stand his arguments in a liberal publication without trying to undermine his credibility. It was for that same reason that many conservatives found Manzi’s criticism of Levin so grating — it’s in a way easier to deny global warming altogether than to argue on Manzi’s level. At the time, a number of liberals cast the reaction to Manzi-Levin as a sign that conservatives are close-minded, despite the fact that National Review did publish the piece, after all. But now that the tables have turned and Manzi is writing for TNR, some of the same liberal observers are questioning his motives and accusing him of “lowering the standard of discourse.”

It is to National Review‘s credit that they published Manzi then, it is to TNR‘s credit that they publish him now despite the left-wing outcry, and it is to Manzi’s credit that his soldiers on producing impeccably factual articles only to be derided as dishonest by both the right and left. If only the same could be said of Romm about his willingness to consider reasoned challenges to his assumptions.

(By the way, Romm’s post originally contained a clear factual error: he cited someone who incorrectly claimed that Manzi was the CEO of Lotus (I can’t find a cached version, but it’s noted in a comment left in the morning). Since then Romm has fixed the error, but there is nothing in the post indicating that it has been changed. A meaningless mistake, but suffice it to say that the “misinformer” Manzi would not make a factual error and then fail to acknowledge it in the post.)

Ezra Klein here and here. Klein:

Letting greenhouse gases build in the atmosphere is a bit like letting a tree grow roots beneath the foundation of your house. It may not be that bad this year, or next year, or even the year after that. But with each year that goes by, the problem becomes incrementally more severe, and harder to reverse. So even if Manzi is right that the costs are manageable into 2100 — a century, after all, is a long time for a human, but not for the atmosphere — what does that do to our descendants who have to deal with a scorching planet between 2100 and 2200? And then into 2300, and then 2400?

I think Manzi’s answer is that technology will save us by then. And maybe he’s right. But maybe he’s not. And if he’s not, then we’ve let the problem become unimaginably bad for our descendants. If you bet on technology and you’re wrong, it’s not like we’ve got another of these planets waiting in the back somewhere.

The appropriate technological approach, it seems to me, is to pair a strategy of aggressive emissions reduction with a huge effort to develop technological solutions. Then, if the research begins to pay off, we can transition over to those technologies and ease up on the regulations. But if we don’t so mitigation and instead trust in technology, we may let the situation get so bad that by the time we’re ready to do mitigation, the problem is essentially irreversible.

Manzi responds to Klein:

When thinking about taking actions now to shape the future environment, we should start with the recognition that our ability to make meaningful predictions generally declines as we look further and further into the future. This proceeds in shades of gray from, illustratively, “2030” to “10,000AD.”

At several points in my post I described the projected impacts of climate change through about the year 2100. This is because numerous IPCC forecasts are done through about that point in time, due to the view that projections beyond this point are too speculative.

When thinking about time after 2100, we have, in cartoon terms, two choices: (i) simply treat it as unknowable fog, or (ii) attempt to guess. I think that if we take the first choice, then we simply try to forecast through the next century, and let future generations worry about the world beyond 2100 (though I’ll point out that it is a very unusual political debate in which we call trying to manage the entire world for about the next 100 years as “short-termism”).

If we take the second approach, how far out do we try to guess? The Nordhaus economic calculations that I cited in my post as formal attempts to compare odds-adjusted costs versus benefits actually extend out for 250 years. That is, they consider expected costs and benefits to about 2250. Therefore, Klein’s point is really about potential damages beyond 2250,not 2100. That’s a long way off.

This doesn’t mean that I don’t care about problems that might occur hundreds of years from now, just that I don’t care much about current predictions about those problems.

UPDATE: Bryan Walsh at Time

Matthew Yglesias

UPDATE #2: Jim Manzi has a round-up at The American Scene

2 Comments

Filed under Environment