Implications of Academic Dishonesty

There has been a recent flap over the appearance online of a video of Jonathan Gruber telling the truth about the Obamacare bill:

This bill was written in a tortured way to make sure CBO did not score the mandate as taxes. If [Congressional Budget Office] scored the mandate as taxes, the bill dies. Okay, so it’s written to do that. In terms of risk-rated subsidies, if you had a law which said that healthy people are going to pay in -– you made explicit that healthy people pay in and sick people get money — it would not have passed… Lack of transparency is a huge political advantage. And basically, call it the stupidity of the American voter, or whatever, but basically that was really, really critical for the thing to pass. And it’s the second-best argument. Look, I wish Mark was right that we could make it all transparent, but I’d rather have this law than not.

What he is saying, pretty clearly, is that he wishes one could both be honest and get good legislation passed but approves of dishonesty if necessary to get the job done. 

My guess is that his view is shared not only by most politicians but by most academics involved in the political system, although I expect many would be unwilling to say so, especially on camera. Part of the reason I believe that is an experience that happened almost fifty years ago. I was spending a summer in Washington as a congressional intern. My congressman lent me for four days a week to the Joint Economic Committee. They lent me to the Project on State and Local Finance of George Washington University, aka the Project on State and Local Finance of the JEC, aka the Project on State and Local Finance of the Governors' Conference. The Project was producing a fact book, a volume to provide the ordinary voter with information on state and local finance. 

I discovered a fact. It was a demographic fact about people already born. It was a fact about future financial requirements for the largest expenditure in state and local budgets. The people running the project refused to include the fact in their factbook, not because they thought it was not true or not important but because it pointed in the wrong direction. Knowing it would make voters less willing to support increases in state and local revenues, which was the opposite of the result they wanted.

The fact itself is one you can easily check. The date was about 1967. For the previous fifteen or so years, as the baby boom came into the school system, the ratio of students to taxpayers had been going up, which meant that taxes for schools had to increase in order to keep per pupil spending from falling. For the next decade or two, as the baby boom came out of the schools and into the labor force, the ratio of students to taxpayers would be going down. That meant that per pupil spending could be kept at its current level while taxes for schools went down. Schooling was and is the largest expenditure of state and local governments.

I had assumed that professional academics, people I liked and respected, were committed to honesty in their professional work. I think of the discovery that they were not as my loss of innocence.

My gut reaction is to disapprove both of what the people I worked with then did—pretending to inform people while deliberately misinforming them—and what Gruber describes and approves of, but I cannot prove that my reaction is justified. Gruber's position is that he is willing to sacrifice one value for another that he thinks more important, and I cannot show that he is wrong. I can, however, point out a danger in the approach. Once academics accept the principle that dishonesty is justified if done for the greater good, their work cannot be trusted on any subject with regard to which they have an incentive to misrepresent it. I offered an example in one of my previous posts.

Consider the relevance for the current climate controversy. No single academic knows enough to base his conclusion solely on his own work and expertise. Each of them is relying on information produced by many others. The economists estimating the net effect of AGW rely on the work of climate scientists predicting the effects on temperature of increased CO2, the work of other climate scientists predicting the effect of increased temperature on rainfall, hurricanes, and other relevant variables, the work of agronomists estimating the effect of changes in CO2 concentration, length of growing season, temperature on agricultural production, the work of statisticians confirming the models of the climate scientists on the basis of their analysis of paleoclimate data, and many others.

What happens if each of those experts feels entitled, even obligated, to lie just a little, to shade his conclusions to strengthen the support they provide for what he believes is the right conclusion? Each of them then interprets the work of all the others as providing more support for that conclusion than it really does. The result might be that they end up biasing their results in support of the wrong conclusion—which each of them believes is right on the basis of the lies of all the others.

That is one of the reasons I am not greatly impressed by the supposed scientific consensus in favor of Catastrophic Anthropogenic Global Warming.

There is a quote usually attributed to Bismarck but apparently due to Saxe:

Laws, like sausages, cease to inspire respect in proportion as we know how they are made.

Science too. At least when it intersects politics.

Me vs Mankiw on Global Warming

A commenter on a old post of mine about global warming points at a response by Greg Mankiw. Both are from 2007. The issues have not changed since then and, while I responded to Mankiw at length by email, I do not think I ever did so publicly.

Mankiw supports a carbon tax. I argued that while a carbon tax might make sense as the answer to the question "what is the best policy for dealing with negative externalities due to global warming," it did not make sense as the answer to the question "what policy should economists support to deal with global warming" since there was no good reason to believe that, if a carbon tax was implemented, it would take the form economists would recommend. Interested readers should probably read both my post and Mankiw's before going on to my response below, which I have copied from my email correspondence with him.

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It seems to me that you are making the error that was the norm in textbooks and the profession fifty years ago, before public choice theory. You are evaluating proposals for government policy on the basis of what they could do if optimally implemented not on what one can expect them to do given the incentives of the people making the decisions—what used to be referred to as the philosopher king model of government. It makes no more sense than evaluating the market alternative on the assumption that all the decision makers in that case will act to maximize social welfare rather than in their own interest. The question is not whether an optimal carbon tax designed and enforced by wise and benevolent economists would produce net benefits—very likely it would. It's whether passing a carbon tax designed and implemented as we can best expect it to be would produce net benefits.

Two further points with regard to your original blog post:

1. I wasn't making a slippery slope argument. If I had been, I would have argued that carbon taxes would initially be a good thing but would set the precedent for other bad things. In fact I argued that, as implemented, they would probably be a bad thing. As I made explicit in my post, it was a public choice argument—completely ignored in your response. I plan to send in my complaints to the Society for the Protection of Straw Men just as soon as I can find their email address.

2. My argument is  consistent with my father's views. For evidence, take a look at the discussion of professional licensing in Capitalism and Freedom. The argument is not that professional licensing, applied by wise and benevolent officials, could do no good. It is that we can expect, on grounds of both theory and evidence, that professional licensing will usually be controlled by the profession and used to restrict entry and raise prices.

If you look again at the quote from him you link to, he isn't saying that one should recommend policies independent of how one thinks they will be implemented—consider the "in light of what can be done." Professional licensing that isn't captured can't be done, or at least not reliably done, on the evidence. He is saying that one shouldn't refrain from making a proposal merely because you think it can't be passed.

In this context, the implication is that one might argue that a specified form of carbon tax would be a good thing and simultaneously that any carbon tax that could be passed would be a bad thing. I don't believe that is your position.

And, again:

Can you see any hint of evidence that the people proposing cap and trade have made any effort to estimate marginal cost of reduction of carbon dioxide, optimal level of emission, or any of the information necessary for a scheme designed to actually produce net benefits?

Isn't that question relevant to how one can expect a carbon tax (or cap and trade) to be implemented, and isn't that relevant to whether one ought to be in favor of it?

Evaluating Controversial Claims

Someone makes a scientific claim, typically as an argument for some policy. Examples would be current claims with regard to global warming, claims fifty years ago about the consequences of population growth, claims early in the Obama administration about the need for large deficits to bring down unemployment. There are at least four different ways in which an interested observer can decide whether or not to believe the claim.

1. Partisanship. If you support the policy, believe the claim. If you don't, don't. This is probably the most common approach.

2. Evaluate the arguments for yourself. This is  the most entertaining and educational approach but no more reliable than the first—and likely to give the same answer. There is always controversy about the claim among people better equipped to evaluate it than the random observer, although one side or both may try to deny it. In the case of global warming, the relevant claim is not merely that temperatures are going up, or that the reason is human activity, or that they can be expected to go up by enough to cause serious net costs, but all of those plus the additional claim that there are ways of reducing the increase that are worth their cost. To evaluate all of that you need a reasonably expert knowledge of climatology, statistics, ecology, economics, and probably two or three other fields I have not thought of. Since you don't have all that, you end up believing whichever arguments you want to believe.

3. The argument from authority. You try to figure out what the consensus of the people who are experts is or what some authoritative source of information says. An outsider trying to figure out what professionals in a field believe is at risk of overvaluing whatever position has the most support from public sources of information, such as the mass media, or has done the best job of getting its supporters onto the committees of scientific organizations that put out public statements. And even if he could figure it out for one field, that isn't sufficient. Again taking the global warming case, it is not enough to know what the consensus of the climatologists is, even if you can separate the facts from the puffery on that subject. Climatologists are not economists, so  could be correct about the expected temperature increase and wrong about the magnitude or even the sign of its consequences. Economists are not ecologists, so might show the costs they are looking at to be insignificant while missing the effects of climate change on other species. I discussed problems with this approach at greater length in an earlier post.

4. Prediction. Once such a controversy has been going for a while, partisans have a track record. If they have made confident predictions that turned out to be wrong, that is good evidence that they are either dishonest or arguing from an incorrect theory. Figuring out whether the arguments for a theory are right or wrong is much harder than finding out what that theory predicted. Sometimes all the latter takes is  a book or article by its supporters written a few years back.

The clearest case is the population hysteria of the 1960's. Paul Ehrlich's Population Bomb, published in 1968, confidently predicted mass famine in the third world over the next decade, with hundreds of millions of people starving to death. Not only did it not happen, the real world moved in the opposite direction, with calorie consumption per capita in the third world going up, not down. That is very strong evidence that Ehrlich can not be trusted. It is somewhat weaker evidence that the movement of which he was part, whose members generally took him and his arguments seriously, can not be trusted.

Weaker examples apply to my other two cases. Early in Obama's first term, the Administration offered predictions of what the unemployment rate would be without a stimulus and how much lower it would be with the stimulus that the Administration wanted and got. Actual unemployment rates for the next several years were higher with the stimulus than predicted without it. That does not tell us whether the stimulus was a good policy. It is possible, as its supporters argued after the fact, that things were simply worse than they thought. But it is good evidence that predictions made by Administration economists can not be trusted, that either they were deliberately fudging the results or were using models much less reliable than they claimed.

For the case of global warming, we have the IPCC's repeated overpredictions of global temperatures, hurricane rates that are strikingly lower, not strikingly higher, this year than the average, and a number of other predictions to which the real world has failed to conform. Again, that does not show that the underlying argument is wrong. It does show that the people and models that have been generating the mistaken predictions cannot be trusted.

Which is about the most that the interested outside observer can hope to learn.

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P.S. Not surprisingly, a lot of the comments on this post focus on the particular case of global warming rather than the general argument. One commenter provides a link to an article by Chris Landsea on the effect of global warming on the frequency and strength of hurricanes. One conclusion is that global warming by the end of the century might result in a slight increase in the strength of hurricanes and might also result in a substantial decrease in their frequency. 

Another is that the historical record provides no support for the claim that hurricanes have been becoming more frequent or stronger over the past century or so. The reasons that hurricane damage has trended up is that the total value of property in coastal counties has increased. The reason that the number of recorded hurricanes has trended up is probably the large improvement in our ability to detect hurricanes, in particular ones that fail to make land. For details see the article.

When Costs Aren't

From the standpoint of an economist, the logic of global warming is  straightforward. There are costs to letting it happen, there are costs to preventing it, and by comparing the two we decide what, if anything, ought to be done. I am fairly sure, however, that  many of those who are sure we should be doing something about it do not see the question that way. What I see as costs, they see as benefits.

Reduced energy use is a cost if you approve of other people being able to do what they want, which includes choosing to live in the suburbs, drive cars instead of taking mass transit, heat or air condition their homes to what they find a comfortable temperature. But it is a benefit if you believe that you know better than other people how they should best live their lives—know that a European style inner city with a dense population, local stores, local jobs, mass transit instead of private cars, is a better, more human, lifestyle than living in the anonymous suburbs, commuting to work, knowing few of your neighbors. It is an attitude that I associate with an old song about little houses made of ticky-tacky—meaning houses the singer didn't like and was therefore confident that other people shouldn't be living in, occupied by people whose life style she thought she knew and was confident she disapproved of. A very arrogant, and very human, attitude.

There are least three obvious candidates for reducing global warming that do not require a reduction in energy use. One is nuclear power—a well established, if somewhat expensive, technology that produces no CO2 and can be expanded more or less without limit. One is natural gas, which produces considerably less carbon dioxide per unit of power than coal, for which it is the obvious substitute. Fracking has now sharply lowered the price of natural gas, with the result that U.S. output of CO2 has actually fallen. The third and more speculative candidate is geoengineering—one or another of several approaches that have been suggested for cooling earth without reducing CO2 output.

One would expect that someone seriously worried about global warming would take an interest in all three alternatives. Of course, in each case, there are arguments against as well as arguments for. But if one believes that global warming is a very serious problem and alternative solutions are costly, one ought to be biased in favor of each of them, inclined to look for arguments for, not arguments against.

In my experience, that is not how people who campaign against global warming act. They are less likely than others, not more, to support nuclear power, to approve of fracking as a way of producing lots of cheap natural gas, or to be in favor of experiments to see whether one or another version of geoengineering will work. That makes little sense if they see a reduction in power consumption as a cost, but quite a lot of sense if they see it as a benefit.

I have focused on global warming, but the pattern exists in other contexts and across the political spectrum. When 9/11 happened, a lot of the people who insisted that the threat of terrorism now made it unfortunately necessary to restrict individual privacy and civil liberties in a variety of ways were people who were in favor of the same policies before 9/11.

The general approach is perhaps best summed up in a quote attributed to Rahm Emanuel, back when he was working for Obama: 

 You never let a serious crisis go to waste. And what I mean by that it's an opportunity to do things you think you could not do before.

The argument for sharply increasing federal spending and doing it with borrowed money was that it was an emergency measure made necessary by the economic crisis. For Emanuel, and presumably his boss, it was an opportunity to do things they would have wanted to do whether or not there was a crisis. The argument for using regulation or carbon taxes to reduce the output of carbon dioxide is that it is made necessary by the threat of global warming. For many of those who make that argument, it is an opportunity to make other people live the way those people think they should.

Physics, Economics, and Hurricane Arguments

I just finished an interview, via Skype, that will eventually be up on the web. One question I was asked was how knowledge of one field feeds into thinking about another. It occurred to me that I had an interesting example, a case where two unrelated fields, both of which I have worked in, showed that two different arguments for a conclusion in a third field were both wrong.

The three fields are physics, economics, and climate science. The conclusion, widely repeated, is that global warming will result in either more frequent or more violent hurricanes, or both. The conclusion may, for all I know, be correct. Two common arguments for it, however, are both wrong.

The first argument is that hurricanes get their energy from heat, so can be expected to be more violent or more frequent if there is more heat to feed them. That sounds plausible—provided you don't know the relevant physics. A hurricane is a heat engine, converting thermal energy to mechanical energy in the form of moving air. A heat engine does not, indeed cannot, simply convert thermal energy to work—one that did that and nothing else, say a ship that ran without fuel on the heat of the ocean, would be what is called a perpetual motion machine of the second kind and is impossible because it violates the second law of thermodynamics.

A heat engine works by taking heat from a high temperature source, turning some of it into work, and dumping the rest into a lower temperature sink. The amount of work it can get out depends not simply on the temperature of the source but on the temperature difference (if my memory from long ago studies is correct, actually the difference in 1/T) between source and sink. So if you warm both source and sink, air and sea in the case of a hurricane, there is no particular reason to expect that more work will be available, hence no particular reason to expect hurricanes to get either more frequent or more violent.

The second argument is empirical. It is claimed—I presume correctly—that on average you get more hurricanes in hot weather. The obvious conclusion is that if earth's climate gets warmer, we will have more (or more powerful) hurricanes. This time it is economics, in particular the history of ideas in economics, that points out the mistake.

Quite a long time ago, William Phillips, an economist from New Zealand, noticed an interesting empirical relation—on average, when inflation was high, unemployment was low. The relation got labeled the "Phillips Curve." The obvious conclusion was that one could hold down unemployment at the cost of tolerating some inflation. A variety of governments tried to implement such policies. Their failure in the U.S. got labeled "stagflation," a situation with both high unemployment and high inflation.

What was wrong with the Phillips Curve was not the empirical evidence but the causal conclusion. What was really going on, as the evidence is now widely interpreted, was that unemployment tended to be low when inflation was higher than people expected. That makes sense on a fairly simple model. If workers underestimate inflation, they will see wage offers as more attractive than they really are and so be more willing to accept them, less willing to wait for a better job, than they would be if they correctly estimated future inflation. If employers underestimate inflation, they will observe high demand for their products at current prices and see that as a reason to hire more workers and expand production.

Times when inflation is high are also, on average, times when it is higher than people expect, giving you the empirical relation Phillips had observed. But if a government tries to exploit the relation by maintaining an inflation rate of (say) five percent a year, after a while people adjust their expectations accordingly and the unemployment rate goes back up. Raise it to ten percent, unemployment falls briefly, people adjust their expectations, and unemployment goes back up again.

The same argument applies in the case of temperature and hurricanes. On average, times when air temperature are higher than normal are also times when the temperature difference between air and sea is larger than normal—the sea, after all, has enormous heat capacity, and so tends to average out short term fluctuations in air temperature. So the observation that hurricanes are more likely in hot weather does not imply that they would be more likely if both sea and air got warmer, as, in a global warming scenario, they do. 

None of this implies that global warming does not make hurricanes more frequent or more violent. I have seen empirical claims in both directions—both that hurricanes are and are not increasing—and do not know enough about the field to evaluate them. But it does mean that two apparently persuasive arguments for why we should expect such a relation are wrong. 

And in each case, I spotted the error because of my background in a different, in one case entirely unrelated, field.