Who’s the Real Economist?

From: Paul Krugman To: James K. Galbraith

       I am grateful to James Galbraith for two things: the relative civility of his letter, and the link to his article on doing economics. That way we need not throw quotations at each other–readers can go look at his piece and see if I have gotten the spirit of it right.
       When you try to talk about the importance of a mathematical sensibility in doing economics, there are two misunderstandings that you must immediately confront. The first is that the math must be fancy–that I must be talking about pages and pages full of squiggles. The second is the charge that if you think that algebra is important, you must believe that everything about the world can be deduced from equations, and be uninterested in checking your equations against reality.
       What I actually have in mind is something much more prosaic. Economics is at least partly about quantities and their relationships; so you can’t make sense of it unless you are willing to do some arithmetic and even some algebra to make sure that the stories you tell hang together–and that they are consistent with the evidence. This doesn’t sound like much, but experience shows that there are many influential intellectuals who are prepared to make sweeping pronouncements on economics without doing the arithmetic. And by the way, throwing around lots of statistics is not the point: It’s a question of thinking hard about how the statistics fit together.
       Maybe the only way to explain what I am talking about is to give an example. It involves Michael Lind of The New Yorker, against whom I have no particular grudge–in fact, part of the point is that he is, undoubtedly, a very smart guy. That is what makes this particular example so revealing: It shows what happens when someone who is very bright but does not understand the role of arithmetic in economic analysis tries to make pronouncements on the subject.
       Two years ago, Lind wrote the following in Harper’s:


Many advocates of free trade claim that higher productivity growth in the United States will offset any downward pressure on wages caused by the global sweatshop economy, but the appealing theory falls victim to an unpleasant fact. Productivity has been going up, without resulting wage gains for American workers. Between 1977 and 1992, the average productivity of American workers increased by more than 30 percent, while the average real wage fell by 13 percent. The logic is inescapable. No matter how much productivity increases, wages will fall if there is an abundance of workers competing for a scarcity of jobs–an abundance of the sort created by the globalization of the labor pool for U.S.-based corporations.

       Now what should Lind have done before publishing this passage? He should have had an internal monologue–something like this: “Hmm, do these numbers make sense? Well, historically, compensation of workers has been around 70 percent of national income. So let’s say that initially, output per worker is 100, and the wage is 70. Now if productivity is up 30 percent, that means that output is 130, while if wages are down 13 percent, that brings the wage down to around 61, which is less than half of 130–wow, that means that the share of labor in national income must have fallen more than 20 percentage points. Let me check that out in the Statistical Abstract. …” Of course, if he had, he would have found out that the share of compensation in national income, far from declining 20 percentage points, was about the same (73 percent) in 1992 as it was in 1977, offering a clear warning bell that something was wrong not only with his numbers–for example, he turns out to have confused productivity in manufacturing with productivity in the economy as a whole–but with his story. (This was not a throwaway passage marginal to his main argument; the claim that globalization has shifted the distribution of income drastically in favor of capital was central to his article.)
       How could Lind have failed to go through this little monologue? Well, I have had several conversations with impressive, highly articulate men, who believe themselves sophisticated about economic matters, but who simply do not understand that if productivity is up and wages are down, this must mean that labor’s share in income has fallen. These conversations are not pleasant: They want to discuss deep global issues, and end up being given a lesson in elementary arithmetic. But that is precisely the point: All too many people think that they can do economics by learning some impressive phrases and reciting some gee-whiz statistics, and do not realize that you need to think algebraically about how the story fits together.
       Presumably, Galbraith will say that this example has nothing to do with him and his friends. But consider the concept of “deindustrialization,” which has been a centerpiece of much economic writing over the past 15 years–in fact, it could be considered Bob Kuttner’s signature contribution to the field. The story is that wages in the United States have stagnated or declined largely because trade deficits have eliminated high-paying jobs in manufacturing. There is nothing wrong with this story, in theory–in fact, it is a perfectly good example of what is known as the “domestic distortions” argument for harm from international trade, which is covered in many undergraduate textbooks on the subject, mine included. But if you do even a rough back-of-the-envelope calculation–a little more complicated than the one Michael Lind should have done, but still very simple–and check it against the data, you immediately realize that the displacement of high-wage manufacturing jobs by imports cannot have pushed average wages down by more than a fraction of a percentage point. The point is that the deindustrializers have a good story, but lack the instinctive urge they should have had to see if that story actually adds up.
       I have no doubt that Galbraith can do linear algebra, probably better than I can. That is not the point, because we are not talking about fancy math. In fact, there is a familiar tendency of some basically anti-mathematical intellectuals to reserve a small pedestal for people who do very complicated math that seems to refute orthodoxy–like the correspondent who told Steven Pinker, the author of The Language Instinct, that “[w]e don’t need natural selection, because now we have chaos theory,” or the one who assured me that global savings don’t have to equal global investment, because the world is nonlinear. (I call this tendency the “Santa Fe syndrome.”) I suspect that this perverse affection for confusing math owes less to any expectation that it will clarify matters than to a sense that it absolves us from the need to understand simpler models.
       Finally, notice how utterly false is the charge that people like me believe that the world can be predicted and understood entirely by a priori reasoning. On the contrary, both Lind and Kuttner have, whether they know it or not, been making arguments that are straight out of standard undergraduate textbooks on international trade–Chapters 4 and 10, respectively, of mine. I don’t start from the position that what they are saying cannot be true in the light of orthodox theory–it could be, but I have looked at the evidence, and it isn’t. But that is a quantitative, arithmetic assessment–which is why they didn’t notice that problem for themselves.