Is Economics a Science?

The 2022 Nobel prize in economics will be announced tomorrow, Monday, October 10. Of course, it is not a “real” Nobel prize but rather the “Sveriges Riksbank Prize in Economic Sciences in Memory of Alfred Nobel” but I will use the conventional phrase “Nobel prize in economics.”

The official name does raise an interesting question. Why does it say “Sciences”? There is a Nobel prize in Physics, not in “Physical Sciences”. Same with Chemistry. Perhaps it was considered preposterous to presume that people thought Economics was a science, so they decided to cover up that problem by using the plural “Sciences”.

I am writing this before the 2022 announcement to avoid giving the impression that I am commenting on the 2022 winner(s). Sometimes the decisions are obviously great ones. Arrow and Samuelson were deservedly among the first recipients. Some recent winners were also obvious. Both Bob Wilson and Leonid Hurwicz were strong Nobel Prize candidates when I was an economics graduate student 43 years ago. Both awards were long overdue, and Hurwicz’s prize came so late in his life that he was not able to properly celebrate.

No one will be surprised that I applaud those awards. Arrow and Samuelson were leaders in developing mathematical economics, Hurwicz is listed as a mathematician and an economist on his Wikipedia page (he had no degree in economics), and Wilson’s PhD was in Applied Math at Harvard. They used their mathematical skills to formulate and analyze important problems in economics.

Many Nobel recipients, such as Schelling, did not use advanced math in their work, and I have no problem with that. In fact, math is not necessary for expressing great ideas in economics. Unfortunately, those great ideas often have different implications for real world issues. Finding out which ideas are of greatest importance often requires mathematical models and tools.

My criticisms of economics as a science fall into two categories: the common practice of using a thin veneer of math to disguise greatly flawed analyses, and the failure to follow standard rules of scientific communication.

My blog posts have highlighted a few examples of flawed math leading to flawed economics as well as the hostility to doing the math correctly. Barro’s analysis of optimal tax and debt policy is invalid for any economically relevant case. Krusell-Kuruscu-Smith misleads readers about the mathematical soundness of its “solution” method. They are both examples of Clarida’s preference for models that are “simple — but solvable!” Has this bad math hurt economics? Chari begins with an obvious observation: one reason for the 2008 economic problems were that the simple models used at that time were not able to capture the complexity of real economies. However, he goes on to say that the focus on simplicity is “essential given scarce computational resources, not to mention the limits of the human mind in absorbing detail!”, a comment that ignored the considerable amount of computing power and expertise that was available in 2010. The real problem is the hostility to the application of modern mathematical and computational tools. Piazessi declared that JPE did not want papers written for “smart people” and Clarida dismisses the idea of helping either Columbia grad students or Federal Reserve research economists learn how to apply modern computational tools to complex macroeconomic problems.

I am not talking only about potential, but can point to examples of what can be done. My paper on the social cost of carbon social cost of carbon is just one example of what is possible. A recent paper analyzes issues in debt and taxation without resorting to the simple and invalid approaches of Barro (1979) and Sargent’s 2002 JPE paper. These are just a couple of the many examples of the potential of computational modeling for economics.

In all of my activity as a referee or an editor, I judged a paper by its content and how it compared to the literature. The AEA argues for “an environment where all can freely participate and where each idea is considered on its own merits.” However, Jim Heckman declared that if I were to criticize a colleague’s methodological demands, he would reject my paper he was handling at the JPE, even though it contained no such criticism. This was a gag order that covered anything I said in any forum or document.

These incidents are not the isolated actions of a few unimportant economists. Heckman has a Nobel prize and Krusell often helps decide who gets Nobel prizes. When I told JPE editors and University of Chicago officials about Heckman’s gag order, the response was that it was not a violation of the free speech principles advocated by the University of Chicago. Those same people approved my release of all the documents related to that matter, telling everyone that they are confident that Heckman’s gag order will be universally deemed as an appropriate use of his power as a journal editor.

Many people have had similar experiences in dealing with economists. When I tell people about my problems with the economics elite, many say that “everyone” knows that economics lacks rigor and is corrupt, and that I am wasting my time discussing these issues. However, I am not sure that this is “common knowledge.” Game theorists love to teach the tale of “Forty Unfaithful Wives” told by Gamow and Stern in their book Puzzle-Math; see a computer science presentation for a modern exposition. It is a great example of the difference between everyone knowing a fact and it being common knowledge. My efforts aim to create common knowledge regarding issues in economics.

I have nothing new to add to the discussion of whether economics is a science. My only point is that parts of economics want to look like science without embracing the rigor and free exchange of ideas that is usually expected of a science. These problems can be fixed if economists want to fix them.

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