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Models Make Economics A Science

Summary:
In the Journal of Economic Literature, Ariel Rubinstein discusses Dani Rodrik’s “superb” book “Economics Rules.” The article nicely articulates what economics and specifically, economic modeling is about. Some quotes (emphasis my own) … … on the nature of economics: [A] quote … by John Maynard Keynes to Roy Harrod in 1938: “It seems to me that economics is a branch of logic, a way of thinking”; “Economics is a science of thinking in terms of models joined to the art of choosing models which are relevant to the contemporary world.” [Rodrik] … declares: “Models make economics a science” … He rejects … the … common justification given by economists for calling economics a science: “It’s a science because we work with the scientific method: we build hypotheses and then test them. When a theory fails the test, we discard it and either replace it or come up with an improved version.” Dani’s response: “This is a nice story, but it bears little relationship to what economists do in practice …” … on models, forecasts, and tests: A good model is, for me, a good story about an interaction between human beings … A story is not a tool for making predictions. At best, it can help us realize that a particular outcome is possible or that some element might be critical in obtaining a particular result. … Personally, I don’t have any urge to predict anything.

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In the Journal of Economic Literature, Ariel Rubinstein discusses Dani Rodrik’s “superb” book “Economics Rules.” The article nicely articulates what economics and specifically, economic modeling is about. Some quotes (emphasis my own) …

… on the nature of economics:

[A] quote … by John Maynard Keynes to Roy Harrod in 1938: “It seems to me that economics is a branch of logic, a way of thinking”; “Economics is a science of thinking in terms of models joined to the art of choosing models which are relevant to the contemporary world.”

[Rodrik] … declares: “Models make economics a science” … He rejects … the … common justification given by economists for calling economics a science: “It’s a science because we work with the scientific method: we build hypotheses and then test them. When a theory fails the test, we discard it and either replace it or come up with an improved version.” Dani’s response: “This is a nice story, but it bears little relationship to what economists do in practice …”

… on models, forecasts, and tests:

A good model is, for me, a good story about an interaction between human beings …

A story is not a tool for making predictions. At best, it can help us realize that a particular outcome is possible or that some element might be critical in obtaining a particular result. … Personally, I don’t have any urge to predict anything. I dread the moment (which will hopefully never arrive) when academics, and therefore also governments and corporations, will be able to predict human behavior with any accuracy.

A story is not meant to be “useful” in the sense that most people use the word. I view economics as useful in the sense that Chekhov’s stories are useful—it inspires new ideas and clarifies situations and concepts. … [Rodrik] is aware … “Mischief occurs when economists begin to treat a model as the model. Then the narrative takes on a life of its own and becomes dislodged from the setting that produced it. It turns into an all-purpose explanation that obscures alternative, and potentially more useful, story lines”.

A story is not testable. But when we read a story, we ask ourselves whether it has any connection to reality. In doing so, we are essentially trying to assess whether the basic scenario of the story is a reasonable one, rather than whether the end of the story rings true. … Similarly, … testing an economic model should be focused on its assumptions, rather than its predictions. On this point, I am in agreement with Economics Rules: “. . . what matters to the empirical relevance of a model is the realism of its critical assumptions”.

… on facts:

The big “problem” with interpreting data collected from experiments, whether in the field or in the lab, is that the researchers themselves are subject to the profession’s incentive system. The standard statistical tests capture some aspects of randomness in the results, but not the uncertainty regarding such things as the purity of the experiment, the procedure used to collect the data, the reliability of the researchers, and the differences in how the experiment was perceived between the researcher and the subjects. These problems, whether they are the result of intentional sleight of hand or the natural tendency of researchers to ignore inconvenient data, make me somewhat skeptical about “economic facts.”

Dirk Niepelt
Dirk Niepelt is Director of the Study Center Gerzensee and Professor at the University of Bern. A research fellow at the Centre for Economic Policy Research (CEPR, London), CESifo (Munich) research network member and member of the macroeconomic committee of the Verein für Socialpolitik, he served on the board of the Swiss Society of Economics and Statistics and was an invited professor at the University of Lausanne as well as a visiting professor at the Institute for International Economic Studies (IIES) at Stockholm University.

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