Why Friedman’s methodology has “jumped the shark”
9 February, 2013 at 11:02 | Posted in Economics, Theory of Science & Methodology | 2 Comments
The basic argument of [Milton Friedman’s infamous 1953 essay ‘The Methodology of Positive Economics’] is the unrealism of a theory’s assumptions should not matter; what matters are the predictions made by the theory. A truly realistic economic theory would have to incorporate so many aspects of humanity that it would be impractical or computationally impossible to do so. Hence, we must make simplifications, and cross check the models against the evidence to see if we are close enough to the truth. The internal details of the models, as long as they are consistent, are of little importance.
The essay, or some variant of it, is a fallback for economists when questioned about the assumptions of their models. Even though most economists would not endorse a strong interpretation of Friedman’s essay, I often come across the defence ’it’s just an abstraction, all models are wrong’ if I question, say, perfect competition, utility, or equilibrium. I summarise the arguments against Friedman’s position below.
The first problem with Friedman’s stance is that it requires a rigorous, empirically driven methodology that is willing to abandon theories as soon as they are shown to be inaccurate enough. Is this really possible in economics? …
The second problem with a ‘pure prediction’ approach to modelling is that, at any time, different theories or systems might exhibit the same behaviour, despite different underlying mechanics. That is: two different models might make the same predictions, and Friedman’s methodology has no way of dealing with this …
The third problem is the one I initially honed in on: the vagueness of Friedman’s definition of ‘assumptions,’ and how this compares to those used in science …
The fourth problem is related to above: Friedman is misunderstanding the purpose of science. The task of science is not merely to create a ‘black box’ that gives rise to a set of predictions, but to explain phenomena: how they arise; what role each component of a system fills; how these components interact with each other …
The fifth problem is one that is specific to social sciences, one that I touched on recently: different institutional contexts can mean economies behave differently. Without an understanding of this context, and whether it matches up with the mechanics of our models, we cannot know if the model applies or not. Just because a model has proven useful in one situation or location, it doesn’t guarantee that it will useful elsewhere, as institutional differences might render it obsolete.
The final problem, less general but important, is that certain assumptions can preclude the study of certain areas. If I suggested a model of planetary collision that had one planet, you would rightly reject the model outright. Similarly, in a world with perfect information, the function of many services that rely on knowledge – data entry, lawyers and financial advisors, for example – is nullified …
Friedman’s essay has economists occupying a strange methodological purgatory, where they seem unreceptive to both internal critiques of their theories, and their testable predictions. This follows directly from Friedman’s ambiguous position. My position, on the other hand, is that the use and abuse of assumptions is always something of a judgment call. Part of learning how to develop, inform and reject theories is having an eye for when your model, or another’s, has done the scientific equivalent of jumping the shark.
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The basic argument of [Milton Friedman’s infamous 1953 essay ‘The Methodology of Positive Economics’] is the unrealism of a theory’s assumptions should not matter; what matters are the predictions made by the theory. A truly realistic economic theory would have to incorporate so many aspects of humanity that it would be impractical or computationally impossible to do so. Hence, we must make simplifications, and cross check the models against the evidence to see if we are close enough to the truth. The internal details of the models, as long as they are consistent, are of little importance.



Edward Herman writes: “Friedman’s methodology in attempting to prove his models have set a new standard in opportunism, manipulation, and the abuse of scientific method.”
Edward Herman, Triumph of the Market (Boston: South End Press, 1995), p. 36
Paul Diesing lists six tactics Friedman uses to support a pet hypothesis called “Permanent Income” (or PI). These are:
“1. If raw or adjusted data are consistent with PI, he reports them as confirmation of PI…
2. If the fit with expectations is moderate, he exaggerates the fit…
3. If particular data points or groups differ from the predicted regression, he invents ad hoc explanations for the divergence…
4. If a whole set of data disagree with predictions, adjust them until they do agree…
5. If no plausible adjustment suggests itself, reject the data as unreliable…
6. If data adjustment or rejection are not feasible, express puzzlement. ‘I have not been able to construct any plausible explanation for the discrepancy…’” (4)
Paul Diesing, “Hypothesis Testing and Data Interpretation: The Case of Milton Friedman,” Research in the History of Economic Thought and Methodology, vol. 3, pp. 61-69.
Comment by Jan Milch— 9 February, 2013 #
The UK Forum for Post Keynesian Economics
Keynes Seminar in Cambridge
Richard Kahn on The Scourge of Monetarism (11 December 1987).
http://www.postkeynesian.net/downloads/RFK111287.mp3
Comment by Jan Milch— 10 February, 2013 #