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Roman Frydman: Modeling a World of Imperfect Knowledge

From the INET blog by Elham Saeidinezhad:

Does it matter if the Rational Expectations Hypothesis is unrealistic?


Not according to New York University Prof. Roman Frydman, head of the Institute for New Economic Thinking’s research group on Imperfect Knowledge Economics (IKE).


Speaking at a seminar organized by the Institute and Columbia University and chaired by Columbia Prof. Joseph Stiglitz, who’s a member of the Institute’s advisory board, Frydman stated that the Rational Expectations Hypothesis, or REH, is simply an abstraction of reality and therefore it is misleading to criticize it for abstracting from many significant aspects of the real world economy. To Frydman, instead, the more pressing questions raised by REH are, what kind of world is it an abstraction of? And can this explain why the models fail so dramatically?


Frydman’s point is that the kind of the world that REH models are abstracting actually does not exist. A REH model assumes that people need to make decisions on how the economy works and the problem that they face is how to forecast when there are so many ways to do so. The relevant economic models, according to John Muth (1961), could serve this purpose. But the current version of REH modeling is empirically non-testable, which creates significant controversy.


Having said that, there also is no proof that other versions of REH models can work.  Although we do not know if the model empirically works, we can determine in which “domain” the model works. This basically means that we have to investigate the following question: How does change proceed in REH models over time?  As Popper (1957) argues, “If there is such a thing as “growing human knowledge,” we cannot anticipate today what we shall know tomorrow.”


Frydman is focusing his work on understanding “imperfect knowledge” to find a solution for the REH’s irrelevance in representing rational decision-making in the real world economy. Frydman and his co-author, Michael D. Goldberg, also argue that they can empirically test this model by formulizing market understanding. Rational forecasting, therefore, needs to be related to the markets’ understanding of the price process. Market understanding is indeed the function of some causal factors. Therefore, one could formulize the market understanding of the price changes in order to empirically test the model. 


The domain that one could choose for the models is macroeconomics or the financial market. By choosing a specific domain we are actually making assumptions about the different processes of change. Mathematically speaking, choosing the domain keeps the model open to an unobserved change.



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