Antoine Reverchon — The Dogmas of the Market Economy under Critical Scrutiny

About Beyond Mechanical Markets: Asset Price Swings, Risk, and the Role of the State by Roman Frydman and Michael D. Goldberg and what the authors call "imperfect knowledge economics."

INET Blog
The Dogmas of the Market Economy under Critical Scrutiny
Antoine Reverchon (translated from French), Le Monde

PDF of the epilogue here.

From the epilogue:

Keynes ... shared Knight’s profound doubts concerning the usefulness of standard probability theory for understanding change in individual decisionmaking and market outcomes: we “cannot depend on strict mathematical expectation, since the basis for making such calculations does not exist” .... The importance that Keynes attached to the role of uncertainty concerning both outcomes and probabilities played a key role in his analysis of financial markets and their influence on the broader economy, particularly investment.

But

Hayek’s admonition was directed at the post- (1945) Keynesian econometric models, which grew out of the purported formalization of Keynes’s ideas and were estimated by statistical methods on the basis of historical data. Around the time of Hayek’s Nobel lecture, the applicability of these models for policy analysis had come under severe criticism, either for portraying market participants’ forecasting behavior with mechanical rules, which did not take into account contemplated changes in policy, or for disregarding such behavior’s eff ects on aggregate outcomes altogether.

While unnamed, the most prominent author of "the post- (1945) Keynesian econometric models" was Paul Samuelson, who integrated some Keynesian principles with neoclassical general equilibrium.

Hayek fared no better.

Rational Expectations models, which were becoming highly influential at the time, were proposed by their advocates as a way to remedy this fl aw in Keynesian econometric models. But the Rational Expectations models were as mechanical as their Keynesian predecessors.

Because their portrayal of individuals' forecasting behavior is woefully inadequate, Rational Expectations models were unsuitable for analyzing how market participants would respond to the contemplated changes in economic policy. Remarkably (given that they were developed by Hayek's successors at the University of Chicago), these models were, moreover, fully predetermined, and thus perpetuated "the pretense of exact knowledge" that Hayek criticized so scathingly in his Nobel lecture.

Behavioral economics, often credited with overturning this did nothing of the sort, since it carried over previous assumptions.

Faith that better fully predetermined models hold the key to
adequately predicting all future changes and their consequences is
puzzling not only with respect to adherents of the Rational Expectations Hypothesis. When behavioral economists, who uncovered
many important empirical failures of Rational Expectations models,
formalized their insights, they followed their conventional predecessors by doing so with fully predetermined models

The authors then outline their approach as qualitative and contingent.

Imperfect Knowledge Economics stakes out an intermediate position between erratic animal spirits and the contemporary presumption that change and its consequences can be adequately prespecifi ed with mechanical rules. In contrast to the contemporary approach, the mathematical models of Imperfect Knowledge Economics explore the possibility that change and its consequences can be portrayed with qualitative and contingent conditions. h ese conditions are context-dependent, and as discussed in Chapter 9, the qualitative regularities that they formalize become manifest—or cease to be relevant—at moments that no one can fully predict.

Imperfect Knowledge Economics therefore does not adopt the extreme view, often associated with Knight, that uncertainty is so radical as to preclude economists from saying anything useful and empirically relevant about how market outcomes unfold over time. Indeed, departing from the position of Knight and Keynes, we make nonstandard use of probabilistic formalism.

This approach facilitates the formalization of qualitative conditions that make up Imperfect Knowledge Economics models and the mathematical derivation of their qualitative and contingent implications. However, Imperfect Knowledge Economics recognizes the importance of early modern arguments that market participants (and economists) have access to only imperfect knowledge of the causal factors that may be useful for understanding outcomes.