Rational Expectations: a Fallacious Foundation for Studying Crucial Decision Making Processes

Abstract

Proponents of the rational expectations hypothesis (hereafter REH) claim they have developed a general theory of how expectations are formed. To assure that these rational expectations generate efficient, unbiased forecasts which do not display any persistent errors when compared to the actual outcome over time, REH theorists assume that information exists and is available for processing by all decision makers. This information, consisting primarily of quantitative time series data, it is assumed, is a finite realization of a stochastic process; from this data the probability distribution of actual outcomes today and for all future dates can be estimated. Or as John Muth puts it, ‘the hypothesis can be rephrased a little more precisely as follows: that expectations of firms (or more generally, the “subjective” probability of outcomes) tend to be distributed, for the same information set, about the prediction of the theory (or the “objective” probability distribution of outcomes)’ (1961, p. 316).

Journal of Post Keynesian Economics, 5 (2) (Winter) 1982–3. The author is grateful to E. Roy Weintraub, G. L. S. Shackle, Basil J. Moore, Jan Kregel, Don Katzner, Victoria Chick and John Blatt for many helpful comments.