Bayesian learning and expectations formation: Anything goes - Max Albert (Universität Konstanz, Fakultät für Wirtschaftswissenschaften und Statistik, 1996)
The paper proves that the Bayesian approach to learning and expectations formation implies no propositions that could conceivably be refuted by observation. For a (non-expanding) universe infinite in time but finite at any point of time, it is shown that by a suitable choice of priors, any betting strategy can be rationalized. Consequently, no sequence of future choices can be excluded on the basis of a decision maker's v. Neumann-Morgenstern utility function, her knowledge of past observations, and the assumption of Bayesian rationality. Since no betting strategy is irrational, Bayesianism is useless as a normative theory as well.
Keywords: B41; C11; D81; D83; D84; 330; Bayesianism; Bayesian learning; decision theory; expectations; learning; rational expectations; rationality; rationalizability; subjectively expected utility theory; subjective probability