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Econometrica Vol. 57 No. 4 1989

Learning Rational Expectations Under Computability Constraints

Stephen E. Spear

Abstract

In this paper, the author considers how boundedly rational agents learn rational expectations when all equilibrium price functions or forecasts of future equilibrium prices are required to be computable. The paper examines two learning environments. In the first, agents have perfect information about the state of nature. In this case, the theory of machine inference can be applied to show that there is a broad class of computable economies whose rational expectations equilibria can be learned by inductive inference. In the second environment, agents do not have perfect information about the state of nature. In this case, a version of Godel's incompleteness theorem implies that rational expectations equilibria cannot be learned.

DOI
10.2307/1913776
Volume
57
Issue
4
Pages
889
Sources
bibtex:phds-export.bib crossref openalex

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