Working Paper Series
Lessons from Learning to Have Rational Expectations
Abstract: This paper reviews a growing literature investigating how
economic agents may learn rational expectations. Fully rational learning
requires implausible initial information assumptions, therefore some form
of bounded rationality has come into focus. Such learning models often
converge to rational expectations equilibria within certain bounds.
Convergence analysis has been much simplified by methods from adaptive
control theory. Learning stability as a correspondence principle show some
promise in common macro models. A new selection problem arises since
differences in initial information and learning methods give rise to many
different equilibria, making economic modelling sensitive to assumptions on
information and information processing.
Keywords: Rational learning; bounded rationality; selection problems; information; (follow links to similar papers)
JEL-Codes: D83; (follow links to similar papers)
49 pages, December 1989
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