Bayesian Networks and Boundedly Rational Expectations

Ran Spiegler ()

No 10062, CEPR Discussion Papers from Centre for Economic Policy Research

Abstract: I present a framework for analyzing decision makers with an imperfect understanding of their environment's correlation structure. The decision maker faces an objective multivariate probability distribution (his own action is one of the random variables). He is characterized by a directed acyclic graph over the set of variables. His subjective belief filters the objective distribution through his graph, via the factorization formula for Bayesian networks. This belief distortion implies that the decision maker's long-run behavior may affect his perception of the consequences of his actions. Accordingly, I define a "personal equilibrium" notion of optimal choices. I show how recent models of boundedly rational expectations (as well as new ones, e.g. reverse causality) can be subsumed into this framework as special cases. Some general properties of the Bayesian-network representation of subjective beliefs are presented, as well as a "missing data" foundation.

Keywords: Bayesian networks; Boundedly rational expectations; Coarse reasoning; Directed acyclic graphs; Misspecified models; Personal equilibrium; Reverse causality (search for similar items in EconPapers)
JEL-codes: D03 (search for similar items in EconPapers)
Date: 2014-07
New Economics Papers: this item is included in nep-hpe, nep-mic and nep-upt
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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Related works:
Journal Article: Bayesian Networks and Boundedly Rational Expectations (2016)
Working Paper: Bayesian Networks and Boundedly Rational Expectations (2014)
Working Paper: Bayesian networks and boundedly rational expectations (2014)
Working Paper: Bayesian Networks and Boundedly Rational Expectations
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