Spiegler, R; (2016) Bayesian Networks and Boundedly Rational Expectations. The Quarterly Journal of Economics , 131 (3) pp. 1243-1290. 10.1093/qje/qjw011.

Preview

Text BN.pdf - Accepted Version Download (327kB) | Preview

Abstract

I present a framework for analyzing decision making under imperfect understanding of correlation structures and causal relations. A decision maker (DM) faces an objective long-run probability distribution p over several variables (including the action taken by previous DMs). The DM is characterized by a subjective causal model, represented by a directed acyclic graph over the set of variable labels. The DM attempts to fit this model to p, resulting in a subjective belief that distorts p by factorizing it according to the graph via the standard Bayesian network formula. As a result of this belief distortion, the DM’s evaluation of actions can vary with their long-run frequencies. Accordingly, I define a "personal equilibrium" notion of individual behavior. The framework enables simple graphical representations of causal-attribution errors (such as coarseness or reverse causation), and provides tools for checking rationality properties of the DM's behavior. I demonstrate the framework’s scope of applications with examples covering diverse areas, from demand for education to public policy.

Download activity - last month

Export as JSONXMLCSV

Download activity - last 12 months

Export as JSONXMLCSV

Downloads by country - last 12 months

Export as JSONXMLCSV

Archive Staff Only

View Item