Discrete Actions in Information-constrained Decision Problems
Filip Matejka and
Christopher Sims ()
Emory Economics from Department of Economics, Emory University (Atlanta)
Changes in economic behavior often appear to be delayed and discontinuous, even in contexts where rational behavior seems to imply immediate and continuously distributed reactions to market signals. One possible explanation is the presence of information-processing costs. Individuals are constantly processing external information and translating it into actions. This draws on limited resources of attention and requires economizing on attention devoted to signals related to economic behavior. A natural measure of such costs is based on Shannon's measure of "channel capacity." Introducing information costs based on Shannon's measure into a standard framework of decision-making under uncertainty turns out to imply that discretely distributed actions, and thus actions that persist across repetitions of the same decision problem, are very likely to emerge in settings that without information costs would imply continuously distributed behavior. We show how these results apply to the behavior of a risk-averse monopoly price setter and to an investor choosing portfolio allocations, as well as to some mathematically simpler "tracking" problems that illustrate the mechanism. Interpreting the behavior in our examples ignoring information costs and postulating fixed ("menu") costs of adjustment would lead to mistaken conclusions.
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