Rational Inattention and Sequential Information Sampling

70 Pages Posted: 11 Sep 2017 Last revised: 1 Jul 2023

See all articles by Benjamin Hebert

Benjamin Hebert

Stanford University

Michael Woodford

Columbia University, Graduate School of Arts and Sciences, Department of Economics

Date Written: September 2017

Abstract

We propose a new principle for measuring the cost of information structures in rational inattention problems, based on the cost of generating the information used to make a decision through a dynamic evidence accumulation process. We introduce a continuous-time model of sequential information sampling, and show that, in a broad class of cases, the choice frequencies resulting from optimal information accumulation are the same as those implied by a static rational inattention problem with a particular static information-cost function. Among the static cost functions that can be justified in this way is the mutual information cost function proposed by Sims (2010), but we show that other cost functions can be micro-founded in this way as well. In particular, we introduce a class of “neighborhood-based” cost functions, which make it more costly to undertake experiments that can produce different results in similar states, and show that the predictions of this alternative rational inattention theory better conform with evidence from perceptual discrimination experiments.

Suggested Citation

Hebert, Benjamin M. and Woodford, Michael, Rational Inattention and Sequential Information Sampling (September 2017). NBER Working Paper No. w23787, Available at SSRN: https://ssrn.com/abstract=3035135

Benjamin M. Hebert (Contact Author)

Stanford University ( email )

Stanford, CA 94305
United States

Michael Woodford

Columbia University, Graduate School of Arts and Sciences, Department of Economics ( email )

420 W. 118th Street
New York, NY 10027
United States

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