Rational Inattention and Sequential Information Sampling

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.

Discrete Choice and Rational Inattention: A General Equivalence Result

“…In this section we show that κ S (p (·) , µ) does indeed possess two reasonable and desirable properties of cost functions that have been discussed in the existing literature (cf. de Oliveira, Denti, Mihm, Ozbek (2015), Hébert and Woodford (2016)), thus providing normative support for the GERI framework.…”

Visual attention modulates the integration of goal-relevant evidence and not value

“…Attention is thought to play a central role, prioritising and enhancing which information is accessed during the decisionmaking process. How attention interacts with value-based choice has been investigated in psychology and neuroscience [1,2,3,4,5,6,7,8,9,10,11] and this question is at the core of the theory of rational inattention in economics [12,13,14,15].…”

Travel time variability and rational inattention

“…It is a standard result in the rational inattention literature (Hébert and Woodford, 2016) that it is wasteful to obtain a signal that is more informative than the action, and we may therefore simplify, at no loss of generality, by identifying the signal with the random action. Our rationally inattentive traveler will then, effectively, be choosing the conditional distribution Pr(A = a|T = t).…”