Measuring and Modeling Attention

Andrew Caplin ()
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Andrew Caplin: Department of Economics, New York University, New York, NY 10003

Annual Review of Economics, 2016, vol. 8, issue 1, 379-403

Abstract: This article presents a selective review of economic research on attentional choice, taking an observation of Block & Marschak (1960) as its starting point. Because standard choice data conflate utilities and perception, they point out that it is inadequate for research in which attention is endogenous. The review focuses on their thesis that advances in our understanding of attention require modeling of novel choice-based data sets, and corresponding methods of measurement. By way of example, recent attentional research based on measuring and modeling state-dependent stochastic choice data is detailed. Next research steps in relation to strategic attention and the dynamics of learning are outlined. If the thesis of Block & Marschak is valid, engineering of new data sets will become an increasingly essential professional activity as attentional research advances.

Keywords: revealed preference; rational inattention; Bayesian updating; behavioral economics; imperfect information; costly information processing (search for similar items in EconPapers)
JEL-codes: D8 (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (48)

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