A Random Attention Model

Matias Cattaneo, Xinwei Ma, Yusufcan Masatlioglu and Elchin Suleymanov

Journal of Political Economy, 2020, vol. 128, issue 7, 2796 - 2836

Abstract: This paper illustrates how one can deduce preference from observed choices when attention is both limited and random. We introduce a random attention model where we abstain from any particular attention formation and instead consider a large class of nonparametric random attention rules. Our intuitive condition, monotonic attention, captures the idea that each consideration set competes for the decision maker’s attention. We then develop a revealed preference theory and obtain testable implications. We propose econometric methods for identification, estimation, and inference for the revealed preferences. Finally, we provide a general-purpose software implementation of our estimation and inference results and simulation evidence.

Date: 2020
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Citations: View citations in EconPapers (27)

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Working Paper: A Random Attention Model (2020)
Working Paper: A Random Attention Model (2019)
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