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A Random Attention Model

Author

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  • Cattaneo, Matias D
  • Ma, Xinwei
  • Masatlioglu, Yusufcan
  • Suleymanov, Elchin

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.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Cattaneo, Matias D & Ma, Xinwei & Masatlioglu, Yusufcan & Suleymanov, Elchin, 2020. "A Random Attention Model," University of California at San Diego, Economics Working Paper Series qt34m788c3, Department of Economics, UC San Diego.
    • Handle: RePEc:cdl:ucsdec:qt34m788c3
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    Other versions of this item:

    • Matias D. Cattaneo & Xinwei Ma & Yusufcan Masatlioglu & Elchin Suleymanov, 2017. "A Random Attention Model," Papers 1712.03448, arXiv.org, revised Aug 2019.

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