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A Random Attention Model

Author

Listed:
  • Matias D. Cattaneo
  • Xinwei Ma
  • Yusufcan Masatlioglu
  • Elchin Suleymanov

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.

Suggested Citation

  • Matias D. Cattaneo & Xinwei Ma & Yusufcan Masatlioglu & Elchin Suleymanov, 2020. "A Random Attention Model," Journal of Political Economy, University of Chicago Press, vol. 128(7), pages 2796-2836.
    • Handle: RePEc:ucp:jpolec:doi:10.1086/706861
    DOI: 10.1086/706861
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