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Adaptive stochastic search

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  • Aguiar, Victor H.
  • Kimya, Mert

Abstract

We characterize Simon’s (1955) search and satisficing model with an adaptive threshold and random search (SM-AT). The decision maker (DM) consistent with the SM-AT is endowed with a utility function, a random search distribution, and a deterministic but menu-dependent threshold. On any given trial, the DM searches the menu and stops whenever she finds an item with a utility level that is above the threshold. This simple choice procedure accommodates the well-known compromise and attraction effects. The SM-AT is more general than the random utility model and allows for systematic departures from regularity. Its characterization lets us differentiate adaptive satisficing behavior from random preference maximization in a (limited) standard stochastic choice data set.

Suggested Citation

  • Aguiar, Victor H. & Kimya, Mert, 2019. "Adaptive stochastic search," Journal of Mathematical Economics, Elsevier, vol. 81(C), pages 74-83.
    • Handle: RePEc:eee:mateco:v:81:y:2019:i:c:p:74-83
    DOI: 10.1016/j.jmateco.2019.01.003
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    Cited by:

    1. Demirkan, Yusufcan & Kimya, Mert, 2020. "Hazard rate, stochastic choice and consideration sets," Journal of Mathematical Economics, Elsevier, vol. 87(C), pages 142-150.
    2. Yudistira Permana, 2020. "Explaining satisficing through risk aversion," Theory and Decision, Springer, vol. 89(4), pages 503-525, November.
    3. Kovach, Matthew & Ülkü, Levent, 2020. "Satisficing with a variable threshold," Journal of Mathematical Economics, Elsevier, vol. 87(C), pages 67-76.
    4. Kashaev, Nail & Aguiar, Victor H., 2022. "A random attention and utility model," Journal of Economic Theory, Elsevier, vol. 204(C).
    5. Li, Boyao, 2023. "Random utility models with status quo bias," Journal of Mathematical Economics, Elsevier, vol. 105(C).

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