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Fast computation algorithm for the random consideration set model

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  • Lee, Younghwan

Abstract

This paper proposes a fast and reliable computation algorithm for the random consideration set model. A simple and numerically tractable representation of the model is developed to reduce the computational burden. I show that the new algorithm outperforms existing methods in terms of accuracy and speed.

Suggested Citation

  • Lee, Younghwan, 2019. "Fast computation algorithm for the random consideration set model," Economics Letters, Elsevier, vol. 179(C), pages 38-41.
    • Handle: RePEc:eee:ecolet:v:179:y:2019:i:c:p:38-41
    DOI: 10.1016/j.econlet.2019.03.018
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    References listed on IDEAS

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    1. Paola Manzini & Marco Mariotti, 2014. "Stochastic Choice and Consideration Sets," Econometrica, Econometric Society, vol. 82(3), pages 1153-1176, May.
    2. Peter M. Guadagni & John D. C. Little, 1983. "A Logit Model of Brand Choice Calibrated on Scanner Data," Marketing Science, INFORMS, vol. 2(3), pages 203-238.
    3. Berry, Steven & Levinsohn, James & Pakes, Ariel, 1995. "Automobile Prices in Market Equilibrium," Econometrica, Econometric Society, vol. 63(4), pages 841-890, July.
    4. Chiang, Jeongwen & Chib, Siddhartha & Narasimhan, Chakravarthi, 1998. "Markov chain Monte Carlo and models of consideration set and parameter heterogeneity," Journal of Econometrics, Elsevier, vol. 89(1-2), pages 223-248, November.
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    Cited by:

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    2. Matthijs R. Wildenbeest, 2022. "Online News Consumption and Limited Consideration," Working Papers 22-10, NET Institute.

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    More about this item

    Keywords

    Bounded rationality; Discrete choice; Random consideration; Numerical method;
    All these keywords.

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • L1 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance

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