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Optimal Categorization

Author

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  • Mohlin, Erik

    (Dept. of Economics, Stockholm School of Economics)

Abstract

The importance of categorical reasoning in human cognition is well-established in psychology and cognitive science, and it is generally acknowledged that one of the most important functions of categorization is to facilitate prediction. This paper provides a model of optimal categorization. In the beginning of each period a subject observes a two-dimensional object in one dimension and wants to predict the object's value in the other dimension. The subject partitions the space of objects into categories. She has a data base of objects that were observed in both dimensions in the past. The subject determines what category the new object belongs to on the basis of observation of its first dimension. The average value in the second dimension, of objects in this category in the data base, is used as prediction for the object at hand. At the end of each period the second dimension is observed and the observation is stored in the data base. The main result is that the optimal number of categories is determined by a trade-off between (a) decreasing the size of categories in order to enhance category homogeneity, and (b) increasing the size of categories in order to enhance category sample size.

Suggested Citation

  • Mohlin, Erik, 2009. "Optimal Categorization," SSE/EFI Working Paper Series in Economics and Finance 721, Stockholm School of Economics, revised 30 May 2014.
    • Handle: RePEc:hhs:hastef:0721
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Chollete, Loran & Schmeidler, David, 2014. "Demand-Theoretic Approach to Choice of Priors," UiS Working Papers in Economics and Finance 2014/14, University of Stavanger.
    2. Daskalova, Vessela & Vriend, Nicolaas J., 2021. "Learning frames," Journal of Economic Behavior & Organization, Elsevier, vol. 191(C), pages 78-96.
    3. Bleile, Jörg, 2016. "Categorization based Belief formations," Center for Mathematical Economics Working Papers 519, Center for Mathematical Economics, Bielefeld University.
    4. Natalia Shestakova, 2010. "Pricing Scheme Choice: How Process Affects Outcome," CERGE-EI Working Papers wp411, The Center for Economic Research and Graduate Education - Economics Institute, Prague.
    5. Topi Miettinen, 2012. "Paying attention to payoffs in analogy-based learning," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 50(1), pages 193-222, May.
    6. Yuval Heller & Eyal Winter, 2016. "Rule Rationality," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 57(3), pages 997-1026, August.
    7. Halpern, Joe & Heller, Yuval & Winter, Eyal, 2022. "The Benefits of Coarse Preferences," MPRA Paper 111670, University Library of Munich, Germany.
    8. Daskalova, Vessela & Vriend, Nicolaas J., 2020. "Categorization and coordination," European Economic Review, Elsevier, vol. 129(C).
    9. Ellingsen, Tore & Mohlin, Erik, 2019. "Decency," Working Papers 2019:3, Lund University, Department of Economics.
    10. Ennio Bilancini & Leonardo Boncinelli, 2014. "Persuasion with Reference Cues and Elaboration Costs," Center for Economic Research (RECent) 102, University of Modena and Reggio E., Dept. of Economics "Marco Biagi".
    11. Jehiel, Philippe & Mohlin, Erik, 2021. "Cycling and Categorical Learning in Decentralized Adverse Selection Economies," Working Papers 2021:11, Lund University, Department of Economics.
    12. Daskalova, Vessela & Vriend, Nicolaas J., 2020. "Categorization and coordination," European Economic Review, Elsevier, vol. 129(C).
    13. Bilancini, Ennio & Boncinelli, Leonardo, 2018. "Rational attitude change by reference cues when information elaboration requires effort," Journal of Economic Psychology, Elsevier, vol. 65(C), pages 90-107.
    14. Philippe Jehiel & Erik Mohlin, 2023. "Categorization in Games: A Bias-Variance Perspective," Working Papers halshs-04154272, HAL.
    15. Mengel, Friederike & Sciubba, Emanuela, 2014. "Extrapolation and structural similarity in games," Economics Letters, Elsevier, vol. 125(3), pages 381-385.
    16. Yasar, Alperen, 2023. "Power struggles and gender discrimination in the workplace," SocArXiv t4g83, Center for Open Science.
    17. Mohlin, Erik & Östling, Robert & Wang, Joseph Tao-yi, 2020. "Learning by similarity-weighted imitation in winner-takes-all games," Games and Economic Behavior, Elsevier, vol. 120(C), pages 225-245.
    18. Simon Gleyze & Philippe Jehiel, 2023. "Expectation Formation, Local Sampling and Belief Traps: A new Perspective on Education Choices," Working Papers halshs-04154324, HAL.

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    More about this item

    Keywords

    Categorization; Priors; Prediction; Similarity-Based Reasoning.;
    All these keywords.

    JEL classification:

    • C72 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Noncooperative Games

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