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Physical Laws and Human Behavior: A Three-Tier Framework

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Abstract

Social sciences start by looking at the social-psychological attributes of humans to model and explain their observed behavior. However, we suggest starting the study of observed human behavior with the universal laws of physics, e.g., the principle of minimum action. In our proposed three-tier framework, behavior is a manifestation of action driven by physical, biological, and social-psychological principles at the core, intermediate, and top tier, respectively. More broadly, this reordering is an initial step towards building a platform for reorganizing the research methods used for theorizing and modeling behavior. This perspective outlines and illustrates how a physical law can account for observed human behavior and sketches the elements of a broader agenda.

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  • Shabnam Mousavi & Shyam Sunder, 2019. "Physical Laws and Human Behavior: A Three-Tier Framework," Cowles Foundation Discussion Papers 2173, Cowles Foundation for Research in Economics, Yale University.
  • Handle: RePEc:cwl:cwldpp:2173
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    File URL: https://cowles.yale.edu/sites/default/files/files/pub/d21/d2173.pdf
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    1. Karni Edi & Valenzuela-Stookey Quitzé & Vierø Marie-Louise, 2021. "Reverse Bayesianism: A Generalization," The B.E. Journal of Theoretical Economics, De Gruyter, vol. 21(2), pages 557-569, June.
    2. Gode, Dhananjay K & Sunder, Shyam, 1993. "Allocative Efficiency of Markets with Zero-Intelligence Traders: Market as a Partial Substitute for Individual Rationality," Journal of Political Economy, University of Chicago Press, vol. 101(1), pages 119-137, February.
    3. Smith,Vernon L., 2009. "Rationality in Economics," Cambridge Books, Cambridge University Press, number 9780521133388.
    4. Edi Karni & Marie-Louise Vier?, 2013. ""Reverse Bayesianism": A Choice-Based Theory of Growing Awareness," American Economic Review, American Economic Association, vol. 103(7), pages 2790-2810, December.
    5. Friedman, Daniel & Isaac, R. Mark & James, Duncan & Sunder, Shyam, 2014. "Risky Curves: On the Empirical Failure of Expected Utility," Santa Cruz Department of Economics, Working Paper Series qt87v8k86z, Department of Economics, UC Santa Cruz.
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    Cited by:

    1. Shabnam Mousavi & Shyam Sunder, 2020. "Physics and decisions: an inverted perspective," Mind & Society: Cognitive Studies in Economics and Social Sciences, Springer;Fondazione Rosselli, vol. 19(2), pages 293-298, November.

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    More about this item

    Keywords

    Human behavior; Physics; Biology; Social sciences;
    All these keywords.

    JEL classification:

    • B30 - Schools of Economic Thought and Methodology - - History of Economic Thought: Individuals - - - General
    • B40 - Schools of Economic Thought and Methodology - - Economic Methodology - - - General
    • D01 - Microeconomics - - General - - - Microeconomic Behavior: Underlying Principles

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