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Implications of quantal response statistical equilibrium

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  • Scharfenaker, Ellis

Abstract

This paper explores the foundations and properties of the quantal response statistical equilibrium (QRSE) model developed by Scharfenaker and Foley (2017). The QRSE model provides a behavioral foundation for the formation of aggregate economic outcomes in social systems characterized by negative feedbacks. It can approximate a wide range of commonly encountered theoretical distributions that have been identified as economic statistical equilibrium and displays qualitatively similar behavior to the Subbotin and Asymmetric Subbotin distributions that range from the Laplace to the Normal distribution in the limit. Asymmetry in the frequency distributions of economic outcomes can be understood as arising from the unfulfilled expectations of entropy-constrained decision makers. This paper demonstrates the logic of the QRSE model in an application to US stock market data dating back to 1926. The model provides a parsimonious explanation for the distribution of rates of return on private equities as well as a behavioral foundation for asset price fluctuations.

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  • Scharfenaker, Ellis, 2020. "Implications of quantal response statistical equilibrium," Journal of Economic Dynamics and Control, Elsevier, vol. 119(C).
    • Handle: RePEc:eee:dyncon:v:119:y:2020:i:c:s0165188920301585
    DOI: 10.1016/j.jedc.2020.103990
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    1. Giorgio Fagiolo & Lucia Alessi & Matteo Barigozzi & Marco Capasso, 2010. "On the distributional properties of household consumption expenditures: the case of Italy," Empirical Economics, Springer, vol. 38(3), pages 717-741, June.
    2. Philipp Mundt & Simone Alfarano & Mishael Milakovic, 2016. "Gibrat’s Law Redux: think profitability instead of growth," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 25(4), pages 549-571.
    3. Filip Matêjka & Alisdair McKay, 2015. "Rational Inattention to Discrete Choices: A New Foundation for the Multinomial Logit Model," American Economic Review, American Economic Association, vol. 105(1), pages 272-298, January.
    4. Milton Friedman, 1957. "Introduction to "A Theory of the Consumption Function"," NBER Chapters, in: A Theory of the Consumption Function, pages 1-6, National Bureau of Economic Research, Inc.
    5. Foley Duncan K., 1994. "A Statistical Equilibrium Theory of Markets," Journal of Economic Theory, Elsevier, vol. 62(2), pages 321-345, April.
    6. Richard Mckelvey & Thomas Palfrey, 1998. "Quantal Response Equilibria for Extensive Form Games," Experimental Economics, Springer;Economic Science Association, vol. 1(1), pages 9-41, June.
    7. Longstaff, Francis A., 1995. "Stochastic Volatility and Option Valuation: A Pricing-Density Approach," University of California at Los Angeles, Anderson Graduate School of Management qt1wg89967, Anderson Graduate School of Management, UCLA.
    8. McKelvey Richard D. & Palfrey Thomas R., 1995. "Quantal Response Equilibria for Normal Form Games," Games and Economic Behavior, Elsevier, vol. 10(1), pages 6-38, July.
    9. Ellis Scharfenaker, Markus P.A. Schneider, 2019. "Labor Market Segmentation and the Distribution of Income: New Evidence from Internal Census Bureau Data," Working Paper Series, Department of Economics, University of Utah 2019_08, University of Utah, Department of Economics.
    10. Giulio Bottazzi & Angelo Secchi, 2011. "A new class of asymmetric exponential power densities with applications to economics and finance," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 20(4), pages 991-1030, August.
    11. Mundt, Philipp & Alfarano, Simone & Milaković, Mishael, 2020. "Exploiting ergodicity in forecasts of corporate profitability," Journal of Economic Dynamics and Control, Elsevier, vol. 111(C).
    12. Ellis Scharfenaker & Gregor Semieniuk, 2017. "A Statistical Equilibrium Approach to the Distribution of Profit Rates," Metroeconomica, Wiley Blackwell, vol. 68(3), pages 465-499, July.
    13. Alfarano, Simone & Milakovic, Mishael, 2008. "Does classical competition explain the statistical features of firm growth?," Economics Letters, Elsevier, vol. 101(3), pages 272-274, December.
    14. Markus P. A. Schneider, 2013. "Evidence for Multiple Labor Market Segments: An Entropic Analysis of US Earned Income, 1996-2007," Journal of Income Distribution, Ad libros publications inc., vol. 22(2), pages 60-98, June.
    15. Shiller, Robert J, 1981. "Do Stock Prices Move Too Much to be Justified by Subsequent Changes in Dividends?," American Economic Review, American Economic Association, vol. 71(3), pages 421-436, June.
    16. Daniel McFadden, 2001. "Economic Choices," American Economic Review, American Economic Association, vol. 91(3), pages 351-378, June.
    17. Giulio Bottazzi & Angelo Secchi, 2006. "Explaining the distribution of firm growth rates," RAND Journal of Economics, RAND Corporation, vol. 37(2), pages 235-256, June.
    18. Daniel L. McFadden, 1976. "Quantal Choice Analysis: A Survey," NBER Chapters, in: Annals of Economic and Social Measurement, Volume 5, number 4, pages 363-390, National Bureau of Economic Research, Inc.
    19. Giulio Bottazzi & Le Li & Angelo Secchi, 2019. "Aggregate fluctuations and the distribution of firm growth rates," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 28(3), pages 635-656.
    20. Ellis Scharfenaker, 2022. "Statistical Equilibrium Methods In Analytical Political Economy," Journal of Economic Surveys, Wiley Blackwell, vol. 36(2), pages 276-309, April.
    21. Mundt, Philipp & Oh, Ilfan, 2019. "Asymmetric competition, risk, and return distribution," BERG Working Paper Series 145, Bamberg University, Bamberg Economic Research Group.
    22. Alfarano, Simone & Milaković, Mishael & Irle, Albrecht & Kauschke, Jonas, 2012. "A statistical equilibrium model of competitive firms," Journal of Economic Dynamics and Control, Elsevier, vol. 36(1), pages 136-149.
    23. Noe Wiener, 2019. "Diversity in Segmention. Patterns of Immigrant Competition in US Labor Markets," Working Papers 1901, New School for Social Research, Department of Economics.
    24. Williams, Michael A. & Baek, Grace & Li, Yiyang & Park, Leslie Y. & Zhao, Wei, 2017. "Global evidence on the distribution of GDP growth rates," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 468(C), pages 750-758.
    25. Mundt, Philipp & Oh, Ilfan, 2019. "Asymmetric competition, risk, and return distribution," Economics Letters, Elsevier, vol. 179(C), pages 29-32.
    26. Herbert A. Simon, 1955. "A Behavioral Model of Rational Choice," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 69(1), pages 99-118.
    27. Paulo L. dos Santos, 2017. "The Principle of Social Scaling," Complexity, Hindawi, vol. 2017, pages 1-9, December.
    28. Paulo L dos Santos & Ellis Scharfenaker, 2019. "Competition, self-organization, and social scaling—accounting for the observed distributions of Tobin’s q," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 28(6), pages 1587-1610.
    29. Caticha, Ariel & Golan, Amos, 2014. "An entropic framework for modeling economies," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 408(C), pages 149-163.
    30. Soofi, E. S. & Retzer, J. J., 2002. "Information indices: unification and applications," Journal of Econometrics, Elsevier, vol. 107(1-2), pages 17-40, March.
    31. Milton Friedman, 1957. "A Theory of the Consumption Function," NBER Books, National Bureau of Economic Research, Inc, number frie57-1, March.
    32. Sims, Christopher A., 2003. "Implications of rational inattention," Journal of Monetary Economics, Elsevier, vol. 50(3), pages 665-690, April.
    33. Duncan K. Foley, 2017. "Information theory and behavior," Working Papers 1731, New School for Social Research, Department of Economics.
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    Cited by:

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    2. Emanuele Citera, 2021. "Stock Returns, Market Trends, and Information Theory: A Statistical Equilibrium Approach," Working Papers 2116, New School for Social Research, Department of Economics.
    3. Ellis Scharfenaker, 2022. "Statistical Equilibrium Methods In Analytical Political Economy," Journal of Economic Surveys, Wiley Blackwell, vol. 36(2), pages 276-309, April.
    4. Jangho Yang, 2023. "Information‐theoretic model of induced technical change: Theory and empirics," Metroeconomica, Wiley Blackwell, vol. 74(1), pages 2-39, February.
    5. Ellis Scharfenaker, Duncan K. Foley, 2021. "Unfulfilled Expectations and Labor Market Interactions: A Statistical Equilibrium Theory of Unemployment," Working Paper Series, Department of Economics, University of Utah 2021_03, University of Utah, Department of Economics.

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    More about this item

    Keywords

    QRSE; Quantal response; Maximum entropy; Statistical equilibrium; Information theory;
    All these keywords.

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • C18 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Methodolical Issues: General
    • C70 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - General
    • D8 - Microeconomics - - Information, Knowledge, and Uncertainty

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