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The particle system model of income and wealth more likely to imply an analogue of thermodynamics in social science

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  • Angle, John

Abstract

The Inequality Process (IP) and the Saved Wealth Model (SW) are particle system models of income distribution. The IP’s social science meta-theory requires its stationary distribution to fit the distribution of labor income conditioned on education. The Saved Wealth Model (SW) is an ad hoc modification of the particle system model of the Kinetic Theory of Gases (KTG). The KTG implies the laws of gas thermodynamics. The IP is a particle system similar to the SW and KTG, but less closely related to the KTG than the SW. This paper shows that the IP passes the key empirical test required of it by its social science meta-theory better than the SW. The IP’s advantage increases as the U.S. labor force becomes more educated. The IP is the more likely of the two particle systems to underlie an analogue of gas thermodynamics in social science as the KTG underlies gas thermodynamics.

Suggested Citation

  • Angle, John, 2011. "The particle system model of income and wealth more likely to imply an analogue of thermodynamics in social science," MPRA Paper 28864, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:28864
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    References listed on IDEAS

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    1. Adrian Dragulescu & Victor M. Yakovenko, 2000. "Statistical mechanics of money," Papers cond-mat/0001432, arXiv.org, revised Aug 2000.
    2. Scalas, Enrico & Gallegati, Mauro & Guerci, Eric & Mas, David & Tedeschi, Alessandra, 2006. "Growth and allocation of resources in economics: The agent-based approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 370(1), pages 86-90.
    3. Anirban Chakraborti & Bikas K. Chakrabarti, 2000. "Statistical mechanics of money: How saving propensity affects its distribution," Papers cond-mat/0004256, arXiv.org, revised Jun 2000.
    4. Chatterjee, Arnab & K. Chakrabarti, Bikas & Manna, S.S, 2004. "Pareto law in a kinetic model of market with random saving propensity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 335(1), pages 155-163.
    5. Arnab Chatterjee & Bikas K. Chakrabarti & S. S. Manna, 2003. "Pareto Law in a Kinetic Model of Market with Random Saving Propensity," Papers cond-mat/0301289, arXiv.org, revised Jan 2004.
    6. S. Ispolatov & P.L. Krapivsky & S. Redner, 1998. "Wealth distributions in asset exchange models," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 2(2), pages 267-276, March.
    7. A. Chakraborti & B.K. Chakrabarti, 2000. "Statistical mechanics of money: how saving propensity affects its distribution," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 17(1), pages 167-170, September.
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    More about this item

    Keywords

    Inequality Process; Kinetic Theory of Gases; labor income distribution; particle system; Saved Wealth Model; social science analogue of thermodynamics;
    All these keywords.

    JEL classification:

    • D03 - Microeconomics - - General - - - Behavioral Microeconomics: Underlying Principles
    • D31 - Microeconomics - - Distribution - - - Personal Income and Wealth Distribution
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General

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