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How To Win Acceptance Of The Inequality Process As Economics?

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  • Angle, John

Abstract

The Inequality Process (IP) is a particle system model similar to that of the Kinetic Theory of Gases. The IP is a parsimonious model of competition among people for wealth. The IP explains a wide scope of stable patterns in the distribution of personal income and wealth. Econophysicists have adopted the IP as part of their field, but the IP has been ignored or rejected by economists even though economists claim expertise on the distribution of personal income and wealth. The academic discipline of statistics in the U.S. claims expertise on data analysis. Yet from the mid-20th century on advances in computationally intensive algorithms for data analysis were developed largely outside of the discipline of statistics. Not until experts on this new paradigm of data analysis diverted resources away from traditional, old paradigm statisticians, was the new paradigm widely accepted in the discipline of statistics, even though a few statisticians had contributed to computationally intensive data analysis all along. This paper’s thesis is that the IP will follow a path into economics similar to that taken by computationally intensive data analysis into statistics, once useful applications of the IP are found and experts on the IP divert resources away from economists. That day is not at hand. There are no applications of the IP to business or government at present. One conceivable application of the IP to market research, small area estimation of personal income distribution, is suggested.

Suggested Citation

  • Angle, John, 2013. "How To Win Acceptance Of The Inequality Process As Economics?," MPRA Paper 52887, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:52887
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    References listed on IDEAS

    as
    1. John Angle, 2007. "The Macro Model of the Inequality Process and The Surging Relative Frequency of Large Wage Incomes," Papers 0705.3430, arXiv.org.
    2. Angle, John, 2006. "The Inequality Process as a wealth maximizing process," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 367(C), pages 388-414.
    3. Salem, A B Z & Mount, T D, 1974. "A Convenient Descriptive Model of Income Distribution: The Gamma Density," Econometrica, Econometric Society, vol. 42(6), pages 1115-1127, November.
    4. Angle, John & Nielsen, Francois & Scalas, Enrico, 2009. "The Kuznets Curve and the Inequality Process," MPRA Paper 16058, University Library of Munich, Germany, revised 29 Jun 2009.
    5. Kirk Hamilton & Gang Liu, 2013. "Human Capital, Tangible Wealth, and the Intangible Capital Residual," OECD Statistics Working Papers 2013/2, OECD Publishing.
    6. Gallegati, Mauro & Keen, Steve & Lux, Thomas & Ormerod, Paul, 2006. "Worrying trends in econophysics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 370(1), pages 1-6.
    7. Adrian Dragulescu & Victor M. Yakovenko, 2000. "Statistical mechanics of money," Papers cond-mat/0001432, arXiv.org, revised Aug 2000.
    8. Hamilton, Kirk & Liu, Gang, 2013. "Human capital, tangible wealth, and the intangible capital residual," Policy Research Working Paper Series 6391, The World Bank.
    9. 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.
    10. Levy, Frank & Murnane, Richard J, 1992. "U.S. Earnings Levels and Earnings Inequality: A Review of Recent Trends and Proposed Explanations," Journal of Economic Literature, American Economic Association, vol. 30(3), pages 1333-1381, September.
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    More about this item

    Keywords

    economics; econophysics; income distribution; inequality; market research; paradigm; particle system; scientific revolutions; small area estimation;
    All these keywords.

    JEL classification:

    • B5 - Schools of Economic Thought and Methodology - - Current Heterodox Approaches
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • D31 - Microeconomics - - Distribution - - - Personal Income and Wealth Distribution

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