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Income distribution and income shares: wealth and income distributions explained using generalised Lotka-Volterra SFC ABM models

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  • Geoff Willis

Abstract

This paper combines a classical approach to economics with standard finance theory in a Lotka-Volterra framework. The models are agent-based, general Lotka-Volterra (GLV) models, using very simple homogeneous or heterogeneous agents. The agents are owners of capital, they receive wages and returns on their capital, and spend a portion of their wealth on consumption. As such the models use realistic economic variables. The models give simple outputs of 'log-normal'-like bodies and power tail distributions for both wealth and income. These distributions match those seen in real economies. The models are unique in giving real world distributions from a statistical mechanical model that uses absolutely identical agents. The models demonstrate that wealth and income inequality is driven by the economic force of concentration of capital through a statistical-mechanical wealth condensation process. The models also show a direct relationship between the macroeconomic labour share of income and the distributions of personal wealth and income. In addition, the models give a proposed 'compulsory saving' regime that appears highly effective for the reduction of poverty.

Suggested Citation

  • Geoff Willis, 2015. "Income distribution and income shares: wealth and income distributions explained using generalised Lotka-Volterra SFC ABM models," International Review of Applied Economics, Taylor & Francis Journals, vol. 29(6), pages 816-842, November.
  • Handle: RePEc:taf:irapec:v:29:y:2015:i:6:p:816-842
    DOI: 10.1080/02692171.2015.1065225
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    References listed on IDEAS

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    1. Ripsy Bandourian & Robert Turley & James McDonald, 2002. "A Comparison of Parametric Models of Income Distribution across Countries and over Time," LIS Working papers 305, LIS Cross-National Data Center in Luxembourg.
    2. A.B. Atkinson & F. Bourguignon (ed.), 2000. "Handbook of Income Distribution," Handbook of Income Distribution, Elsevier, edition 1, volume 1, number 1.
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    Cited by:

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    2. Emiliano Brancaccio & Mauro Gallegati & Raffaele Giammetti, 2022. "Neoclassical influences in agent‐based literature: A systematic review," Journal of Economic Surveys, Wiley Blackwell, vol. 36(2), pages 350-385, April.
    3. Hajamini, Mehdi, 2020. "Analyzing the Causal Relationships between Economic Growth, Income Inequality, and Transmission Channels: New Empirical Evidences from Iran," Journal of Money and Economy, Monetary and Banking Research Institute, Central Bank of the Islamic Republic of Iran, vol. 15(3), pages 313-342, July.

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