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Scalability in a two-class interoccupational earnings distribution model

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  • Maia, Adriano
  • Matsushita, Raul
  • Demarcus, Antonio
  • Da Silva, Sergio

Abstract

In this study, we evaluate a two-class earnings distribution model that combines a power law distribution for higher-earning individuals and a lognormal distribution for the rest of the sample, while considering occupation scalability. We analyze data from the Brazilian labor market and model entire distributions, not just the tails. Our findings suggest that non-scalable occupations may be more egalitarian than scalable ones in the upper portion of the data from the optimal cutoff point.

Suggested Citation

  • Maia, Adriano & Matsushita, Raul & Demarcus, Antonio & Da Silva, Sergio, 2023. "Scalability in a two-class interoccupational earnings distribution model," SocArXiv 23brg, Center for Open Science.
    • Handle: RePEc:osf:socarx:23brg
    DOI: 10.31219/osf.io/23brg
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    References listed on IDEAS

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    1. Maia, Adriano & Matsushita, Raul & Da Silva, Sergio, 2020. "Earnings distributions of scalable vs. non-scalable occupations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 560(C).
    2. Drăgulescu, Adrian & Yakovenko, Victor M., 2001. "Exponential and power-law probability distributions of wealth and income in the United Kingdom and the United States," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 299(1), pages 213-221.
    3. Clementi, F. & Gallegati, M., 2005. "Power law tails in the Italian personal income distribution," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 350(2), pages 427-438.
    4. Xavier Gabaix, 2016. "Power Laws in Economics: An Introduction," Journal of Economic Perspectives, American Economic Association, vol. 30(1), pages 185-206, Winter.
    5. repec:cup:cbooks:9781107013445 is not listed on IDEAS
    6. Victor M. Yakovenko & J. Barkley Rosser, 2009. "Colloquium: Statistical mechanics of money, wealth, and income," Papers 0905.1518, arXiv.org, revised Dec 2009.
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