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Earnings distributions of scalable vs. non-scalable occupations

Author

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

Abstract

It has been suggested that occupations where one is paid by the hour are not scalable, while scalable occupations allow one to make more money without an equivalent increase in labor and time. Non-scalable occupations are expected to have low income variance, whereas scalable ones show large income inequalities. This study examines the evidence for this suggested categorizing using personal earnings microdata for twelve candidate occupations of both types, scalable and not. We find the upper tails of all distributions decay as power laws. Moreover, we cannot reject the suggested categorizing for earnings above medians.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:phsmap:v:560:y:2020:i:c:s037843712030621x
    DOI: 10.1016/j.physa.2020.125192
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    Cited by:

    1. Petra Štamfestová & Lukáš Sobíšek & Jiří Hnilica, 2023. "Firm Size Distribution in the Central European Context," Central European Business Review, Prague University of Economics and Business, vol. 2023(5), pages 151-175.
    2. 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.

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