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Accounting For Income Inequality And Its Change: A New Method, With Application To The Distribution Of Earnings In The United States

In: Worker Well-Being and Public Policy

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  • Gary S. Fields

Abstract

This paper devises a new method for using the information contained in income-generating equations to “account for” or “decompose” the level of income inequality in a country and its change over time. In the levels decomposition, the shares attributed to each explanatory factor are independent of the particular inequality measure used. In the change decomposition, methods are presented to break down the contribution of each explanatory factor into a coefficients effect, a correlation effect, and a standard deviation effect. In an application to rising earnings inequality in the United States, it is found that schooling is the single most explanatory variable, only one other variable (occupation) has any appreciable role to play, and all of schooling’s effect was a coefficients effect.

Suggested Citation

  • Gary S. Fields, 2003. "Accounting For Income Inequality And Its Change: A New Method, With Application To The Distribution Of Earnings In The United States," Research in Labor Economics, in: Worker Well-Being and Public Policy, pages 1-38, Emerald Group Publishing Limited.
    • Handle: RePEc:eme:rleczz:s0147-9121(03)22001-x
    DOI: 10.1016/S0147-9121(03)22001-X
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    Cited by:

    1. David S. Jacks & Dennis Novy, 2020. "Trade Blocs and Trade Wars during the Interwar Period," Asian Economic Policy Review, Japan Center for Economic Research, vol. 15(1), pages 119-136, January.
    2. Thi Thu Thuy Tran & Kazunari Tsuji & Miho Fujimura, 2024. "Understanding Household Income Inequality in Rural Vietnam: A Regression-Based Decomposition Study," Sustainability, MDPI, vol. 16(20), pages 1-14, October.
    3. Emilio Padilla Rosa & Evans Jadotte, 2023. "The determinants of the inequality in CO2 emissions per capita between developing countries and their implications for environmental policy," Sustainable Development, John Wiley & Sons, Ltd., vol. 31(1), pages 151-169, February.
    4. Lorenzo Caliendo & Robert C. Feenstra & John Romalis & Alan M. Taylor, 2023. "Tariff Reductions, Heterogeneous Firms, and Welfare: Theory and Evidence for 1990–2010," IMF Economic Review, Palgrave Macmillan;International Monetary Fund, vol. 71(4), pages 817-851, December.
    5. Dawkins, Casey J., 2023. "The geography of US homeownership tax expenditures," Journal of Housing Economics, Elsevier, vol. 59(PA).
    6. Kashour, Mohammad, 2023. "A step towards a just transition in the EU: Conclusions of a regression-based energy inequality decomposition," Energy Policy, Elsevier, vol. 183(C).
    7. Schettino, Francesco & Scicchitano, Sergio & Suppa, Domenico, 2024. "COVID 19 and Wage Polarization: A task based approach," GLO Discussion Paper Series 1398, Global Labor Organization (GLO).
    8. Rohde, Nicholas & Trivedi, Pravin & Tang, K.K. & Rao, Prasada, 2023. "Cognitive and non-cognitive traits and the intergenerational transmission of socioeconomic inequality," Journal of Economic Psychology, Elsevier, vol. 97(C).
    9. Xu Zhang & Xian Yang & Jianping Li & Jun Hao, 2023. "Contemporaneous and noncontemporaneous idiosyncratic risk spillovers in commodity futures markets: A novel network topology approach," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(6), pages 705-733, June.
    10. Bengtsson, Erik & Molinder, Jakob, 2024. "Incomes and income inequality in Stockholm, 1870–1970: Evidence from micro data," Explorations in Economic History, Elsevier, vol. 92(C).
    11. Linden, Jules & O’Donoghue, Cathal & Sologon, Denisa M., 2024. "The many faces of carbon tax regressivity—Why carbon taxes are not always regressive for the same reason," Energy Policy, Elsevier, vol. 192(C).

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