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Metropolitan Earnings Inequality: Union and Government‐Sector Employment Effects

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  • Thomas W. Volscho
  • Andrew S. Fullerton

Abstract

Objective. This study examines the effects of union density and government‐sector employment on earnings inequality in Metropolitan Statistical Areas (MSAs) in the United States. Methods. Data on 167 MSAs from the 2000 Census are analyzed using standard regression techniques. Four measures of Atkinson's index (e=0.5, 1.0, 2.0, 3.0) are used as the measure of earnings inequality for full‐time, year‐round workers. Results. MSAs with greater union density and greater government‐sector employment have lower earnings inequality. The progressive effect of union density is strongest for earners in the middle of the distribution and less beneficial for workers at the bottom of the distribution. Government employment is generally associated with lower levels of earnings inequality, but state and federal government employment have the strongest effects. Conclusion. Even in the late 1990s, unions and government‐sector employment remain effective at reducing earnings inequality.

Suggested Citation

  • Thomas W. Volscho & Andrew S. Fullerton, 2005. "Metropolitan Earnings Inequality: Union and Government‐Sector Employment Effects," Social Science Quarterly, Southwestern Social Science Association, vol. 86(s1), pages 1324-1337, December.
    • Handle: RePEc:bla:socsci:v:86:y:2005:i:s1:p:1324-1337
    DOI: 10.1111/j.0038-4941.2005.00348.x
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    References listed on IDEAS

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    1. Christopher H. Wheeler, 2007. "Industry localisation and earnings inequality: Evidence from U.S. manufacturing," Papers in Regional Science, Wiley Blackwell, vol. 86(1), pages 77-100, March.
    2. Janice F. Madden, 2000. "Changes in Income Inequality within U.S. Metropolitan Areas," Books from Upjohn Press, W.E. Upjohn Institute for Employment Research, number cii, November.
    3. repec:eee:labchp:v:2:y:1986:i:c:p:1139-1181 is not listed on IDEAS
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    Cited by:

    1. Allen Hyde, 2018. "“Left behind?” Financialization and Income Inequality Between the Affluent, Middle Class, and the Poor," LIS Working papers 745, LIS Cross-National Data Center in Luxembourg.
    2. Neil Lee & Andrés Rodríguez-Pose, 2013. "Innovation and spatial inequality in Europe and USA," Journal of Economic Geography, Oxford University Press, vol. 13(1), pages 1-22, January.
    3. Patricia Beeson & Lara Shore-Sheppard & Tara Watson, 2010. "Local Fiscal Policies and Urban Wage Structures," Public Finance Review, , vol. 38(5), pages 540-584, September.
    4. Tara Watson & Sara McLanahan, 2011. "Marriage Meets the Joneses: Relative Income, Identity, and Marital Status," Journal of Human Resources, University of Wisconsin Press, vol. 46(3), pages 482-517.
    5. Töngür, Ünal & Elveren, Adem Yavuz, 2014. "Deunionization and pay inequality in OECD Countries: A panel Granger causality approach," Economic Modelling, Elsevier, vol. 38(C), pages 417-425.
    6. Linda Lobao & P. Wilner Jeanty & Mark Partridge & David Kraybill, 2012. "Poverty and Place across the United States," International Regional Science Review, , vol. 35(2), pages 158-187, April.

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