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Reconsidering Union Wage Effects: Surveying New Evidence on an Old Topic

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  • BARRY T. HIRSCH

Abstract

I examine evidence on private sector union wage gaps in the United States. The consensus opinion among labor economists of an average union premium of roughly 15 percent is called into question. Two forms of measurement error bias downward standard wage gap estimates. Match bias results from Census earnings imputation procedures that do not include union status as a match criterion. Downward bias is roughly equal to the proportion of workers with imputed earnings, currently about 30 percent. Misclassification of union status causes additional attenuation in union gap measures. This bias has worsened as private sector density has declined, since an increasing proportion of workers designated as union are instead nonunion workers. Corrections for misclassification and match bias lead to estimated union gaps substantially higher than standard estimates, but with less of a downward trend since the mid 1980s. Private sector union gaps corrected for these biases are estimated from the CPS for 1973-2001. The uncorrected estimate for 2001 is .13 log points. Correction for match bias increases the gap to .18 log points; further correction for misclassification bias, based on an assumed 2 percent error rate, increases the gap to .24. Reexamination of the skill-upgrading hypothesis leads to the conclusion that higher union gap estimates are plausible. The conventional wisdom of a 15 percent union wage premium warrants reexamination.

Suggested Citation

  • Barry T. Hirsch, 2004. "Reconsidering Union Wage Effects: Surveying New Evidence on an Old Topic," Journal of Labor Research, Transaction Publishers, vol. 25(2), pages 233-266, April.
  • Handle: RePEc:tra:jlabre:v:25:y:2004:i:2:p:233-266
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    JEL classification:

    • J3 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs
    • J5 - Labor and Demographic Economics - - Labor-Management Relations, Trade Unions, and Collective Bargaining
    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access

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