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Even one is too much: the economic consequences of being a smoker

Author

Listed:
  • Hotchkiss, Julie L.

    () (Federal Reserve Bank of Atlanta)

  • Pitts, M. Melinda

    () (Federal Reserve Bank of Atlanta)

Abstract

It is well known that smoking leads to lower wages. However, the mechanism of this negative relationship is not well understood. This analysis includes a decomposition of the wage gap between smokers and nonsmokers, with a variety of definitions of smoking status designed to reflect differences in smoking intensity. This paper finds that nearly two-thirds of the 24 percent selectivity-corrected smoking/nonsmoking wage differential derives from differences in characteristics between smokers and nonsmokers. These results suggest that it is not differences in productivity that drive the smoking wage gap. Rather, it is differences in the endowments smokers bring to the market along with unmeasured factors, such as baseline employer tolerance. In addition, we also determine that even one cigarette per day is enough to trigger the smoking wage gap and that this gap does not vary by smoking intensity.

Suggested Citation

  • Hotchkiss, Julie L. & Pitts, M. Melinda, 2013. "Even one is too much: the economic consequences of being a smoker," FRB Atlanta Working Paper 2013-03, Federal Reserve Bank of Atlanta.
  • Handle: RePEc:fip:fedawp:2013-03
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    File URL: http://www.frbatlanta.org/documents/pubs/wp/wp1303.pdf
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    Citations

    Blog mentions

    As found by EconAcademics.org, the blog aggregator for Economics research:
    1. How smoking hurts you on the labor market
      by Economic Logician in Economic Logic on 2013-09-06 19:33:00
    2. #HEJC papers for August 2013
      by academichealtheconomists in The Academic Health Economists' Blog on 2013-08-01 04:00:48

    More about this item

    Keywords

    smoking wage penalty; wage decomposition; wage differentials;

    JEL classification:

    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • I19 - Health, Education, and Welfare - - Health - - - Other
    • J31 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Wage Level and Structure; Wage Differentials

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