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Selection, Investment, and Women's Relative Wages Since 1975

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  • Casey B. Mulligan
  • Yona Rubinstein

Abstract

In theory, growing wage inequality within gender should cause women to invest more in their market productivity and should differentially pull able women into the workforce, thereby closing the measured gender gap even though women's wages might have grown less than men's had their behavior been held constant. Using the CPS repeated cross-sections between 1975 and 2001, we use control function (Heckit) methods to correct married women's conditional mean wages for selectivity and investment biases. Our estimates suggest that selection of women into the labor market has changed sign, from negative to positive, or at least that positive selectivity bias has come to overwhelm investment bias. The estimates also explain why measured women's relative wage growth coincided with growth of wage inequality within-gender, and attribute the measured gender wage gap closure to changing selectivity and investment biases, rather than relative increases in women's earning potential. Using PSID waves 1975-93 to control for the changing female workforce with person-fixed effects, we also find little growth in women's mean log wages. Finally, we make a first attempt to gauge the relative importance of selection versus investment biases, by examining the family and cognitive backgrounds of members of the female workforce. PSID, NLS, and NLSY data sets show how the cross-section correlation between female employment and family/cognitive background has changed from "negative" to "positive" over the last thirty years, in amounts that might be large enough to attribute most of women's relative wage growth to changing selectivity bias.

Suggested Citation

  • Casey B. Mulligan & Yona Rubinstein, 2005. "Selection, Investment, and Women's Relative Wages Since 1975," NBER Working Papers 11159, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:11159
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    2. Pierre-André Chiappori & Murat Iyigun & Yoram Weiss, 2009. "Investment in Schooling and the Marriage Market," American Economic Review, American Economic Association, vol. 99(5), pages 1689-1713, December.
    3. John J. Donohue III, 2005. "The Law and Economics of Antidiscrimination Law," NBER Working Papers 11631, National Bureau of Economic Research, Inc.
    4. Philip U. Sauré & Hosny Zoabi, 2009. "Effects of Trade on Female Labor Force Participation," Working Papers 2009-12, Swiss National Bank.
    5. Lee, Donghoon & Wolpin, Kenneth I., 2010. "Accounting for wage and employment changes in the US from 1968-2000: A dynamic model of labor market equilibrium," Journal of Econometrics, Elsevier, vol. 156(1), pages 68-85, May.
    6. Madrigal, Lucia & Torero, Maximo, 2016. "Using quantitative tools to measure gender differences within value chains," IFPRI book chapters, in: Devaux, André & Torero, Maximo & Donovan, Jason & Horton, Douglas E. (ed.), Innovation for inclusive value-chain development: Successes and challenges, chapter 14, pages 441-464, International Food Policy Research Institute (IFPRI).
    7. Akee, Randall K. Q. & Yuksel, Mutlu, 2010. "Skin Tone's Decreasing Importance on Employment: Evidence from a Longitudinal Dataset, 1985-2000," IZA Discussion Papers 5120, Institute of Labor Economics (IZA).
    8. David H. Autor & Lawrence F. Katz & Melissa S. Kearney, 2005. "Trends in U.S. Wage Inequality: Re-Assessing the Revisionists," NBER Working Papers 11627, National Bureau of Economic Research, Inc.
    9. Dragana Djurdjevic & Sergiy Radyakin, 2007. "Decomposition of the Gender Wage Gap Using Matching: An Application for Switzerland," Swiss Journal of Economics and Statistics (SJES), Swiss Society of Economics and Statistics (SSES), vol. 143(IV), pages 365-396, December.
    10. Devaux, André & Torero, Maximo & Donovan, Jason & Horton, Douglas E. (ed.), 2016. "Innovation for inclusive value-chain development: Successes and challenges," IFPRI books, International Food Policy Research Institute (IFPRI), number 978-0-89629-213-0.
    11. Morley Gunderson, 2006. "Viewpoint: Male‐female wage differentials: how can that be?," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 39(1), pages 1-21, February.

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    More about this item

    JEL classification:

    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity
    • J31 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Wage Level and Structure; Wage Differentials
    • J16 - Labor and Demographic Economics - - Demographic Economics - - - Economics of Gender; Non-labor Discrimination
    • C34 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Truncated and Censored Models; Switching Regression Models

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