“Family-Friendly” Fringe Benefits and the Gender Wage Gap


Evidence suggests a large portion of the gender wage gap is explained by gender occupational segregation. A common hypothesis is that gender differences in preferences or abilities explain this segregation; women may prefer jobs that provide more “family-friendly” fringe benefits. Much of the research provides no direct evidence on gender differences in access to fringe benefits, nor how provision affects wages. Using data from the National Longitudinal Survey of Youth 1979, we find that women are more likely to receive family-friendly benefits, but not other types of fringe benefits. We find no evidence that the differences in fringe benefits explain the gender wage gap.

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  1. 1.

    Although, similar to Averett and Hotchkiss (1995), the presence of children does not raise the probability of receiving health insurance.

  2. 2.

    The DOT codes provide information on several non-wage aspects of occupations but not on fringe benefits.

  3. 3.

    Hwang et al. (1992) discuss the size of the bias caused by unobserved heterogeneity and conclude that it is potentially quite large. Some research that corrects for the heterogeneity bias has succeeded in finding compensating wage differentials in some cases. In particular, Olson (2002) uses an IV method and finds that health care benefits have a statistically significant, negative effect on wages. Duncan and Holmlund (1983), like Brown, use FE methods and find more supportive evidence of the theory of compensating wage differentials than did Brown.

  4. 4.

    For example, in 1975, 47.4 percent of women with children under the age of 18 were in the labor force. By 1998, this figure had risen to 72.3 percent (U.S. Bureau of Labor Statistics 2006).

  5. 5.

    Since this information is self-reported, there is concern as to whether this information is truly measuring actual fringe benefits or merely awareness of the fringe benefits offered. We explore this below.

  6. 6.

    We use the created hourly wage variable provided in the NLSY79. For those who report being paid hourly, the NLSY79 provides this wage rate directly. For those who report being paid other than hourly, the NLSY79 provides a calculated hourly wage using information on hours worked and pay. We calculate constant dollar (1998) wages using the Consumer Price Index (CPI).

  7. 7.

    Family-friendly benefits are those that make it easier for women to be a primary care-giver in the home while also participating in the labor market. Arguably a more descriptive name would be “women-friendly”, but we use the more common term, “family-friendly.”

  8. 8.

    We thank an anonymous referee for raising this concern.

  9. 9.

    Also, in 1979, respondents are asked about weeks worked in 1975, 1976 and 1977. We did not use this information because we are concerned with the accuracy of retrospective data.

  10. 10.

    Urate is a series of dummy variables for local unemployment rates between 0-3 percent, 3-6 percent, 6-9 percent, 9-12 percent, 12-15 percent and greater than 15 percent. Oyer shows that the local unemployment rate is a determinant of fringe benefits.

  11. 11.

    Averett and Hotchkiss (1995) show that fringe benefits depend on part-time versus full-time status. Oyer (2005) finds that those who work more than full-time receive more benefits, ceteris paribus.

  12. 12.

    A correlation matrix for all variables used in our analysis is provided in Appendix Table 8.

  13. 13.

    The method used for this adjustment is explained in StataCorp (2007, p. 272).

  14. 14.

    The full set of regressors is listed in a footnote in Table 4.

  15. 15.

    We also included broad industry and occupation controls with FEM. However, there is strong collinearity between the mean of FEM and each family-friendly fringe within broad occupation controls (correlations ranging from 0.67 to 0.76). Thus, in our view, the most credible specifications are those including FEM, but omitting the broad controls.

  16. 16.

    Note that FEM is constant across all individuals in the same 3-digit occupation, although we treat it as if it varies at the individual level. Thus, while the estimated coefficients are unbiased, the reported standard errors overstate the precision of the estimates.

  17. 17.

    We also estimated all equations including a quadratic term for FEM. The coefficient on the quadratic term was negative for every fringe except training. For some fringes the quadratic term in FEM is significant, but for most it was not. No qualitative conclusions depend on the inclusion of the quadratic term. For simplicity, we report results exclusively for the linear-in-FEM specifications.

  18. 18.

    Recreating Macpherson and Hirsh’s standard regression (education, potential experience, union coverage, part-time status, race, region, urban area and broad industry and occupation controls) using the NLSY79 data, we find an adjusted log wage gap of 0.193.

  19. 19.

    All reported regressions omit the broad industry and occupation dummies because of the concern with multicollinearity discussed above. None of the conclusions from the wage regressions depend on the presence of these controls.

  20. 20.

    We also experimented with IV estimators in unreported regressions, but it is difficult to find credible identifying restrictions and the results were statistically insignificant.

  21. 21.

    Using a Hausman test, random effects models are rejected in favor of FE for every case.

  22. 22.

    The results are available on request.


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Correspondence to Paul Sicilian.



Table 8

Table 8 Correlation matrix, supplement to Table 2

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Lowen, A., Sicilian, P. “Family-Friendly” Fringe Benefits and the Gender Wage Gap. J Labor Res 30, 101–119 (2009). https://doi.org/10.1007/s12122-008-9046-1

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  • Fringe benefits
  • Gender wage gap
  • Compensating wage differentials
  • National longitudinal study of youth