Skip to main content

Advertisement

Log in

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

  • Published:
Journal of Labor Research Aims and scope Submit manuscript

Abstract

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.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

Notes

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

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

  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. 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. 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. 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. 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. We thank an anonymous referee for raising this concern.

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

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

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

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

  22. The results are available on request.

References

  • Anderson D, Binder M, Krause K (2003) The motherhood wage penalty revisited: experience, heterogeneity, work effort, and work-schedule flexibility. Ind Labor Relat Rev 56:273–294

    Article  Google Scholar 

  • Averett S, Hotchkiss J (1995) The probability of receiving benefits at different hours of work. Am Econ Rev 85:276–280

    Google Scholar 

  • Baughman R, DiNardi D, Holtz-Eakin D (2003) Productivity and wage effects of “family-friendly” fringe benefits. Int J Manpow 24:247–259

    Article  Google Scholar 

  • Bayard K, Hellerstein J, Neumark D, Troske K (2003) New evidence on sex segregation and sex differences in wages from matched employee-employer data. J Labor Econ 21:887–922

    Article  Google Scholar 

  • Berger L, Hill J, Waldfogel J (2005) Maternity leave, early maternal employment and child health and development in the US. Econ J 115:29–47

    Article  Google Scholar 

  • Berger L, Waldfogel J (2004) Maternity leave and employment of new mothers in the United States. J Popul Econ 17:331–349

    Article  Google Scholar 

  • Brown C (1980) Equalizing differences in the labor market. Q J Econ 94:113–134

    Article  Google Scholar 

  • Carneiro P, Heckman J, Masterov D (2005) Labor market discrimination and racial differences in premarket factors. J Law Econ 48:1–39

    Article  Google Scholar 

  • Carrington W, Troske K (1998) Sex segregation in U.S. manufacturing. Ind Labor Relat Rev 51:445–464

    Article  Google Scholar 

  • Dale-Olsen H (2006) Wages, fringe benefits and worker turnover. Labour Econ 13:87–105

    Article  Google Scholar 

  • DeLeire T, Levy H (2004) Worker sorting and the risk of death on the job. J Labor Econ 22:925–953

    Article  Google Scholar 

  • Dickens W (1990) Assuming the can opener: hedonic wage estimates and the value of life. NBER Working Paper Series, Working Paper 3446

  • Duncan G, Holmlund B (1983) Was Adam Smith right after all? another test of the theory of compensating wage differentials. J Labor Econ 1:366–379

    Article  Google Scholar 

  • Filer R (1985) Male–female wage differences: the importance of compensating differentials. Ind Labor Relat Rev 38:426–437

    Article  Google Scholar 

  • Filer R (1986) The role of personality and tastes in determining occupational structure. Ind Labor Relat Rev 39:412–424

    Article  Google Scholar 

  • Fullerton H (1999) Labor force projections to 2008: steady growth and changing composition. Mon Labor Rev November:19–32

  • Gariety B, Shaffer S (2001) Wage differentials associated with flextime. Mon Labor Rev 124:68–75

    Google Scholar 

  • Glass J, Camarigg V (1992) Gender, parenthood, and job–family compatibility. Am J Sociol 98:131–151

    Article  Google Scholar 

  • Golden L (2001) Flexible work schedules: what are we trading off to get them? Mon Labor Rev 124:50–67

    Google Scholar 

  • Heckman J, Stixrud J, Urzua S (2006) The effects of cognitive and noncognitive abilities on labor market outcomes and social behavior. J Labor Econ 24:441–482

    Google Scholar 

  • Hwang H, Reed W, Hubbard C (1992) Compensating wage differentials and unobserved productivity. J Polit Econ 100:835–858

    Article  Google Scholar 

  • Johnson N, Provan K (1995) The relationship between work/family benefits and earnings: a test of competing predictions. J Socio-Econ 24:571–584

    Article  Google Scholar 

  • Macpherson D, Hirsch B (1995) Wages and gender composition: why do women's jobs pay less? J Labor Econ 13:426–471

    Article  Google Scholar 

  • McCrate E (2005) Flexible hours, workplace authority, and compensating wage differentials in the US. Fem Econ 11:11–39

    Article  Google Scholar 

  • Olson C (2002) Do workers accept lower wages in exchange for health benefits? J Labor Econ 20:S91–114

    Article  Google Scholar 

  • Oyer P (2005) Salary or benefits? NBER Working Paper Series, Working Paper 11818

  • Rosen S (1986) The theory of equalizing differences. In: Ashenfelter O, Layard R (eds) Handbook of labor economics, vol 1. North Holland, Amsterdam

    Google Scholar 

  • Rothstein D (1997) Early career supervisor gender and the labor market outcomes of young women. In: Blau F, Ehrenberg R (eds) Gender and family issues in the workplace. Russell Sage Foundation, New York

    Google Scholar 

  • Simon K, Kaestner R (2004) Do minimum wages affect non-wage job attributes? Evidence on fringe benefits. Ind Labor Relat Rev 58:52–70

    Article  Google Scholar 

  • StataCorp (2007) Stata user’s guide release 10. StataCorp LP, College Station, TX

    Google Scholar 

  • U.S. Bureau of Labor Statistics (2005) Workers on flexible and shift schedules in 2004 summary. U.S. Department of Labor, Washington DC

    Google Scholar 

  • U.S. Bureau of Labor Statistics (2006) Usual weekly earnings of wage and salary workers: second quarter 2006. U.S. Department of Labor, Washington DC

    Google Scholar 

  • Waldfogel J (1998) The family gap for young women in the United States and Britain: can maternity leave make a difference? J Labor Econ 16:505–545

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Paul Sicilian.

Appendix

Appendix

Table 8

Table 8 Correlation matrix, supplement to Table 2

Rights and permissions

Reprints and permissions

About this article

Cite this article

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

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12122-008-9046-1

Keywords

Navigation