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Laissez-Faire Economic Policy in a World Where Gender Income Gaps Exist: Helping or Hurting?

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Abstract

Using IPUMS data on U.S. states from 1980 to 2010, we examine the effect of economic freedom on the gender income gap. We find that economic freedom is positively related to an increase in the gender income gap. When we break up the index into its components, we find different effects of various types of policy. For example, we find that decreases in government spending and a lower minimum wage have a statistically significant and positive effect on gender income disparities across states.

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Notes

  1. For example, Kreft and Sobel (2005) and Wiseman and Young (2013) both find that the EFNA index positively correlates with state-level measures of entrepreneurial activity; Garrett and Rhine (2011) find this index to be positively related to employment growth. Ashby and Sobel (2008) find that the EFNA index is associated with increases in income and income growth; Compton et al. (2011) find similar results using a panel dataset. Researchers tend to find analogous results in the cross-country setting. For an extensive review of studies using the EFW index, see Hall and Lawson (2014).

  2. One possible explanation for the differences across pay is gender discrimination across occupations (Olfert and Moebis 2006). While this consideration is important, it is beyond the scope of this paper to look at the role of occupation in the gender wage gap.

  3. The large gap stems from the inability to separate full-time and part-time workers even in this narrow category.

  4. While we are interested in the effect of economic freedom on the aggregate income gap, it is also important to consider if these aggregate effects hold for men and women that are already employed. The aggregate income gap captures not only changes in income, but also changes in employment status. The narrower income gap measure (the gap in salary and wage income) focuses more on changes in income alone. We therefore re-estimate the main results with this narrower income measure and report the associated coefficients in Appendix Table 17. The main results hold.

  5. Includes employment insurance, workers compensation, and other pensions as a percentage of GSP.

  6. Includes income taxes, consumption taxes, property and sales taxes, contributions to Social Security plans, and other taxes.

  7. Includes property taxes, contributions to Social Security Insurance, and various other taxes.

  8. Includes general sales tax revenues as well as revenue from liquor and tobacco taxes.

  9. See Karabegovic and McMahon (2006) for more information on the components that make up the EFNA Index.

  10. Because we are using fixed effects, the levels and first-differenced regressions should be very similar. Nevertheless because our T is greater than two, it is important to test the robustness of the fixed effects results with analogous first differenced specifications.

  11. Because instrumenting for multiple collinear endogenous variables leads to a serious weak instrument problem, we only conduct the GMM robustness analysis for the aggregate freedom measure.

  12. Appendix Table 17 presents the analogous results of Table 4 using the narrower definition of the income gap that includes only individuals that earn positive salary or wage income. The general pattern of the results hold in that economic freedom is more strongly associated with increases in male income, widening the gap. However, the more interesting finding is that the positive association between female income and economic freedom disappears. This suggest that economic freedom increases female income through increased employment rather than increased wages of those that are employed.

  13. This does not imply that women are not getting any of the newly available jobs, just that men may be getting the higher quality, higher paying jobs. As the results of Table A1 imply, the simple positive correlation between female income and economic freedom disappears when looking only at the average working income of females that are earning a positive income from salary or wages. This suggests that the positive correlation uncovered in Table 4 stems from an increase in employment.

  14. College degree is defined here as an individual have 4 years of college; no college degree is defined as having less than 4 years of college.

  15. We are indebted to a referee for bringing this literature to our attention, as well as the work of Frazis et al. (1998) on gender differences in on-the-job training. If employers are judging female candidates as a group with either different preferences or less on-the-job training rather than individuals, this could lead to our findings.

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Authors and Affiliations

  1. Department of Economics, West Virginia University, Morgantown, WV, USA

    Joshua Hall

  2. Department of Economics, Finance, & Legal Studies, University of Alabama, Tuscaloosa, AL, USA

    Amanda Ross

  3. Department of Agricultural and Applied Economics, Texas Tech University, Lubbock, TX, USA

    Jamie Bologna Pavlik

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  1. Joshua Hall
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  2. Amanda Ross
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Correspondence to Jamie Bologna Pavlik.

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Appendix

Appendix

Table 17 Impact of the Overall Economic Freedom Index on the salary/wage income gap with individuals that earned a positive income only
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Hall, J., Ross, A. & Pavlik, J.B. Laissez-Faire Economic Policy in a World Where Gender Income Gaps Exist: Helping or Hurting?. J Econ Race Policy 3, 144–158 (2020). https://doi.org/10.1007/s41996-019-00044-y

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