Male-female wage gap in the private sector versus the state and local public sectors
|Private sector||State and local public sectors|
|Average female wage income compared with male wage income||-20.4%***||-20.9%***|
|Female wage income compared with wage income of similarly educated males|
|Less than a high school education||-25.7%***||-23.7%|
Notes: Controls for all models include education, experience, gender, race, marital status, organizational size, metropolitan status, citizenship, Census region, full-time status, and total work hours. Full regression results are included in the appendix tables. See the “Table and figure notes” section of the briefing paper for more detail.
*Probability estimate 0 is >.1. (Interactive models show significance of the interaction term.)
**Probability estimate 0 is >.05.
***Probability estimate 0 is >.01.
Values describe percentage difference in annual income from wages compared with that of similar male workers in the same sector, using the equation dlog(y)/dx =100% x (e≈í‚â§-1).
We use interactive models to calculate specific effects by education. The values displayed are calculated using the equation dlog(y)/dx =100% x (e≈í‚â§-1), where ≈í‚â§ equals the sum of the coefficients on the education indicator term and the education-state and local sector interaction term.
In the interactive models, the probability estimates denote the statistical significance of the interaction terms. Thus for models with statistically insignificant interaction terms, such as the "less than a high school education" interaction in the state and local public sectors, this indicates that the male-female wage gap at this education level is not statistically different from the wage gap at the "high school" education level. Full regression results are included in the appendix tables.
Source: Authors’ analysis of Current Population Survey Annual Social and Economic Supplement microdata, pooled years 2006 and 2007
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