State and local public-sector wage penalty, overall and by sex and race
| Wage penalty | |
|---|---|
| Average annual wage income penalty for state and local public-sector employees versus private-sector employees | -11.7%*** |
| Comparison with private-sector employees of the same sex | |
| Men in state and local public sectors | -11.1%*** |
| Women in state and local public sectors | -12.2% |
| Comparison with private-sector employees of the same race | |
| Whites in state and local public sectors | -14.5%*** |
| African Americans in state and local public sectors | -1.7%*** |
| Hispanics in state and local public sectors | -3.7%*** |
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 private-sector workers, using the equation dlog(y)/dx =100% x (eβ-1).
We use interactive models to calculate specific effects by sex and race. The values displayed are calculated using the equation dlog(y)/dx =100% x (eβ-1), where β equals the sum of the coefficients on the sex/race indicator term and the sex/race-state and local sector interaction term.
In the model interacting the state and local sector indicator variable with the female indicator variable, the state and local indicator is highly significant (p<.0001), while the interactive term is not statistically significant (p=.2). This suggests that the wage penalty of working in the state and local public sectors versus the private sector is the same for both men and women. 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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