Table 1
Estimates of the public-sector pay gap in Connecticut from different regression models
| Classic human capital | With demographic controls | With all Biggs’s variables | Using Biggs’s sample | |
|---|---|---|---|---|
| State and local government | -0.114 | -0.091 | -0.011 | 0.057 |
| Adjusted for firm size | -0.165 | -0.142 | -0.062 | -0.002 |
| Education | 0.121 | 0.112 | 0.046 | Yes |
| Experience | 0.056 | 0.049 | 0.049 | Yes |
| Experience squared | -0.001 | -0.001 | -0.001 | Yes |
| Hours of work | 0.025 | 0.021 | 0.019 | Yes |
| Year | -0.012 | -0.011 | -0.012 | Yes |
| Female | No | -0.222 | -0.211 | Yes |
| Black | No | -0.152 | -0.090 | Yes |
| Other race | No | -0.060 | -0.056 | Yes |
| Hispanic | No | -0.174 | -0.145 | Yes |
| Married | No | 0.165 | 0.136 | Yes |
| Immigrant | No | -0.066 | -0.099 | Yes |
| Degree field controls? | No | No | Yes | Yes |
| Occupation group controls? | No | No | Yes | Yes |
| Local area controls? | No | No | Yes | Yes |
Sources: Author's analysis of 2009-2013 microdata from the American Community Survey (Ruggles et al. 2015); Biggs (2015).
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