Public-private sector pay differentials in a devolved Scotland

Public-PRIVATE Pay Differentials

Table 1. (Continued) Estimation results for males and three different model
specifications

Notes: OLS, sample selection terms based on separate probits, and sample correction terms
based on bivariate probit. Dependent variable is wage in public and private sector. Cross-section
weights applied. ^*,^**, and ^*** denote significance at 10%, 5% and 1% respectively. Standard
errors in parentheses, where OLS standard errors are robust and the S.E. for the remaining
models are bootstrapped. (P) refers to percentile, (BC) to bias correct.

Clearly, significant coefficients are very similar across model specifications,
while significance levels vary. This is particularly pronounced for females. In
general, there is a tendency for standard errors in the OLS model to be slightly
smaller than estimated using bootstrapping. However, in the majority of cases this
only marginally affects significance levels.

Besides age, occupation has the most pronounced impact on wages in both
the public and private sector. Unsurprisingly, professional, managerial and non-
manual occupations yield significantly higher wages than unskilled occupations.

As expected, union membership significantly increases wages in the public
sector yet unions do not affect the private sector wage. In contrast, firm size does
impact on the latter, while it has hardly any affect on the former. Education has little

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