The impact of a government pay reform in Mexico on the public sector wage gap

Using cross-sectional data from 2017 to 2019, both the mean and unconditional quantile (UQ) regression models within a difference-in-differences (DID) framework are fit. Stata allows the use of UQ regressions based on the recentred influence function (RIF) to center the IF around the statistic of interest (for example, the population mean ‘µ’, 10 E[Y]) and not zero (for example, reweighting the observations) for generating the RIF quantiles. The RIF average effects are interpreted at different quantiles of the unconditional wage distribution (for example, the 5th or 95th percentiles or other intermediate quantiles).

Then the DID approach implemented through Stata provides the effects of the reform before and after the policy intervention. It also deals with the endogeneity of employment selection by accounting for the differences in the unobservable effects of the public–private employment sector selection pretreatment. Posttreatment, such unobservables are differenced out to mitigate the concerns about potential selection bias.

Robustness checks are also executed with Stata, such as cohort fixed effects with pseudopanel dataset, a two-step model within a Heckman framework, the Hansen J-statistic to test orthogonality, an IV-based model, an individual-level fixed-effects (FE) model with a panel dataset, and a placebo in-time test.

Although there is some evidence that public sector employees anticipated the introduction of the policy, it reduced the public sector pay gap strongly among the lower-paid workers of the unconditional pay distribution. The UQ effects of this policy change on the public–private sectoral wage gap contribute to the limited literature for both developed and developing countries.