Gender Pay Gap (Private and Public Sector)
Introduction
Using Italian microdata and the analysis conducted by the Department of Economics at the University of Pavia and the University of Milan, this article aims to analyze the variations in the gender pay gap in the public sector compared to the private one. During the last decades polices have been increased to cut down the gender pay gap. Yet massive differences still exist around countries. However, studies have proved that the mechanisms of selection in public contests may include a merit-based procedure.
Descriptive statistics
The empirical approach used is based on the estimation and comparison of the gender pay gap (GPG) in log hourly wages and starts from a large survey of the Italian labor market, conducted between 2005 and 2014.
It includes exclusively full-time employees between 18 and 64 years old.
The first table above illustrates the difference between the average net hourly earnings of men and women, not considering differences in individual characteristics such as age, education, experience, or occupation.
The second table shows both means and standard deviations of various variables for men and women engaged in public contests or not. Log hourly wages are not particularly different for men and women recruited by public contests, but in terms of background characteristics (for instance, educational or family) men and women working in a public sector differ.
Women register a higher level of education, are more likely to pursue managerial positions, and have more often children below the age of ten. Generally speaking, more females than males are gainfully employed via public contest. Panel B shows that men and women not recruited by public contest face a significant wage gap of 10% and Women are still significantly better educated. Table 3 shows that the wage difference for public servants, though being positive, is not significant whereas for private-sector workers the difference in wages is again relevant (Panel B). The previous section suggests important differences in hourly wages by public-contest recruitment.
Largely, what emerges from this analysis is that there are significant differences between public contest and private employment, mainly in terms of managerial roles and the number of mothers in the workforce. Moreover, public-contest recruitment leads to a wage premium, with women experiencing a premium between 43% and 58%, and men between 33% and 45%. These findings bring to light that public contest selection positively affects wages, with a stronger impact on early career earnings.
The hiring decision
Furthermore, it is also highly necessary to investigate the hiring decision which consists of a potential cause of selection bias.The selection method depends on two choices: employment hiring and public-contest enrollment. The selection rules are described by this equation:
where Y*iw is the unobservable index function that underlies the employment decision (yes or no); Y*ir is the unobservable index function of public-contest recruitment of individual I (yes or no); Zi and Qi are the vectors of the explanatory variables, and the error terms are uiw and uir.
The two-step method approximates equations 2 and 3 to find the correction and selectivity terms, λW and λR. The parameter which measures the correlation of the residuals from the two models (ρ) shows that equations 2 and 3, are strongly and positively correlated for both sexes, meaning that the two decisions should be formed together.
This approach employs, for example, the variables Kids and Kids < 10 Years, as women with children are less likely than others to be in service. Yet, men tend to receive more often job offers, undoubtedly because of the traditional view that still exists.
Table 7 gives the results based on 2 steps: the identification of at least one variable that affects the selection process but not the outcome practice, and the additive separability of the errors in the selection process.
In the second step, the (double) selection-corrected wage equations are valued and the selection terms λW and λR are included in the equivalences, making an approximation of the wages for those selected by the public contest and those who are not.
Studying λPC and λNPC (coefficients of the selection terms) demonstrates the existence of selection bias.
Considering people who were recruited by public contest, the positive sign of λPC denotes that unobserved positive characteristics that raise the probability of winning a contest also increase earnings. So, workers recruited by public tournaments have better unobserved characteristics and obtain higher wages than those not engaged in public contests.
Generally, the results imply that workers recruited by public contests have better unobserved characteristics and earnings than other employees with comparable features, and this is valid both for males and females.
Quantile decomposition
Another perspective to study the phenomenon is to decompose the wage gap in explained and unexplained factors, using the procedure proposed by Machado and Mata (2005), which generalizes the Oaxaca-Blinder decomposition to a quantile regression framework.
The wage gap between males and females can be divided into two parts: one reflecting the impact of different characteristics, and the other catching differences unexplained by the quantile regression model. Since the same features should have an equal impact on earnings for both sexes, the wage equation should ideally be gender-neutral. Thus, this represents the unexplained quantity of the gender pay gap.
Where yk(𝜃) denotes the observed log wages fork=(male, female),̂yk(𝜃) denotes the estimator of the k = (male, female) log wages based on the observed sample, and y ̃f (𝜃) denotes the estimated counterfactual log wages.
For this study, the target population included individuals between 15 and 64 years of age.
As regards the independent variables, education, family, occupation, geographic characteristics, and personal skills were included.
In the private sector, the unexplained part of the gap declines as you move across the wage distribution. This means that employer discrimination is more relevant among low-wage employees than high-wage workers in the private sector. When examining the impact of observed features on the gender wage gap rises in the private sector but remains stable in the public sector. This reveals that gender segregation is more discernable in the private sector.
The longitudinal analysis offers insights into the influence of introducing occupation measures into the set of labor market controls. Unlike the cross-section analysis, the longitudinal analysis does not reveal evidence of a segregation effect. In this case, controlling for substitutions of individual ability, occupation, and industry allocation does not significantly change the percentage of the gender gap.
This implies that the effect of segregation, highlighted in the cross-section analysis, is not as significant when individual heterogeneity is considered and it becomes clear that the source of the gap differs between the two sectors.
The explanation for the larger unexplained component of the GWG in the public sector has two components. From one point of view, unexplained components may encompass non-monetary benefits offered by the public sector. Furthermore, the increasing weight of the wage effect may indicate favoritism in the public sector for men: top management roles in the public sector often involve political arrangements that are more likely to favor men over women.
Conclusion
These results denote that in the public sector, the gap may be associated with standardized careers and different selection methods (e.g. competitions). The public sector’s stress on gender equality policies could also contribute to the lower unexplained component. Yet, the increasing weight of the wage effect in the public sector, especially at the top, may indicate favoritism toward men.
The results of the study generally confirm that the Gender Pay Gap is significantly higher in the private sector compared to the public one.
The public sector conventionally attracts women by offering jobs with working conditions that allow them to find a work-life balance. In Italy, these non-monetary advantages have a fundamental role in setting salaries. In contrast to the reduced support offered by the private reality, it can help to settle both work and family duties.
Sources:
Angrist, J., Imbens, G., & Rubin, D. (1996). Identification of causal effect using instrumental variables. Journal of the American Statistical Association, 91, 444–472.
“Discriminate me — If you can! The disappearance of the gender pay gap among public-contest selected employees in Italy” written by Carolina Castagnetti, Luisa Rosti, Marina Töpfer (Department of Economics and Management, University of Pavia, Italy, School of Business and Economics, University of Erlangen-Nürnberg, Germany)
“Understanding the gender wage-gap differential between the public and private sectors in Italy: A quantile approach” written by Carolina Castagnetti ,Maria Letizia Giorgetti.
