Cyclical dynamics and the gender pay gap: A structural VAR approach - Kovalenko, Tim; Töpfer, Marina (Economic Modelling, 2021)
Gender pay gaps persist worldwide despite political emphasis to close them. The literature found various drivers of the gaps but remained vastly silent about the role of cyclical dynamics. Using quarterly US data over the period 1979-2019, we study the effects of cyclical dynamics on the gender pay gap based on a structural vector auto-regression model with zero and sign restrictions. The results suggest that technology shocks lead to lower levels of the gender pay gap in the medium run, while higher wage bargaining power reduces the gap in the short run. However, these reductions of the gap come at the cost of increased unemployment. As a policy implication, these results imply a trade-off between lower gender pay gaps and higher unemploymen
Keywords: Gender pay gap; Vector Auto-Regression(VAR) model; Cyclical dynamics; Macroeconomic shocks; Gender

Discriminate Me – If You Can! The Disappearance of the Gender Pay Gap among Public‐Contest Selected Employees in Italy - Castagnetti, Carolina; Rosti, Luisa; Töpfer, Marina (Gender, Work & Organization, 2020)
This paper investigates the effect of public‐contest recruitment on earnings for men and women using Italian microdata over a time period of ten years. We find that the gender pay gap vanishes, and even reverses among young employees when they are selected through public contests. The results suggest that selection mechanisms like public contests may offer a way for merit‐based and gender‐fair wage‐setting. However, since public contests and the public sector are highly correlated, we analyze the gender pay gap by taking into account both the connection between the public and private sector and the open contest issue. By decomposing our results by sector, we find that public contests are a necessary but not sufficient condition for merit‐based and gender‐fair recruitment. Similarly, the institutional environment of the public sector is a necessary but not sufficient condition for ensuring that public contests are merit‐based and gender‐fair screening devices. Taken together, these two factors cause the gender pay gap to disappea
Keywords: Diskriminierung

Do Unions and Works Councils really dampen the Gender Pay Gap? Discordant Evidence from Germany - Oberfichtner, Michael; Schnabel, Claus; Töpfer, Marina (Economics letters, 2020)
Using a large employer–employee dataset, we provide new evidence on the relationship between the gender pay gap and industrial relations from within German workplaces. Controlling for unobserved workplace heterogeneity, we find no evidence that introducing or abandoning collective agreements or works councils affects the gender pay gap. This result holds at the mean and along the distribution, challenging the stylized fact that unions and works councils dampen the gender pay ga
Keywords: Gender

Honours as a Signal – Evidence from a Quasi-Natural Experiment in Italy - Töpfer, Marina (Economics Bulletin, 2019)
This note compares the wage premium of honours degrees in two different Italian university systems (old and new) in 2011 using data from the Italian National Institute of Statistics. The wage premium of a honours degree in the new system disappears due to honours inflation and hence the signal of potential higher productivity stopped working. In contrast, for graduates under the old system, the signal statistically significantly affects wage
Keywords: Signalling Model; Higher Education; Italy

Overeducation and the Gender Pay Gap in Italy - Töpfer, Marina; Castangetti, Carolina; Rosti, Luisa (International Journal of Manpower, 2018)
Purpose The purpose of this paper is to highlight the pivotal role of overeducation in explaining the unexplained part of the gender pay gap (GPG), i.e. the component usually attributed to gender discrimination in the Oaxaca-Blinder decomposition. Design/methodology/approach The study uses a large Italian data set (ISFOL PLUS 2005–2014) to estimate the GPG among properly educated and overeducated workers. The model simultaneously accounts for both participation bias and endogeneity bias by applying an extension of the Heckman’s two-stage procedure. Findings Estimates show that the GPG is significantly higher among overeducated than among properly educated workers because women’s unobservable characteristics driving female employment into overeducation also drag down female wages more than men’s unobservable characteristics drag down male wages. Correcting for the participation and overeducation decisions, the unexplained portion of the GPG disappears among overeducated workers, while it remains significant among properly educated individuals. Originality/value The authors draw the conclusion that overeducation is, first, a first-best matching for individuals (both men and women) compensating with more education for their lower productive characteristics. Second, it may be a signaling device for women spending their useless-for-the-job diploma to inform employers on their valuable though unobservable productive characteristics and fight gender wage discrimination. The results favor education as a tool of counteracting gender discrimination. Hence, as females are less overeducated than males despite their larger representation in higher education, there should not be concern that expanding higher education will disadvantage females.
Keywords: Italy; Overeducation; Gender Pay Gap; Double Selection

The Age Pay Gap and Labor Market Heterogeneity: A New Empirical Approach Using Data for Italy - Töpfer, Marina (Labour, 2020)
Using Italian microdata over the period 2005–2016, this paper studies the difference in pay between elderly (55–64) and adult (34–54) workers in Italy along the wage distribution. The estimation strategy consists in using a three‐way fixed effects wage model and adjusting the wage gap for (observed and unobserved) labour market heterogeneity. The estimation relies on OLS as well as on unconditional quantile regressions. The analysis beyond the mean shows substantial differences in the age pay gap along the wage distribution and finds particularly pronounced gaps at the top. The fixed effects of interest (individual, job, and industry) are estimated via a partitioned procedure. Adjusting the gap for labour market heterogeneity reduces the gap almost to zero. The results suggest that individual differences between the cohorts both observed and unobserved are the main driver of the ga
Keywords: Diskriminierung

The Age Pay Gap between Young and Older Employees in Italy: Perceived or Real Discrimination against the Young? - Castagnetti, Carolina; Rosti, Luisa; Töpfer, Marina (Research in Labor Economics, 2020)
This paper analyzes the age pay gap in Italy (22%), particularly as it is of interest in an aging society and as it may affect social cohesion. Instead of the traditional approach for model selection, we use a machine-learning approach (post double robust Least Absolute Shrinkage Operator [LASSO]). This approach allows us to reduce Omitted Variable Bias (OVB), given data restrictions, and to obtain a robust estimate of the conditional age pay gap. We then decompose the conditional gap and analyze the impact of four further potential sources of heterogeneity (workers', sectors', and occupations' permanent heterogeneity as well as sample selection bias). The results suggest that age discrimination in pay is only perceived but not real in Italy for both men and wome
Keywords: Age pay gap; Perceived discrimination; Machine learning; Italian labour market; Omitted variable bias; Oaxaca-Blinder decomposition

The gender pay gap revisited: Does machine learning offer new insights? - Bonaccolto-Töpfer, Marina; Briel, Stephanie (Labour Economics, 2022)
This paper analyses gender differences in pay at the mean as well as along the wage distribution in Germany. We estimate the adjusted gender pay gap applying a machine learning method (post-double-LASSO procedure). Comparing results from this method to conventional models in the literature, we find that the estimated gap differs substantially depending on the approach used. The main reason is that the machine learning approach selects numerous interactions and second-order polynomials as well as different covariates at various points of the distribution. This insight suggests that more flexible specifications are needed to estimate gender differences in pay more appropriately.<br
Keywords: Gender pay gap; Machine learning; Model selection; Unconditional quantile regression; Gender

The Public-Private Sector Wage Differential Across Gender in Italy: a New Quantile-Based Decomposition Approach - Castagnetti, Carolina; Rosti, Luisa; Töpfer, Marina (Economics Bulletin, 2019)
We use a novel approach that combines quantile wage gap decomposition to standard technique for panel regression.We apply this methodology to investigate the public sector wage gap throughout the wage distribution in Italy by gender. Controlling for unobserved (time-invariant) individual heterogeneity suggests no positive selection effect in the public sector. The analysis reveals a consistent public sector premium throughout the wage distribution and across gender independent from individual endowments (both observed and unobserved
Keywords: Gender

Understanding the public-private sector wage gap in Germany: New evidence from a Fixed Effects quantile Approach∗ - Bonaccolto-Töpfer, Marina; Castagnetti, Carolina; Prümer, Stephanie (Economic Modelling, 2022)
The public-private sector wage gap is an important labor market indicator, reflecting sectoral differences in wage and recruitment policies. We provide new evidence on this sectoral gap throughout the wage distribution in Germany. Using data from the German Socio-Economic Panel (1984–2017), we decompose the wage gap and control for unobservable factors that endogenously determine the occupational sector choice. Our estimates confirm the result in the literature that women benefit from working in the public sector. For men, we find that they are unambiguously disadvantaged, with higher remuneration in the private sector across the entire wage distribution. This result contrasts with previous findings in the literature. Moreover, our findings show that taking endogenous selection into account substantially changes the decomposition of the gap, and it is crucial for assessing alternative policy measures.
CRIS-Team Scopus Importer:2022-09-30
Keywords: Germany; Public-private sector wage gap; Quantile regression for panel data; Gender