Drawing on a matched survey–administrative dataset tracking careers from 1975 to 2018, we examine the trends in intragenerational earnings mobility in Italy over the past 40 years. We compare earnings trajectories from age 35 to age 45 via a refined version of the ‘income risk decomposition’ proposed by Austin Nichols in 2008, distinguishing between ‘good’ and ‘bad’ earnings mobility from an individual welfare perspective. Our findings reveal that the long-run trend of increasing cross-sectional earnings inequality in Italy has been accompanied by widening persistent disparities within the same generation. For all cohorts of workers, at least 80% of inequality is permanent, reaching nearly 90% for the most recent cohort. We also uncover that a substantial share of individuals — between 25% and 39% — do not benefit from stable upward income mobility during a crucial career phase. This issue has worsened over time, with the last ten cohorts experiencing higher income instability (+20.2%) and declining upward mobility (−34.7%), largely explained by the growing prevalence of atypical employment arrangements. Furthermore, using intragenerational Great Gatsby curves, we show that cohorts exposed to greater earnings inequality also face more persistent differences and reduced earnings growth, especially in the aftermath of the Great Recession. 

Abstract: The work compares across cohorts and different levels of education the early-stage evolution of several labour market outcomes, with the aim of studying whether and to what extent education matters for the level, growth and stability of earnings. By using a rich longitudinal dataset developed from merging survey and administrative data, this article describes the evolution of earnings in the five years following education completion in Italy comparing differently educated workers born between 1970 and 1984. We find evidence of an 'education premium' in terms of faster school-to-work transition, higher employability and higher earnings. Moreover, education is associated with positive, faster and more volatile earnings growth. However, no clear-cut changes across cohorts in the association between the various outcomes and the level of education emerge from our analysis.

Abstract: The economic literature provides evidence that standard demographic characteristics and human capital variables explain at most one third of wage inequality in Mincerian earnings equations. This work explores the unexplained inequality by using Italian linked employer-employee data from 1998 to 2016. I provide evidence that, from the end of the 1990s to 2016, the type of contract became increasingly important in explaining wage inequality, especially annual and weekly, but around 70% of annual earnings inequality, and 40% of weekly and hourly wages remain unexplained by observable characteristics. My results suggest that part of the unexplained variance is due to differences between the firms in which the workers are employed, but the largest contribution remains workers’ unobserved heterogeneity. 

Keywords: earnings inequality, linked employer-employee data, AKM model, Italy.

Abstract: Using administrative data on the universe of labor market flows for Italy, we estimate the causal effect of job creation and destruction shocks on internal migration. We exploit plausibly exogenous variation resulting from mass hiring and layoff events at the establishment level. Our estimates show that job creation has a strong effect on in-migration while job destruction has a milder effect on out- migration. Crucially, we document that the large responsiveness of in-migration operates through changes in workers’ chosen destination alternatives. We show that these empirical findings can be reconciled by a simple model of migration enriched by labor demand shocks.

Abstract: Restoring the theoretical foundation of John Roemer’s conceptualization of inequality of opportunity (IOp), we introduce an innovative empirical approach to measure unfair inequalities through Bayesian networks. This methodology enhances our understanding of income inequality through structural learning algorithms, generating an IOp index and, most importantly, shedding light on the underlying income formation process. We demonstrate how this proposal relates to established measurement methods through simulated data, and provide an application to five European countries to illustrate the potential of Bayesian networks in the context of measuring inequality of opportunity.

This paper introduces a novel global collection of data on estate, inheritance, and gift (EIG) taxes, across several decades and over 160 countries. The data provide a comprehensive collection of harmonized EIG tax rates, exemptions, schedules, and revenues. We observe an overall decreasing prominence of EIG taxation around the globe. Before the 1980s, the top marginal tax rate averaged approximately 30 percent, but by 2022, it had dropped to around 20 percent. However, the data also suggest substantial heterogeneity across countries in EIG taxation dynamics. We identify three main clusters: groups of countries that have reduced top rates, increased them, or repealed the tax altogether. Likewise, countries can be grouped according to whether they experienced a reduction or an increase in EIG tax revenue over the past four decades. Examining the tax schedule structure, we find that some countries use progressively increasing tax brackets, while others apply a flat rate. Over time, the number of tax brackets has significantly decreased, from over 20 in the 1970s to around 5 in recent years. We then illustrate an application of our data by analyzing the effect of changes in top marginal tax rates on EIG tax revenue both in World countries and in U.S. states only. We estimate an average 9% increase in EIG tax revenue for every percentage point increase in the top marginal tax rate.

Using administrative data on the universe of labor market flows for Italy, we estimate the causal effect of job creation and job destruction shocks on internal migration flows. To do so, we exploit plausibly exogenous variation stemming from mass hire and layoff events at the establishment level. Our estimates show that job creation has a strong effect on the in-migration rate, while job destruction has a milder effect on the out-migration rate. Crucially, we document that the large responsiveness of in-migration operates through changes in workers’ chosen destination alternatives. We show that the broad pattern of the estimated response can be reconciled by a simple migration model enriched by labor demand shocks.

Abstract: Measures of income polarization are often motivated as quantifying conflict potential in a society. The key premise is that individuals share a feeling of “group identity” with people with similar income and feel “alienated” from people distant in income. The group identity element makes the concept of polarization distinct from the concept of inequality. Existing measures of polarization however assume static societies. We argue that this is unsatisfactory and propose a measure that incorporates the dynamics of income over time in its elaboration. This inter-temporal income polarization measure introduces memory parameters that allow past income differences to determine the degree of current alienation and identification in a society. This leads to measures of income polarization that are sensitive to the history of interpersonal proximity and distances in income trajectories. We illustrate the empirical relevance of this longitudinal perspective with an application based on administrative data on labour income of cohorts of Italians.

This thesis stems from research work I carried out in various universities and institutions to provide new perspectives on the analysis of mobility in different research contexts. The first two chapters deal with earnings mobility and its association with inequality (Chapter 1) and polarization (Chapter 2), while the third chapter is concerned with geographical mobility in response to labour market shocks (Chapter 3). In all three cases, the focus of the analysis is on the Italian labour market. However, while the first and last works are applied in nature, the second one is a theoretical paper whose application is instrumental to understanding the theory and demonstrating its empirical relevance.

Abstract: The report investigates the role played by the middle class in Italy over the last decades, in comparison with other European countries, using various proxies of economic well-being (i.e. individual labour income, equivalised disposable income, wealth), and exploiting various cross-sectional and longitudinal sources (i.e. AD-SILC, EU-SILC, SHIW). Adopting an economic definition of the middle class, based on individual positions with respect to median positions in the income scale, we first assess how the relative weight of the middle class – in terms of population share and share of total income – has evolved over time, and then use longitudinal data to explore mobility in and out of the middle class.