Abstract This paper focuses on the estimation of the latent variable human capital (HC) at disaggregated level (worker) by available routinely institutional data flows. In particular we utilize the Lombardy region administrative archive ‘Employment Centers of the Province of Milan’, collecting information about careers of workers in the private sector of the Milan area, and administrative flows collecting mandatory workers' individual income tax returns, filed with the National Internal Revenue Service. First, we propose and empirically estimate HC scores in a static (referred to 2004) framework, by means of a realistic measurement model within causal relationships among endogenous and exogenous (investment) HC indicators. Furthermore, the model also specifies a set of (concomitant) indicators that, not belonging to HC investment indicators, have causal impact on endogenous variables and on HC scores, too. Second, we propose a longitudinal analysis (period 2000–2004) aimed to investigate how workers' earned income growth rates vary over workers' educational levels and other personal characteristics. The empirical results of both analyses confirm the characteristics of the Italian job market, denoted by marked inequalities, and knowledge regarding the process of school to work transition, characterized by a weak incidence of education on longitudinal trajectories of earned income.