Modeling Skills Mismatch in the Labor Market Using an Agent-Based Approach

In this study, we propose an agent-based model to analyze the process of skills matching in the labor market, treated as a complex adaptive system, in which individuals adjust their behavior and level of competence through learning mechanisms and interaction with training providers. The model integrates two main types of agents: employed or job-seeking individuals and skills providers. It describes individual skills through a multidimensional vector, calibrated based on empirical data from a questionnaire. Thus, three categories of scenarios are analyzed: (i) variations in the demand for skills in the labor market, (ii) increased efficiency of university-type providers and (iii) increased efficiency of training center-type providers. The results highlight the fact that an increase in the demand for skills, in the absence of effective training mechanisms, leads to a significant extension of the time needed to reach equilibrium in the labor market. On the other hand, improving the efficiency of skills providers accelerates the matching process, with stronger effects in the case of training centers, due to their orientation towards specific skills required by employers. The conclusions underline the importance of approaching the labor market as a complex adaptive system and highlight the need to correlate labor demand stimulation policies with strategic investments in education and vocational training.