Agent-based modeling for the study of labor market dynamics

Abstract The advancement of computer science has transformed the study of labor market dynamics, moving it away from traditional equation-based neoclassical theory toward more realistic, agent-based models. Agent-based modeling (ABM)—as a tool for describing complex systems—has become increasingly used in economics and business research, including the labor market. In this paper, we assess the applicability of agent-based modeling and simulation to the study of labor market dynamics, adopting a distinctive approach to the economics literature. We adopt a computer science perspective to evaluate how well existing models satisfy the software requirements of agent-based models. Accordingly, we identify the key components of an ABM and provide a recipe for developing agent-based models in labor market research. We highlight the advantages of ABMs over traditional econometric models and emphasize the practical implications of this bottom-up approach, including increased realism and an improved capacity to assess the effectiveness of economic policy tools.