Search In Artificial Labour Markets: A Simulation Study

Job search theory involves perfectly rational, maximising actors which make decisions under imperfect information. In the paper we simulate a labour market which works differently: heterogeneous firms and workers interact following rules that place only bounded demands on their computational capacities. We model an adaptive sequential search process in which workers canvass firms. Contrarily to traditional search models, the worker reservation wage is not the optimal one, but it is determined according to individual features such as wealth and skills. Similarly to the simplest search models, search costs are constant and expressed by unit of search. As for firms, we assume that enterprises which require a more educated labour force are willing to pay higher wages and that more skilled workers have higher reservation wage. This allows us to analyse jointly the process of search and the possibility of skill mismatch phenomena. We analyse departures from traditional GE models by means of two versions of the model. In the first one, agents have infinite life, whereas, in the second one, there are demographic and aging processes which affect internal states and decision making of agents. In both versions, we devise various educational and training policies to assess the effect training and formal education on the labour market setting. We stress the relevance of heterogeneity, demography, formal education, and training on the job in determining employment, activity rate, wage, and skill mismatch phenomena by comparing the ACE model with a more traditional general equilibrium model. Results are interesting from both the theoretical and the empirical point of view.