Structure, Behavior, and Market Power in an Evolutionary Labor Market with Adaptive Search

This study uses an agent-based computational labor market framework to undertake a systematic experimental investigation of the relationship between market structure and market power. Market structure is measured in terms of job capacity (total potential job openings to total potential work offers) and job concentration (total number of workers to total number of employers). For each tested market structure, workers and employers repeatedly seek preferred worksite partners based on continually updated expected utility, engage in efficiency-wage worksite interactions modelled as prisoner's dilemma games, and evolve their worksite behaviors over time. A key finding is the presence of strong learning and network effects. Each tested market structure maps into a "spectral" distribution of observed interaction networks exhibiting one dominant attractor (frequent network pattern) with one or two weaker attractors (less frequent network patterns). Market structure is strongly predictive for the relative market power of workers and employers across all network attractors, but the magnitudes of the market power levels attained by workers and employers vary widely across the network attractors