Learning through Transient Matching in Congested Markets

Explore a Google TechTalk presented by Andrew Ferdowsian on transient matching in congested markets where workers learn preferences through experience. Delve into a framework examining decentralized markets with capacity-constrained firms and workers facing multi-armed bandit problems. Discover how market competition influences search patterns, matching stylized facts from labor market data. Analyze the inefficiencies in equilibria due to competition depressing search levels. Evaluate the effectiveness of interventions aimed at improving efficiency in both congested and uncongested markets. Examine the impact of headhunters on worker outcomes and overall efficiency. Investigate the potential effects of unemployment benefits on search behavior and match efficiency. Gain insights from Ferdowsian's research on improving marketplaces, including public housing in Singapore and the medical resident labor market.

Learning through Transient Matching in Congested Markets