Tax policy and entrepreneurial entry with information asymmetry and learning

摘要

We study a market with entrepreneurial and worker entry where both entrepreneurs' abilities and workers' qualities are private information. We develop an agent-based computable model to mimic the mechanisms described in a previous analytical model (Boadway and Sato in Int Tax Public Finance 18(2):166-192, 2011). Then, we introduce the possibility that agents may learn over time about abilities and qualities of other agents, by means of Bayesian inference over informative signals. We show how such different assumptions affect the optimality of second-best tax and subsidy policies. While with no information, it is optimal to have a subsidy to labour and a simultaneous tax on entrepreneurs to curb excessive entry, with learning the detrimental effects of excessive entry are partly compensated by surplus-increasing faster learning.