Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/202247
Authors: 
d'Andria, Diego
Year of Publication: 
2017
Series/Report no.: 
JRC Working Papers on Taxation and Structural Reforms 01/2017
Abstract: 
We study a market with entrepreneurial and workers 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 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 set of assumptions affects 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 a subsidy-only policy can be optimal as the detrimental effects of excessive entrepreneurial entry are (partly or totally) compensated by surplus-increasing faster learning.
Subjects: 
Entrepreneurship
Taxation
Asymmetric Information
Learning
Adverse Selection
Agent-Based Computational Model
JEL: 
D82
D83
G14
H25
Document Type: 
Working Paper

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