Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/202247 
Autor:innen: 
Erscheinungsjahr: 
2017
Schriftenreihe/Nr.: 
JRC Working Papers on Taxation and Structural Reforms No. 01/2017
Verlag: 
European Commission, Joint Research Centre (JRC), Seville
Zusammenfassung: 
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.
Schlagwörter: 
Entrepreneurship
Taxation
Asymmetric Information
Learning
Adverse Selection
Agent-Based Computational Model
JEL: 
D82
D83
G14
H25
Dokumentart: 
Working Paper

Datei(en):
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