Tax policy and entrepreneurial entry with information asymmetry and learning

Diego d’Andria ()
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Diego d’Andria: European Commission Joint Research Centre (JRC), Unit B2 Fiscal Policy Analysis
Authors registered in the RePEc Author Service: Diego d'Andria

International Tax and Public Finance, 2019, vol. 26, issue 5, No 9, 1229 pages

Abstract: Abstract 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.

Keywords: Entrepreneurship; Taxation; Asymmetric information; Learning; Adverse selection; Agent-based computational model (search for similar items in EconPapers)
JEL-codes: D82 D83 G14 H25 (search for similar items in EconPapers)
Date: 2019
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Working Paper: Tax policy and entrepreneurial entry with information asymmetry and learning (2017)
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DOI: 10.1007/s10797-019-09540-1

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