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dc.contributor.authorD'ANDRIA DIEGOen_GB
dc.date.accessioned2019-09-11T00:26:11Z-
dc.date.available2019-09-10en_GB
dc.date.available2019-09-11T00:26:11Z-
dc.date.created2019-04-29en_GB
dc.date.issued2019en_GB
dc.date.submitted2019-04-08en_GB
dc.identifier.citationINTERNATIONAL TAX AND PUBLIC FINANCE vol. 26 no. 5 p. 1211-1229en_GB
dc.identifier.issn0927-5940 (online)en_GB
dc.identifier.urihttps://link.springer.com/article/10.1007%2Fs10797-019-09540-1en_GB
dc.identifier.urihttp://publications.jrc.ec.europa.eu/repository/handle/JRC116411-
dc.description.abstractWe 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 the detrimental effects of excessive entry are partly compensated by surplus-increasing faster learning.en_GB
dc.description.sponsorshipJRC.B.2-Fiscal Policy Analysisen_GB
dc.format.mediumOnlineen_GB
dc.languageENGen_GB
dc.publisherSPRINGERen_GB
dc.relation.ispartofseriesJRC116411en_GB
dc.titleTax policy and entrepreneurial entry with information asymmetry and learningen_GB
dc.typeArticles in periodicals and booksen_GB
dc.identifier.doi10.1007/s10797-019-09540-1 (online)en_GB
JRC Directorate:Growth and Innovation

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