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On the Marginal Excess Burden of Taxation in an Overlapping Generations Model

Chung Tran and Sebastian Wende

ANU Working Papers in Economics and Econometrics from Australian National University, College of Business and Economics, School of Economics

Abstract: We quantify marginal excess burden, defined as the change in deadweight loss for an additional dollar of tax revenue, for different taxes. We use a dynamic general equilibrium, overlapping generations model featured with heterogeneous agents and a realistic structure of corporate finance and taxes. Our main results, based on an economy calibrated to Australian data, indicate that company taxes are more distorting than personal income and consumption taxes. Specifically, the marginal excess burden for the company income tax is 83 cents per dollar of tax revenue raised, compared to 34 cents and 24 cents for the personal income and consumption taxes, respectively. A broader analysis of more tax instruments confrim that the relatively larger excess burden of company taxes ultimately falls on households. Importantly, the marginal excess burden is distributed unevenly across skill types, generations and ages. This highlights political challenges when obtaining popular support for raising taxes. Hence, our analysis demonstrates that marginal excess burden can be an useful tool for evaluating both eciency and distributional implications of a tax increase at the margin.

Keywords: Taxation; scal distortion; overlapping generations; skill hetero-geneity; corporate nance; deadweight loss; dynamic general equilibrium; welfare (search for similar items in EconPapers)
JEL-codes: E62 H21 H22 H24 H25 (search for similar items in EconPapers)
Date: 2017-09
New Economics Papers: this item is included in nep-dge, nep-mac, nep-pbe and nep-pub
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (9)

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Journal Article: On the marginal excess burden of taxation in an overlapping generations model (2021) Downloads
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