Gamannossi degl’Innocenti, D. and Rablen, M.D. orcid.org/0000-0002-3521-096X (2019) Tax evasion on a social network. Working Paper. Sheffield Economic Research Paper Series (2019005). Department of Economics , University of Sheffield. ISSN 1749-8368
Abstract
We relate tax evasion behavior to a substantial literature on social comparison in judgements. Taxpayers engage in tax evasion as a means to boost their expected consumption relative to others in their social network. The unique Nash equilibrium of the model relates optimal evasion to a (Bonacich) measure of network centrality: more central taxpayers evade more. Given that tax authorities are now investing heavily in big-data tools that aim to construct social networks, we investigate the value of acquiring network information. We do this using networks that allow for celebrity taxpayers, whose consumption is widely seen, and who are systematically of higher wealth. We show that there are pronounced returns to the initial acquisition of network information, albeit targeting audits with highly incomplete knowledge of social networks may be counterproductive.
Metadata
Item Type: | Monograph |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2019 The Author(s). For reuse permissions, please contact the Author(s). |
Keywords: | Tax evasion; Social networks; Network centrality; Optimal auditing; Social comparison; Relative consumption |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Social Sciences (Sheffield) > Department of Economics (Sheffield) > Sheffield Economics Research Papers Series The University of Sheffield > Faculty of Social Sciences (Sheffield) > Department of Economics (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 22 Mar 2019 15:56 |
Last Modified: | 22 Mar 2019 15:56 |
Published Version: | https://www.sheffield.ac.uk/economics/research/ser... |
Status: | Published |
Publisher: | Department of Economics |
Series Name: | Sheffield Economic Research Paper Series |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:144012 |