Leighton Vaughan Williams
Taxing Gambling Machines to Enhance Tourism
Vaughan Williams, Leighton; Garrett, Thomas A.; Paton, David
Authors
Thomas A. Garrett
Professor DAVID PATON DAVID.PATON@NOTTINGHAM.AC.UK
PROFESSOR OF INDUSTRIAL ECONOMICS
Abstract
Gambling machines are a key component of global gambling tourism. The taxation of these machines is a highly controversial area of policy debate involving tensions between industry profitability, economic growth and government revenue. We present the background and context to the debate around the optimal taxation of gambling machines, and reach conclusions and recommendations based on the recent and extended literature as to the best way to tax gambling machines in order to enhance gambling tourism. These recommendations provide guidance for jurisdictions in which gambling tourism is a significant actual or potential source of public revenue.
Citation
Vaughan Williams, L., Garrett, T. A., & Paton, D. (2020). Taxing Gambling Machines to Enhance Tourism. Journal of Gambling Business and Economics, 13(2), 83-90. https://doi.org/10.5750/jgbe.v13i2.1870
Journal Article Type | Article |
---|---|
Acceptance Date | Dec 11, 2020 |
Online Publication Date | Dec 11, 2020 |
Publication Date | 2020 |
Deposit Date | Dec 16, 2020 |
Journal | Journal of Gambling Business and Economics |
Print ISSN | 1751-7990 |
Electronic ISSN | 1751-8008 |
Publisher | University of Buckingham Press |
Peer Reviewed | Not Peer Reviewed |
Volume | 13 |
Issue | 2 |
Pages | 83-90 |
DOI | https://doi.org/10.5750/jgbe.v13i2.1870 |
Public URL | https://nottingham-repository.worktribe.com/output/5152362 |
Publisher URL | http://www.ubplj.org/index.php/jgbe/article/view/1870 |
You might also like
Law, Ethics and Lockdowns: impacts on life, liberty and the economy
(2023)
Journal Article
Financial transaction taxes and market structure: lessons from the gambling industry
(2022)
Journal Article
Downloadable Citations
About Repository@Nottingham
Administrator e-mail: discovery-access-systems@nottingham.ac.uk
This application uses the following open-source libraries:
SheetJS Community Edition
Apache License Version 2.0 (http://www.apache.org/licenses/)
PDF.js
Apache License Version 2.0 (http://www.apache.org/licenses/)
Font Awesome
SIL OFL 1.1 (http://scripts.sil.org/OFL)
MIT License (http://opensource.org/licenses/mit-license.html)
CC BY 3.0 ( http://creativecommons.org/licenses/by/3.0/)
Powered by Worktribe © 2025
Advanced Search