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Durham Research Online
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Predictive analytics and the targeting of audits.

Hashimzade, N. and Myles, G. D. and Rablen, M. D. (2016) 'Predictive analytics and the targeting of audits.', Journal of economic behavior and organization., 124 . pp. 130-145.

Abstract

The literature on audit strategies has focused on random audits or on audits conditioned only on income declaration. In contrast, tax authorities employ the tools of predictive analytics to identify taxpayers for audit, with a range of variables used for conditioning. The paper explores the compliance and revenue consequences of the use of predictive analytics in an agent-based model that draws upon a behavioral approach to tax compliance. The taxpayers in the model form subjective beliefs about the probability of audit from social interaction, and are guided by a social custom that is developed from meeting other taxpayers. The belief and social custom feed into the occupational choice between employment and two forms of self-employment. It is shown that the use of predictive analytics yields a significant increase in revenue over a random audit strategy.

Item Type:Article
Keywords:Tax compliance, Social network, Agent-based model.
Full text:(AM) Accepted Manuscript
Available under License - Creative Commons Attribution Non-commercial No Derivatives.
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Status:Peer-reviewed
Publisher Web site:http://dx.doi.org/10.1016/j.jebo.2015.11.009
Publisher statement:© 2015 This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/
Date accepted:19 November 2015
Date deposited:23 November 2015
Date of first online publication:08 December 2015
Date first made open access:08 June 2017

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