Predictive analytics and the targeting of audits

Nigar Hashimzade, Gareth Myles (profgarethdmyles@yahoo.com) and Matthew Rablen

Journal of Economic Behavior & Organization, 2016, vol. 124, issue C, 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.

Keywords: Tax compliance; Social network; Agent-based model (search for similar items in EconPapers)
JEL-codes: D85 H26 (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (13)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:jeborg:v:124:y:2016:i:c:p:130-145

DOI: 10.1016/j.jebo.2015.11.009

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