Hashimzade, N. and Myles, G. (2017) 'Risk-based audits in a behavioural model.', Public finance review., 45 (1). pp. 140-165.
The tools of predictive analytics are widely used in the analysis of large data sets to predict future patterns in the system. In particular, predictive analytics is used to estimate risk of engaging in certain behavior. Risk-based audits are used by revenue services to target potentially noncompliant taxpayers, but the results of predictive analytics serve predominantly only as a guide rather than a rule. “Auditor judgment” retains an important role in selecting audit targets. This article assesses the effectiveness of using predictive analytics in a model of the compliance decision that incorporates several components from behavioral economics: subjective beliefs about audit probabilities, a social custom reward from honest tax payment, and a degree of risk aversion that increases with age. Simulation analysis shows that predictive analytics are successful in raising compliance and that the resulting pattern of audits is very close to being a cutoff rule.
|Keywords:||Tax compliance, Audits, Behavioral.|
|Full text:||(AM) Accepted Manuscript|
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|Publisher Web site:||https://doi.org/10.1177/1091142115602062|
|Publisher statement:||Hashimzade, N. and Myles, G. (2017) 'Risk-based audits in a behavioural model.', Public finance review., 45 (1). pp. 140-165. Copyright © 2015 The Author(s). Reprinted by permission of SAGE Publications.|
|Record Created:||20 Jul 2015 11:20|
|Last Modified:||20 Apr 2018 10:15|
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