Compliance effects of risk-based tax audits
Gaute Torsvik,
Oddbjørn Raaum,
Knut Løyland and
Arnstein Øvrum
No 6u3ns, OSF Preprints from Center for Open Science
Abstract:
Tax administrations use machine learning to predict risk scores as a basis for selecting individual taxpayers for audit. Audits detect noncompliance immediately, but may also alter future filing behavior. This analysis is the first to estimate compliance effects of audits among high-risk wage earners. We exploit a sharp audit assignment discontinuity in Norway based on individual tax payers risk score. Additional data from a random audit allow us to estimate how the audit effect vary across the risk score distribution. We show that the current risk score audit threshold is set far above the one that maximizes net public revenue.
Date: 2019-04-12
New Economics Papers: this item is included in nep-acc, nep-iue, nep-pbe and nep-rmg
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)
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https://osf.io/download/5cb03626353c58001b99442c/
Related works:
Working Paper: Compliance effects of risk-based tax audits (2019) 
Working Paper: Compliance effects of risk-based tax audits (2019) 
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Persistent link: https://EconPapers.repec.org/RePEc:osf:osfxxx:6u3ns
DOI: 10.31219/osf.io/6u3ns
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