Compliance effects of risk-based tax audits

Knut Løyland, Oddbjørn Raaum, Gaute Torsvik and Arnstein Øvrum

No 7616, CESifo Working Paper Series from CESifo

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.

Keywords: tax audits; tax revenue; tax reporting decisions; income tax; machine learning; risk; profiling (search for similar items in EconPapers)
JEL-codes: D04 H26 H83 (search for similar items in EconPapers)
Date: 2019
New Economics Papers: this item is included in nep-acc, nep-big, nep-iue, nep-law, nep-pbe and nep-pub
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

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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:ces:ceswps:_7616

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