Toward a Perspective-Dependent Theory of Audit Probability for Tax Compliance Models

24 Pages Posted: 12 Dec 2013 Last revised: 6 May 2018

See all articles by Jack Manhire

Jack Manhire

Texas A&M University School of Innovation; Bush School of Government & Public Service

Date Written: April 18, 2014

Abstract

The classic deterrence theory model of income tax evasion first articulated in 1972 has met significant criticism because it does not comport with the observed rate of tax compliance. This article argues that the classic expected utility model and its various progeny, including nonexpected utility models, employ too general a notion of taxpayers’ probability of audit by equating the latter to the frequency with which the government audits tax returns. Given that audit probabilities vary significantly based on whether taxpayers underreport tax on their returns, these models should be revised to reflect the conditional nature of audit probability from the taxpayers’ perspective. If one applies this perspective-dependent definition of audit probability to both expected and nonexpected utility models, the theoretical results will more closely reflect the observed rate of tax compliance.

Keywords: tax evasion, tax compliance, audit probability, tax salience, taxpayer perception, heuristics

JEL Classification: C11, C51, C54, H26, K34, K42, P16, Z18

Suggested Citation

Manhire, Jack, Toward a Perspective-Dependent Theory of Audit Probability for Tax Compliance Models (April 18, 2014). 33 Virginia Tax Review 629 (2014). Available at SSRN: https://ssrn.com/abstract=2366325 or http://dx.doi.org/10.2139/ssrn.2366325

Jack Manhire (Contact Author)

Texas A&M University School of Innovation

1249 TAMU
College Station, TX 77843-1249
United States

Bush School of Government & Public Service ( email )

4220 TAMU
College Station, TX 76845
United States

Register to save articles to
your library

Register

Paper statistics

Downloads
424
rank
66,608
Abstract Views
1,361
PlumX Metrics
!

Under construction: SSRN citations will be offline until July when we will launch a brand new and improved citations service, check here for more details.

For more information