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Using the 'Smart Return' to Reduce Tax Evasion

23 Pages Posted: 16 Mar 2015  

Joseph Bankman

Stanford Law School

Clifford Nass

Stanford University

Joel B. Slemrod

University of Michigan, Stephen M. Ross School of Business; National Bureau of Economic Research (NBER)

Date Written: March 14, 2015

Abstract

Tax evasion costs government over 400 billion dollars a year. We suggest enforcement efforts can be strengthened by redesigning the tax return to take advantage of social psychology research, and industry experience with data-driven systems. To illustrate the potential of this approach, in this paper we propose three categories of changes that merit testing through pilot studies. The first involves changing the wording on existing returns to increase the psychological cost of evasion and increase the perceived expectation of detection. The second builds appeals to morality in the return itself through the use of a short phrase containing a "self-relevant" noun. The third uses on-line "conversational agents" to ask adaptive questions.

Keywords: tax evasion, tax evasion costs, tax returns, government, social psychology research, data-driven systems, merit testing, pilot studies, tax return wording, psychological cost of tax evasion, perceived expectation of detection, morality, self-relevant noun, on-line conversational agents, adaptive que

JEL Classification: H02, H26, K34, K42

Suggested Citation

Bankman, Joseph and Nass, Clifford and Slemrod, Joel B., Using the 'Smart Return' to Reduce Tax Evasion (March 14, 2015). Stanford Public Law Working Paper No. 2578432. Available at SSRN: https://ssrn.com/abstract=2578432 or http://dx.doi.org/10.2139/ssrn.2578432

Joseph Bankman (Contact Author)

Stanford Law School ( email )

559 Nathan Abbott Way
Stanford, CA 94305-8610
United States
650-725-3825 (Phone)
650-725-7663 (Fax)

Clifford I Nass

Stanford University ( email )

Stanford, CA 94305
United States

Joel B. Slemrod

University of Michigan, Stephen M. Ross School of Business ( email )

701 Tappan Street
Room R5396
Ann Arbor, MI 48109-1234
United States
734-936-3914 (Phone)
734-763-4032 (Fax)

National Bureau of Economic Research (NBER)

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

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