Using the 'Smart Return' to Reduce Tax Evasion

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