Citations (17)



Thinking about Tax

Edward J. McCaffery

USC Gould School of Law

Jonathan Baron

University of Pennsylvania - Department of Psychology

July 16, 2004

USC Law School, Olin Research Paper No. 04-13; and USC CLEO Research Paper No. C04-10

Behavioral economics and cognitive psychology have demonstrated that people deviate from ideal precepts of rationality in many settings, showing inconsistent judgment in the face of framing and other formal manipulations of the presentation of problems. This article summarizes the finding of original experiments about subjects' perceptions of aspects of tax-law design and argues for the relevance of behavioral perspectives to the understanding and improvement of real-world fiscal systems. We show that in evaluating tax systems, subjects are vulnerable to a wide range of heuristics and biases, leading to inconsistent judgment and evaluation. The prevalence of these biases suggests that there is room for skillful politicians to manipulate public opinion, and that tax-system design can be volatile on account of the possibility of eliciting preference reversals through purely formal rhetorical means. More troubling, the findings suggest a likely and persistent wedge between observed and optimal public finance systems.

Number of Pages in PDF File: 40

JEL Classification: A12, H20

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Date posted: July 23, 2004  

Suggested Citation

McCaffery, Edward J. and Baron, Jonathan, Thinking about Tax (July 16, 2004). USC Law School, Olin Research Paper No. 04-13; and USC CLEO Research Paper No. C04-10. Available at SSRN: http://ssrn.com/abstract=567767 or http://dx.doi.org/10.2139/ssrn.567767

Contact Information

Edward J. McCaffery (Contact Author)
USC Gould School of Law ( email )
699 Exposition Boulevard
Los Angeles, CA 90089
United States
213-740-2567 (Phone)
213-740-5502 (Fax)

Jonathan Baron
University of Pennsylvania - Department of Psychology ( email )
3815 Walnut Street
Philadelphia, PA 19104-6196
United States
215-898-6918 (Phone)
HOME PAGE: http://www.sas.upenn.edu/~baron
Feedback to SSRN

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