Attention Variation and Welfare: Theory and Evidence from a Tax Salience Experiment∗

A rapidly growing literature shows that consumers can be inattentive to complex or notfully-salient financial incentives. This literature typically estimates “the average mistake,” and uses representative agent models to analyze the economic implications. This paper shows, theoretically and empirically, that accounting for heterogeneity in mistakes is crucial in positive and normative analysis. Focusing on consumer underreaction to not-fully-salient sales taxes, we show theoretically that 1) individual differences in underreaction generate inefficiency in the resulting allocation of the taxed good, 2) the variation of underreaction across the income distribution affects the regressivity of the tax burden, and 3) the variation of underreaction across different tax rates affects the distortions to demand resulting from tax changes. To empirically assess the importance of these issues, we implement an online shopping experiment in which 3000 consumers—matching the U.S. adult population on key demographics—purchase common household products, facing tax rates that vary in size and salience. We find that: 1) there are significant individual differences in underreaction to taxes. Accounting for this heterogeneity increases the efficiency cost of taxation estimates by at least 200%, as compared to estimates generated from a representative agent model. 2) High income earners are less likely to underreact to taxes than low income earners, and thus the financial burden of misoptimization falls disproportionately on the poor. 3) Tripling existing sales tax rates roughly doubles consumers’ attention to taxes, which implies that raising taxes increases deadweight loss through an additional “debiasing channel.” Our results provide new insights into the mechanisms and determinants of boundedly rational processing of not-fully-salient incentives, and our general approach provides a framework for robust behavioral welfare analysis in other domains. ∗We thank Hunt Allcott, Eduardo Azevedo, Doug Bernheim, Raj Chetty, Stefano DellaVigna, Emmanuel Farhi, Xavier Gabaix, Jacob Goldin, Tatiana Homonoff, Shachar Kariv, Supreet Kaur, Judd Kessler, David Laibson, Matthew Rabin, Emmanuel Saez, Andrei Shleifer, Jeremy Tobacman, Glen Weyl, Michael Woodford, Danny Yagan, and audiences at Berkeley, Carnegie Mellon SDS, CESifo Behavioral Economics Meeting, Cornell, Haas (marketing), Harvard, Stanford, and Wharton for helpful comments and suggestions. We thank James Perkins at ClearVoice research for help in managing the data collection, Jessica Holevar for able research assistance, and Sargent Shriver and Vincent Conley for technical support. For financial support, we are grateful to the Lab for Economic Applications and Policy (LEAP), the Pension Research Council/Boettner Center for Pension and Retirement Research, the Russell Sage Foundation (small grants program), and the Wharton Dean’s Research Fund. The opinions expressed in this paper are solely the authors’, and do not necessarily reflect the views of any individual or institution listed above. †Corresponding and first author. Email: [email protected]