A Big Data Approach to Optimal Sales Taxation

44 Pages Posted: 19 May 2014 Last revised: 3 Jul 2023

See all articles by Christian Baker

Christian Baker

affiliation not provided to SSRN

Jeremiah Bejarano

Office of Financial Research, U.S. Department of the Treasury

Richard W. Evans

University of Chicago, Becker Friedman Institute and M.A. Program in Computational Social Science

Kenneth L. Judd

Stanford University - The Hoover Institution on War, Revolution and Peace; Center for Robust Decisionmaking on Climate & Energy Policy (RDCEP); National Bureau of Economic Research (NBER)

Kerk Phillips

Brigham Young University - Department of Economics; Government of the United States of America - Congressional Budget Office (CBO)

Date Written: May 2014

Abstract

We characterize and demonstrate a solution method for an optimal commodity (sales) tax problem consisting of multiple goods, heterogeneous agents, and a nonconvex policy maker optimization problem. Our approach allows for more dimensions of heterogeneity than has been previously possible, incorporates potential model uncertainty and policy objective uncertainty, and relaxes some of the assumptions in the previous literature that were necessary to generate a convex optimization problem for the policy maker. Our solution technique involves creating a large database of optimal responses by different individuals for different policy parameters and using "Big Data" techniques to compute policy maker objective values over these individuals. We calibrate our model to the United States and test the effects of a differentiated optimal commodity tax versus a flat tax and the effect of exempting a broad class of goods (services) from commodity taxation. We find that only a potentially small amount of tax revenue is lost for a given societal welfare level by departing from an optimal differentiated sales tax schedule to a uniform flat tax and that there is only a small loss in revenue from exempting a class of goods such as services in the United States.

Suggested Citation

Baker, Christian and Bejarano, Jeremiah and Evans, Richard William and Judd, Kenneth L. and Phillips, Kerk L and Phillips, Kerk L, A Big Data Approach to Optimal Sales Taxation (May 2014). NBER Working Paper No. w20130, Available at SSRN: https://ssrn.com/abstract=2438551

Christian Baker (Contact Author)

affiliation not provided to SSRN

Jeremiah Bejarano

Office of Financial Research, U.S. Department of the Treasury ( email )

717 14th Street, NW
Washington DC, DC 20005
United States

HOME PAGE: http://bit.ly/44JWBu8

Richard William Evans

University of Chicago, Becker Friedman Institute and M.A. Program in Computational Social Science ( email )

Chicago, IL 60637
United States

HOME PAGE: http://https://sites.google.com/site/rickecon/

Kenneth L. Judd

Stanford University - The Hoover Institution on War, Revolution and Peace ( email )

Stanford, CA 94305-6010
United States

Center for Robust Decisionmaking on Climate & Energy Policy (RDCEP) ( email )

5735 S. Ellis Street
Chicago, IL 60637
United States

National Bureau of Economic Research (NBER) ( email )

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

Kerk L Phillips

Brigham Young University - Department of Economics ( email )

166 Faculty Office Bldg.
Provo, UT 84602-2363
United States
801-422-5928 (Phone)

HOME PAGE: http://sites.google.com/site/kerkphillips

Government of the United States of America - Congressional Budget Office (CBO) ( email )

Ford House Office Building
2nd & D Streets, SW
Washington, DC 20515-6925
United States

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