LOST in America: Evidence on Local Sales Taxes from National Panel Data

57 Pages Posted: 10 Nov 2013 Last revised: 8 Oct 2014

David R. Agrawal

University of Kentucky - James W. Martin School of Public Policy and Administration; University of Kentucky - Department of Economics; CESifo (Center for Economic Studies and Ifo Institute)

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Date Written: September 1, 2014

Abstract

This paper studies comprehensive national panel data of local option sales taxes at the monthly frequency. I calculate state-by-month population weighted averages and standard deviations of local sales tax rates. I document ten stylized facts concerning the time series patterns and spatial dynamics of local sales tax rates. The paper then proposes a “tax system” approach to tax competition where states compete on a variety of margins -- including restrictions on localities' tax setting authority -- that are often ignored by the standard focus on tax rates. Using spatial panel data techniques and the state-by-month population weighted averages, I find a significant association between one state's tax system and its neighboring states' tax systems.

Keywords: Commodity Taxation, Local Public Finance, Fiscal Federalism, Spatial Tax Competition

JEL Classification: H20, H71, H77, R50, L81

Suggested Citation

Agrawal, David R., LOST in America: Evidence on Local Sales Taxes from National Panel Data (September 1, 2014). Available at SSRN: https://ssrn.com/abstract=2352000 or http://dx.doi.org/10.2139/ssrn.2352000

David Robert Agrawal (Contact Author)

University of Kentucky - James W. Martin School of Public Policy and Administration ( email )

433 Patterson Office Tower
Lexington, KY 40506-0027
United States
859-257-8608 (Phone)

HOME PAGE: http://www.uky.edu/~drag222/

University of Kentucky - Department of Economics ( email )

Lexington, KY 40506
United States

HOME PAGE: http://www.uky.edu/~drag222/

CESifo (Center for Economic Studies and Ifo Institute) ( email )

Poschinger Str. 5
Munich, DE-81679
Germany

HOME PAGE: http://www.uky.edu/~drag222/

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