Tax burden distribution and GDP growth: Non-linear causality considerations in the USA

Abstract

The objective of the study is to investigate for non-linear causality running from a set of alternative tax burden ratios — i.e. total tax burden, tax burden on production and imports, tax burden on personal income and, tax burden on corporate income — to per capita GDP growth. The study employs tax revenues and GDP U.S. government data for the period 1948:1–2008:4 in two non-linear causality tests, developed by Hiemstra and Jones (1994) and Diks and Panchenko (2006). Using the two alternative tests serves the need for evaluating the role of heteroskedasticity as a non-linear causality-affecting factor. In a fiscal policy framework, the study explores the GDP growth influential role of the tax burden distribution across tax-liable groups in a country's economy. The empirical findings provide two discrete policy considerations. First, when the policy challenge is to influence the GDP growth by means of taxation, this should be preferably attempted by adjusting the taxes levied on production and imports or, on corporate income. On the contrary, when stability in GDP growth is required, while a change in the tax policy is attempted, this should be preferably restricted in the field of the personal income taxation.