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TRACING THE ROLE OF FORESIGHT IN THE EFFECTS OF U.S. TAX POLICY: EVIDENCE FROM A TIME-VARYING STRUCTURAL VECTOR AUTOREGRESSION

Published online by Cambridge University Press:  19 October 2016

T. Philipp Dybowski
T. Philipp Dybowski*
Affiliation:
University of Muenster
*
Address correspondence to: T. Philipp Dybowski, University of Muenster, Universitaetstrasse 14–16, 48143 Muenster, Germany; e-mail: philipp.dybowski@wiwi.uni-muenster.de.
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Abstract

Recent empirical research stresses the importance of foresight in tax policy analyses, because failing to model foresight adequately leads to two types of biases: a bias that relates to a mismatch of information sets in the presence of foresight, and one that arises when time variation in foresight is ignored. This paper incorporates tax foresight into a framework of time-varying structural vector autoregression models with stochastic volatility to account for both types of biases. This reveals the effects of changing degrees of tax foresight on U.S. tax policy. Two findings stand out: First, anticipated and unanticipated tax shocks show considerable time variations, suggesting that some tax reforms were more anticipated than others. Second, the time-varying bias reveals that tax foresight was higher during the 1980s and 1990s than during the 1960s and 1970s. The results compare well with the literature and find support in documented U.S. tax episodes.

Keywords

Fiscal MultiplierTax ExpectationsIdentified Vector AutoregressionsBayesian Estimation
Type
Articles
Information
Macroeconomic Dynamics , Volume 22 , Issue 4 , June 2018 , pp. 754 - 778
Copyright
Copyright © Cambridge University Press 2016 

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Footnotes

I thank Bernd Kempa, Philipp Adämmer, Jana Riedel, Samad Sarferaz, and one anonymous referee for helpful comments on earlier versions of this paper.

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