Fiscal Prudence: It’s All in the Timing – Estimating Time-Varying Fiscal Policy Reaction Functions for Core EU Countries

36 Pages Posted: 8 Apr 2021

See all articles by Tino Berger

Tino Berger

University of Goettingen (Göttingen) - Department of Economics

Tore Dubbert

University of Münster

Ruben Schoonackers

Nationale Bank van België

Date Written: March 23, 2021

Abstract

When estimating fiscal policy reaction functions (FRF), the literature has well recognized the importance of non-linearities. However, there is yet very little attempt to formally test for the presence and potential sources of a non-linear fiscal responsiveness. In this paper we address this gap by formally adressing model specification of the FRF in a panel of five EU countries. Employing a Bayesian stochastic model specification search algorithm, we provide formal evidence for time-varying fiscal prudence over the last 50 years. The primary balance responsiveness exhibits smooth but significant variation over time and thus confirms the necessity of a non-linear model. Moreover, the extended results show that dynamics can be partially linked to the interest rate growth differential and the level of public debt itself. However, no clear evidence is found in favor of the fiscal fatigue proposition.

Suggested Citation

Berger, Tino and Dubbert, Tore and Schoonackers, Ruben, Fiscal Prudence: It’s All in the Timing – Estimating Time-Varying Fiscal Policy Reaction Functions for Core EU Countries (March 23, 2021). Available at SSRN: https://ssrn.com/abstract=3810841 or http://dx.doi.org/10.2139/ssrn.3810841

Tino Berger (Contact Author)

University of Goettingen (Göttingen) - Department of Economics ( email )

Platz der Goettinger Sieben 3
Goettingen, 37073
Germany

Tore Dubbert

University of Münster ( email )

Schlossplatz 2
Muenster, D-48149
Germany

Ruben Schoonackers

Nationale Bank van België ( email )

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Downloads
100
Abstract Views
424
Rank
510,279
PlumX Metrics