Is Volatility Good for Growth? Evidence from the G7

52 Pages Posted: 8 Jan 2013 Last revised: 24 Jan 2014

See all articles by Elena Andreou

Elena Andreou

University of Cyprus - Department of Economics

Alessandra Pelloni

University of Rome II, Department of Economics

Marianne Sensier

University of Manchester

Multiple version iconThere are 2 versions of this paper

Date Written: January 8, 2013

Abstract

We provide empirical support for an analytical DSGE model with nominal wage stickiness where growth is driven by learning-by-doing and money shocks and their variance are allowed to impact on long-run output growth. In our theoretical model the variance of monetary shocks has a negative effect on growth, while output volatility is good for growth as a positive relationship exists. Using a bivariate GARCH-M model we test the empirical conditional mean and variance relationships of nominal money and production growth rates in the G7 countries. We corroborate the theoretical model predictions with evidence from Bonferroni multiple tests across the G7.

Keywords: growth uncertainty, learning-by-doing, monetary uncertainty, multivariate GARCH-in-mean, nominal rigidity

JEL Classification: C32, E32, O42

Suggested Citation

Andreou, Elena and Pelloni, Alessandra and Sensier, Marianne, Is Volatility Good for Growth? Evidence from the G7 (January 8, 2013). CEIS Working Paper No. 258, Available at SSRN: https://ssrn.com/abstract=2197720 or http://dx.doi.org/10.2139/ssrn.2197720

Elena Andreou

University of Cyprus - Department of Economics ( email )

75 Kallipoleos Street
P.O. Box 20537
1678 Nicosia
Cyprus
+357 2 892449 (Phone)
+357 2 892432 (Fax)

Alessandra Pelloni (Contact Author)

University of Rome II, Department of Economics ( email )

Via Columbia n.2
Rome, rome 00100
Italy
390672595908 (Phone)

Marianne Sensier

University of Manchester ( email )

Economics, Arthur Lewis Building
Oxford Road
Manchester, M13 9PL
United Kingdom

HOME PAGE: http://www.socialsciences.manchester.ac.uk/disciplines/economics/about/staff/sensier/

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