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IMPLEMENTING STOCHASTIC VOLATILITY IN DSGE MODELS: A COMMENT

Published online by Cambridge University Press:  29 November 2018

Lorenzo Bretscher
Affiliation:
London Business School
Alex Hsu*
Affiliation:
Georgia Institute of Technology
Andrea Tamoni
Affiliation:
London School of Economics and Political Science
*
Address correspondence to: Alex Hsu, Scheller College of Business, Georgia Institute of Technology, USA. e-mail: alex.hsu@scheller.gatech.edu

Abstract

We highlight a state variable misspecification with one accepted method to implement stochastic volatility (SV) in DSGE models when transforming the nonlinear state-innovation dynamics to its linear representation. Although the technique is more efficient numerically, we show that it is not exact but only serves as an approximation when the magnitude of SV is small. Not accounting for this approximation error may induce substantial spurious volatility in macroeconomic series, which could lead to incorrect inference about the performance of the model. We also show that, by simply lagging and expanding the state vector, one can obtain the correct state-space specification. Finally, we validate our augmented implementation approach against an established alternative through numerical simulation.

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Articles
Copyright
© Cambridge University Press 2018

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Footnotes

We would like to thank two anonymous referees and the associate editor for their valuable comments. We are also grateful to Wouter den Haan and Martin Andreasen for helpful discussions.

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