Simulation Evidence on Theory‐Based and Statistical Identification Under Volatility Breaks

19 Pages Posted: 20 Jan 2016

See all articles by Helmut Herwartz

Helmut Herwartz

University of Goettingen (Gottingen)

Martin Plödt

Kiel Institute for the World Economy

Date Written: February 2016

Abstract

Beside a priori theoretical assumptions on instantaneous or long‐run effects of structural shocks, sign restrictions have become a prominent means for structural vector autoregressive (SVAR) analysis. Moreover, changes in second order moments of systems of time series can be fruitfully exploited for identification purposes in SVARs. By means of Monte Carlo studies, we examine to what degree theory‐based and statistical identification approaches offer an accurate quantification of the true structural relations in a standard model for monetary policy analysis. Subsequently, we discuss how identifying information from theory‐based and statistical approaches can be combined on the basis of a low‐dimensional empirical model of US monetary policy.

Suggested Citation

Herwartz, Helmut and Plödt, Martin, Simulation Evidence on Theory‐Based and Statistical Identification Under Volatility Breaks (February 2016). Oxford Bulletin of Economics and Statistics, Vol. 78, Issue 1, pp. 94-112, 2016. Available at SSRN: https://ssrn.com/abstract=2718673 or http://dx.doi.org/10.1111/obes.12098

Helmut Herwartz (Contact Author)

University of Goettingen (Gottingen) ( email )

Platz der Gottinger Sieben 3
Gottingen, D-37073
Germany

Martin Plödt

Kiel Institute for the World Economy ( email )

P.O. Box 4309
Kiel, Schleswig-Hosltein D-24100
Germany

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