Proxy SVAR Identification of Monetary Policy Shocks – Monte Carlo Evidence and Insights for the US

57 Pages Posted: 15 Dec 2020

See all articles by Helmut Herwartz

Helmut Herwartz

University of Goettingen (Göttingen)

Hannes Rohloff

University of Goettingen (Göttingen)

Shu Wang

Chair of Econometrics, University of Goettingen (Gottingen)

Date Written: October 06, 2020

Abstract

In empirical macroeconomics, proxy structural vector autoregressive models (SVARs) have become a prominent path towards detecting monetary policy (MP) shocks. However, in practice, the merits of proxy SVARs depend on the relevance and exogeneity of the instrumental information employed. Our Monte Carlo analysis sheds light on the performance of proxy SVARs under realistic scenarios of low relative signal strength attached to MP shocks and alternative assumptions on instrument accuracy. In an empirical application with US data we argue in favor of the specific informational content of instruments based on the dynamic stochastic general equilibrium model of Smets and Wouters (2007). A joint assessment of the benchmark proxy SVAR and the outcomes of a structural covariance change model imply that from 1973 until 1979 monetary policy contributed on average between 2.2 and 2.4 units of inflation in the GDP deflator. For the so-called Volcker disinflation starting in 1979Q4, the benchmark structural model shows that the Fed’s policy measures effectively reduced the GDP deflator within three years (i.e. by -3.06 units until 1982Q3). While the empirical analysis largely conditions on a small-dimensional trinity SVAR, the benchmark proxy SVAR shocks remain remarkably robust within a six-dimensional factor-augmented model comprising rich information from Michael McCracken’s database (FRED-QD).

Keywords: Structural Vector Autoregression, External Instruments, Proxy SVAR, Heteroskedasticity, Monetary Policy Shocks

JEL Classification: C15, C32, C36, E47

Suggested Citation

Herwartz, Helmut and Rohloff, Hannes and Wang, Shu, Proxy SVAR Identification of Monetary Policy Shocks – Monte Carlo Evidence and Insights for the US (October 06, 2020). Available at SSRN: https://ssrn.com/abstract=3714542 or http://dx.doi.org/10.2139/ssrn.3714542

Helmut Herwartz

University of Goettingen (Göttingen) ( email )

Platz der Gottinger Sieben 3
Gottingen, D-37073
Germany

Hannes Rohloff

University of Goettingen (Göttingen) ( email )

Platz der Gottinger Sieben 3
Gottingen, D-37073
Germany

Shu Wang (Contact Author)

Chair of Econometrics, University of Goettingen (Gottingen) ( email )

Platz der Gottinger Sieben 3
Humboldtallee 3
Gottingen, D-37073
Germany
+49 (0) 551 - 39 21390 (Phone)

HOME PAGE: http://https://www.uni-goettingen.de/en/629796.html

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