Robust inference intime-varying structural VAR models: The DC-Cholesky multivariate stochasticvolatility model

Benny Hartwig

No 34/2020, Discussion Papers from Deutsche Bundesbank

Abstract: This paper investigates how the ordering of variables affects properties of the time-varying covariance matrix in the Cholesky multivariate stochastic volatility model.It establishes that systematically different dynamic restrictions are imposed whenthe ratio of volatilities is time-varying. Simulations demonstrate that estimated co-variance matrices become more divergent when volatility clusters idiosyncratically.It is illustrated that this property is important for empirical applications. Specifically, alternative estimates on the evolution of U.S. systematic monetary policy andinflation-gap persistence indicate that conclusions may critically hinge on a selectedordering of variables. The dynamic correlation Cholesky multivariate stochasticvolatility model is proposed as a robust alternative.

Keywords: Model uncertainty; Multivariate stochastic volatility; Dynamic correlations; Monetary policy; Structural VAR (search for similar items in EconPapers)
JEL-codes: C11 C32 E32 E52 (search for similar items in EconPapers)
Date: 2020
New Economics Papers: this item is included in nep-ecm, nep-ets, nep-mac and nep-ore
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Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:zbw:bubdps:342020

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