In structural vector autoregressive analysis identifying the shocks of interest via heteroskedasticity has become a … standard tool. Unfortunately, the approaches currently used for modelling heteroskedasticity all have drawbacks. For instance … used conventional identification schemes in this context are rejected by the data if heteroskedasticity is allowed for …

mechanism and multivariate generalized autoregressive conditional heteroskedasticity (GARCH) models. Using changes in volatility …

restrictions for the structural shocks and also use (conditional) heteroskedasticity in the residuals for identification purposes …. Heteroskedasticity is modelled by a Markov-switching mechanism. We find a plausible identification scheme for stock market and monetary …

We develop a vector autoregressive framework that combines an external instrument and heteroskedasticity for the … identifying information in heteroskedasticity are less efficient and tend to underestimate the effects of monetary policy. …

We develop a structural vector autoregressive framework that combines external instruments and heteroskedasticity for … identified with both a valid instrument and heteroskedasticity have larger effects on production and prices than monetary shocks …

autoregression ; heteroskedasticity ; rude oil market …

new method by Klein and Vella (2010) that bases identification on the presence of conditional heteroskedasticity. Compared …

identification. The present study focusses on the latter device. Some possible setups for identification via heteroskedasticity are …. -- Markov switching model ; vector autoregression ; heteroskedasticity ; vector GARCH ; conditional heteroskedasticity …