Tests for identification through heteroskedasticity in structural vector autoregressive analysis are developed for …

parameters are identified via Markov-switching heteroskedasticity. In such a model, restrictions that are just-identifying in the … distributions. As an empirical example, monetary models are compared using heteroskedasticity as an additional device for …

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

(VAR) analysis. A number of different models for heteroskedasticity or conditional heteroskedasticity are proposed and used … drawbacks. It thereby enables researchers wishing to use identification of structural VAR models via heteroskedasticity to make …

heteroskedasticity is occasionally allowed for, it is typically taken for granted that the impact effects of the structural shocks are …

Identification through heteroskedasticity in heteroskedastic simultaneous equations models (HSEMs) is considered. The … possibility that heteroskedasticity identifies the structural parameters only partially is explicitly allowed for. The … asymptoticproperties of the identified parameters are derived. Moreover, tests for identification through heteroskedasticity are developed …

shocks as there are variables in the model. It is pointed out that heteroskedasticity can be used to identify more shocks … than variables. However, even if there is heteroskedasticity, the number of shocks that can be identified is limited. A … heteroskedasticity …

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