taking the initial conditions problem and potential endogeneity of panel attrition into account. In line with results from …

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

means of a Markov switching-SVAR (MS-SVAR) model in heteroskedasticity. Using data from France, Germany, Italy, Japan, the …

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 …

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 …

from the US Commodity Futures Trading Commission, aggregated by trader groups. We exploit the heteroskedasticity in the …