Abstract Changes in residual volatility are often used for identifying structural shocks in
vector autoregressive (VAR) analysis. A number of different models for heteroskedasticity or …

Long‐run restrictions have been used extensively for identifying structural shocks in vector
autoregressive (VAR) analysis. Such restrictions are typically just‐identifying but can be …

In structural vector autoregressive analysis identifying the shocks of interest via
heteroskedasticity has become a standard tool. Unfortunately, the approaches currently …

Tests for identification through heteroskedasticity in structural vector autoregressive analysis
are developed for models with two volatility states where the time point of volatility change is …

We introduce a structural vector autoregressive model with endogenously switching
conditional covariance matrix. The structural shocks are identified by simultaneously …

The dynamics of European unemployment showed considerable fluctuations and
asymmetric behaviour during business cycles over the past decade. The dynamic pattern of …

In this study, Bayesian inference is developed for structural vector autoregressive models in
which the structural parameters are identified via Markov-switching heteroskedasticity. In …

Identification of shocks of interest is a central problem in structural vector autoregressive
(SVAR) modeling. Identification is often achieved by imposing restrictions on the impact or …

Purpose This study investigates the spillover effects between exchange rate changes and
stock returns in China. The authors find that no significant interconnections exist between …

We consider structural vector autoregressions identified through stochastic volatility. Our
focus is on whether a particular structural shock is identified by heteroskedasticity without …