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, assuming known dates for variance changes is often...

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, assuming known dates for variance changes is often...

Alternative modeling strategies for specifying subset VAR models are considered. It is shown that under certain conditions a testing procedure based on t-ratios is equivalent to sequentially eliminating lags that lead to the largest improvement in a prespecified model selection criterion. A...

The role of expectations for economic fluctuations has received considerable attention in recent business cycle analysis. We exploit Markov regime switching models to identify shocks in cointegrated structural vector autoregressions and investigate different identification schemes for bi-variate...