Johansen's reduced rank maximum likelihood (ML) estimator for cointegration parameters in vector error correction models is known to produce occasional extreme outliers. Using a small monetary system and German data we illustrate the practical importance of this problem. We also consider an...

Structural vector autoregressive (VAR) models are in frequent use for impulse response analysis. If cointegrated variables are involved, the corresponding vector error correction models offer a convenient framework for imposing structural long-run and short-run restrictions. Occasionally it is...

A growing literature uses changes in residual volatility for identifying structural shocks in vector autoregressive (VAR) analysis. A number of different models for heteroskedasticity or conditional heteroskedasticity are proposed and used in applications in this context. This study reviews the...

The shocks in structural vector autoregressive (VAR) analysis are typically assumed to be instantaneously uncorrelated. This condition may easily be violated in proxy VAR models if more than one shock is identified by a proxy variable. Correlated shocks may be obtained even if the proxies are...

We propose a test for time-varying impulse responses in heteroskedastic structural vector autoregressions that can be used when the shocks are identified by external proxy variables as a group. The test can be used even if the shocks are not identified individually. The asymptotic analysis is...

Studies of the crude oil market based on structural vector autoregressive (VAR) models typically assume a time-invariant model and transmission of shocks or they consider a time-varying model and shock transmission. We assume a heteroskedastic reduced-form VAR model with time-invariant slope...

Structural vector autoregressive (VAR) models are important tools for empirical work in macroeconomics, finance, and related fields. This book not only reviews the many alternative structural VAR approaches discussed in the literature, but also highlights their pros and cons in practice. It...

A major challenge for proxy vector autoregressive analysis is the construction of a suitable instrument variable for identifying a shock of interest. We propose a simple proxy that can be constructed whenever the dating and sign of particular shocks are known. It is shown that the proxy can lead...

We propose a new bootstrap for inference for impulse responses in structural vector autoregressive models identified with an external proxy variable. Simulations show that the new bootstrap provides confidence intervals for impulse responses which often have more precise coverage than and...