Vorträge des DIW Berlin

Structural Vector Autoregressions with Smooth Transition in Variances: The Interaction Between U.S. Monetary Policy and the Stock Market

Structural Vector Autoregressions with Smooth Transition in Variances: The Interaction between U.S. Monetary Policy and the Stock Market

Structural Vector Autoregressions with Smooth Transition in Variances: The Interaction Between U.S. Monetary Policy and the Stock Market

Confidence Bands for Impulse Responses: Bonferroni versus Wald

It is emphasized that the shocks in structural vector autoregressions are only identified up to sign and it is pointed out that this feature can result in very misleading confidence intervals for impulse responses if simulation methods such as Bayesian or bootstrap methods are used. The confidence intervals heavily depend on which variable is used for fixing the sign of the initial responses. In...

Structural Vector Autoregressions with Short-Run Restrictions

Structural Vector Error Correction Models

Structural Vector Autoregressions: Checking Identifying Long-run Restrictions via Heteroskedasticity

Confidence Bands for Impulse Responses: Bonferroni versus Wald

Structural Vector Autoregressions: Checking Identifying Long-run Restrictions via Heteroskedasticity

Confidence Bands for Impulse Responses: Bonferroni versus Wald

Simulation von Konfidenzintervallen für Impuls-Antwort-Folgen struktureller Vektorautoregressionen

Identifying Structural Vector Autoregressions via Changes in Volatility: Keynote Speech

Identification of shocks of interest is a central problem in structural vector autoregressive (SVAR) modelling. Identification is often achieved by imposing restrictions on the impact or long-run effects of shocks or by considering sign restrictions for the impulse responses. In a number of articles changes in the volatility of the shocks have also been used for identification. The present study...

Comparison of Methods for Constructing Joint Confidence Bands for Impulse Response Functions

In vector autoregressive analysis confidence intervals for individual impulse responses are typically reported to indicate the sampling uncertainty in the estimation results. A range of methods are reviewed and a new proposal is made for constructing joint confidence bands, given a prespecified coverage level, for the impulse responses at all horizons considered simultaneously. The methods are...

Comparison of Methods for Constructing Joint Confidence Bands for Impulse Response Functions

In vector autoregressive analysis confidence intervals for individual impulse responses are typically reported to indicate the sampling uncertainty in the estimation results. A range of methods are reviewed and a new proposal is made for constructing joint confidence bands, given a prespecified coverage level, for the impulse responses at all horizons considered simultaneously. The methods are...

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Structural Vector Autoregressions with Markov Switching: Combining Conventional with Statistical Identification of Shocks

Identifying Structural Vector Autoregressions via Changes in Volatility

Identification of shocks of interest is a central problem in structural vector autoregressive (SVAR) modelling. Identification is often achieved by imposing restrictions on the impact or long-run effects of shocks or by considering sign restrictions for the impulse responses. In a number of articles changes in the volatility of the shocks have also been used for identification. The present study...

Structural Vector Autoregressive Analysis

Comparison of Methods for Constructing Joint Confidence Bands for Impulse Response Functions: Keynote Speech

In vector autoregressive analysis confidence intervals for individual impulse responses are typically reported to indicate the sampling uncertainty in the estimation results. A range of methods are reviewed and a new proposal is made for constructing joint confidence bands, given a prespecified coverage level, for the impulse responses at all horizons considered simultaneously. The methods are...