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Structural vector autoregressive models with more shocks than variables identified via heteroskedasticity

Lütkepohl, Helmut - 2020

In conventional structural vector autoregressive (VAR) models it is assumed that there are at most as many structural shocks as there are variables in the model. It is pointed out that heteroskedasticity can be used to identify more shocks than variables. However, even if there is...

Persistent link: https://www.econbiz.de/10012223488

Bayesian inference for structural vector autoregressions identified by Markov-switching heteroskedasticity

Lütkepohl, Helmut; Woźniak, Tomasz - 2017

In order to identify structural shocks that affect economic variables, restrictions need to be imposed on the parameters of structural vector autoregressive (SVAR) models. Economic theory is the primary source of such restrictions. However, only over-identifying restrictions can be tested with...

Persistent link: https://www.econbiz.de/10011771740

Bayesian inference for the mixed-frequency VAR model

Viefers, Paul - 2011

In this paper a mixed-frequency VAR à la Mariano & Murasawa (2004) with Markov regime switching in the parameters is estimated by Bayesian inference. Unlike earlier studies, that used the pseuo-EM algorithm of Dempster, Laird & Rubin (1977) to estimate the model, this paper describes how to...

Persistent link: https://www.econbiz.de/10009579612

Bootstrapping impulse responses of structural vector autoregressive models identified through GARCH

Lütkepohl, Helmut; Schlaak, Thore - 2018 - Revised version: January 29, 2019

identified by generalized autoregressive conditional heteroskedasticity (GARCH) are reviewed and compared in a Monte Carlo study …. The bootstrap methods considered are a wild bootstrap, a moving blocks bootstrap and a GARCH residual based bootstrap …. Estimation is done by Gaussian maximum likelihood, a simplified procedure based on univariate GARCH estimations and a method that …

Persistent link: https://www.econbiz.de/10012041300

Structural vector autoregressions with heteroskedasticity : a comparison of different volatility models

Lütkepohl, Helmut; Netšunajev, Aleksei - 2015

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...

Persistent link: https://www.econbiz.de/10010501257

Bootstrapping impulse responses of structural vector autoregressive models identified through GARCH

Lütkepohl, Helmut; Schlaak, Thore - 2018

generalized autoregressive conditional heteroskedastic (GARCH) innovations. The bootstrap methods considered are a wild bootstrap …, a moving blocks bootstrap and a GARCH residual based bootstrap. Estimation is done by Gaussian maximum likelihood, a … simplified procedure based on univariate GARCH estimations and a method that does not re-estimate the GARCH parameters in each …

Persistent link: https://www.econbiz.de/10011880712

Choosing between different time-varying volatility models for structural vector autoregressive analysis

Lütkepohl, Helmut; Schlaak, Thore - 2017 - This version: July 4, 2017

The performance of information criteria and tests for residual heteroskedasticity for choosing between different models for time-varying volatility in the context of structural vector autoregressive analysis is investigated. Although it can be difficult to find the true volatility model with the...

Persistent link: https://www.econbiz.de/10011669909