Calculating Joint Confidence Bands for Impulse Response Functions using Highest Density Regions

This paper proposes a new non-parametric method of constructing joint confidence bands for impulse response functions of vector autoregressive models.The estimation uncertainty is captured by means of bootstrapping and the highest density region (HDR) approach is used to construct the bands. A Mont...

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Wedi'i Gadw mewn:
Manylion Llyfryddiaeth
Cyhoeddwyd yn:MAGKS - Joint Discussion Paper Series in Economics (Band 16-2016)
Prif Awduron: Lütkepohl, Helmut, Staszewska-Bystrova, Anna, Winker, Peter
Fformat: Erthygl
Iaith:Saesneg
Cyhoeddwyd: Philipps-Universität Marburg 2016
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Crynodeb:This paper proposes a new non-parametric method of constructing joint confidence bands for impulse response functions of vector autoregressive models.The estimation uncertainty is captured by means of bootstrapping and the highest density region (HDR) approach is used to construct the bands. A Monte Carlo comparison of the HDR bands with existing alternatives shows that the former are competitive with the bootstrap-based Bonferroni and Wald confidence regions. The relative tightness of the HDR bands matched with their good coverage properties makes them attractive for applications. An application to corporate bond spreads for Germany highlights the potential for empirical work.
Disgrifiad Corfforoll:40 Seiten
ISSN:1867-3678
DOI:10.17192/es2024.0508