Calculating joint confidence bands for impulse response functions using highest density regions

Helmut Lütkepohl, Anna Staszewska-Bystrova and Peter Winker

No 2016-017, SFB 649 Discussion Papers from Humboldt University Berlin, Collaborative Research Center 649: Economic Risk

Abstract: This paper proposes a new non-parametric method of constructing joint con- dence 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 con dence 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.

Keywords: impulse responses; joint confidence bands; highest density region; vector autoregressive process (search for similar items in EconPapers)
JEL-codes: C32 (search for similar items in EconPapers)
Date: 2016
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Related works:
Journal Article: Calculating joint confidence bands for impulse response functions using highest density regions (2018)
Working Paper: Calculating Joint Confidence Bands for Impulse Response Functions Using Highest Density Regions (2016)
Working Paper: Calculating Joint Confidence Bands for Impulse Response Functions using Highest Density Regions (2016)
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