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

Arbeitspapier

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.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Series: MAGKS Joint Discussion Paper Series in Economics ; No. 16-2016

Classification and Topics

• Classification: Wirtschaft ; Multiple or Simultaneous Equation Models: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
• Subject: impulse responses ; joint confidence bands ; highest density region ; vector autoregressive process

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Lütkepohl, Helmut ; Staszewska-Bystrova, Anna ; Winker, Peter
• Event: Veröffentlichung
• (who): Philipps-University Marburg, School of Business and Economics
• (where): Marburg
• (when): 2016

Further information

• Handle: http://hdl.handle.net/10419/144681
• Last update: 10.03.2025, 11:42 AM CET