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Erscheinungsjahr: 
2018
Schriftenreihe/Nr.: 
MAGKS Joint Discussion Paper Series in Economics No. 10-2018
Verlag: 
Philipps-University Marburg, School of Business and Economics, Marburg
Zusammenfassung: 
This article investigates the construction of skewness-adjusted confidence intervals and joint confidence bands for impulse response functions from vector autoregressive models. Three different implementations of the skewness adjustment are investigated. The methods are based on a bootstrap algorithm that adjusts mean and skewness of the bootstrap distribution of the autoregressive coefficients before the impulse response functions are computed. Using extensive Monte Carlo simulations, the methods are shown to improve the coverage accuracy in small and medium sized samples and for unit root processes for both known and unknown lag orders.
Schlagwörter: 
Bootstrap
confidence intervals
joint confidence bands
vector autoregression
JEL: 
C15
C32
Dokumentart: 
Working Paper

Datei(en):
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