Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/181590 
Year of Publication: 
2018
Series/Report no.: 
Beiträge zur Jahrestagung des Vereins für Socialpolitik 2018: Digitale Wirtschaft - Session: Time Series No. D04-V2
Publisher: 
ZBW - Leibniz-Informationszentrum Wirtschaft, Kiel, Hamburg
Abstract: 
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.
Subjects: 
Bootstrap
confidence intervals
joint confidence bands
vector autoregression
impulse response functions
JEL: 
C15
C32
Document Type: 
Conference Paper

Files in This Item:
File
Size





Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.