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Skewness-Adjusted Bootstrap Confidence Intervals and Confidence Bands for Impulse Response Functions

This article investigates the construction of skewness-adjusted con�dence 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...

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Bibliographic Details
Published in:MAGKS - Joint Discussion Paper Series in Economics (Band 10-2018)
Main Authors: Grabowski, Daniel, Staszewska-Bystrova, Anna, Winker, Peter
Format: Article
Language:English
Published: Philipps-Universität Marburg 2018
Subjects:
vector autoregression
Wirtschaft
confidence intervals
joint confidence bands
Bootstrap
Economics
Online Access:PDF Full Text
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Summary:This article investigates the construction of skewness-adjusted con�dence 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 coeffcients 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.
Physical Description:22 Pages
ISSN:1867-3678
DOI:10.17192/es2024.0563

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