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

Daniel Grabowski (), Anna Staszewska-Bystrova and Peter Winker
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Daniel Grabowski: University of Giessen

MAGKS Papers on Economics from Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung)

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.

Keywords: Bootstrap; confidence intervals; joint confidence bands; vector autoregression (search for similar items in EconPapers)
JEL-codes: C15 C32 (search for similar items in EconPapers)
Pages: 22 pages
Date: 2018
New Economics Papers: this item is included in nep-ecm and nep-ets
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http://www.uni-marburg.de/fb02/makro/forschung/mag ... 0-2018_grabowski.pdf First 201810 (application/pdf)

Related works:
Journal Article: Skewness-adjusted bootstrap confidence intervals and confidence bands for impulse response functions (2020)
Working Paper: Skewness-Adjusted Bootstrap Confidence Intervals and Confidence Bands for Impulse Response Functions (2018)
Working Paper: Skewness-Adjusted Bootstrap Confidence Intervals and Confidence Bands for Impulse Response Functions (2018)
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Persistent link: https://EconPapers.repec.org/RePEc:mar:magkse:201810

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