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

Daniel Grabowski and Anna Staszewska-Bystrova

Annual Conference 2018 (Freiburg, Breisgau): Digital Economy from Verein für Socialpolitik / German Economic Association

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; impulse response functions (search for similar items in EconPapers)
JEL-codes: C15 C32 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ecm
Date: 2018
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https://www.econstor.eu/bitstream/10419/181590/1/VfS-2018-pid-13707.pdf (application/pdf)

Related works:
Working Paper: Skewness-Adjusted Bootstrap Confidence Intervals and Confidence Bands for Impulse Response Functions (2018) Downloads
Working Paper: Skewness-Adjusted Bootstrap Confidence Intervals and Confidence Bands for Impulse Response Functions (2018) Downloads
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