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: Department of Economics, University of Giessen

No 1/2018, Lodz Economics Working Papers from University of Lodz, Faculty of Economics and Sociology

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)
Date: 2018-03-08
New Economics Papers: this item is included in nep-ets
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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:ann:wpaper:1/2018

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