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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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| 发表在: | MAGKS - Joint Discussion Paper Series in Economics (Band 10-2018) |
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| Autoren: | , , |
| 格式: | 文件 |
| 语言: | 英语 |
| 出版: |
Philipps-Universität Marburg
2018
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| 主题: | |
| 在线阅读: | PDF-Volltext |
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| 总结: | 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. |
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| 实物描述: | 22 Seiten |
| ISSN: | 1867-3678 |
| DOI: | 10.17192/es2024.0563 |