 A Comparison between bias Approximations Applied to Bivariate VAR ModelsTomas Brännström
No 22, SSE/EFI Working Paper Series in Economics and Finance from Stockholm School of Economics Abstract: Bivariate VAR models are Monte Carlo simulated and OLS estimated, The resulting biases are used to compare two alternative approximations to the bias. They are found to be equivalent for first-order models, whereas for second-order models Nicholls and Pope's approximation outperforms Tjostheim and Paulsen's approximation, although the difference is negligible. This being the case when approximations are based on true parameters as well as when they are based on estimates, any of the two approximation can be used to construct bias-reduced estimates as outlined in an earlier paper, leading to better estimates both in terms of bias and mean square error than the original OLS estimate. Finally, using a more correct version of Nicholls and Pope's approximation turns out to improve results only marginally for second-order models, and for first-order models they appear to deteriorate. Keywords: VAR models; Monte Carlo simulation; bias approximation and reduction (search for similar items in EconPapers) There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it. Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:hhs:hastef:0022 Access Statistics for this paper More papers in SSE/EFI Working Paper Series in Economics and Finance from Stockholm School of Economics The Economic Research Institute, Stockholm School of Economics, P.O. Box 6501, 113 83 Stockholm, Sweden. Contact information at EDIRC. |
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