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Bias-Corrected Bootstrap Inference for Regression Models with Autocorrelated Errors

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  • Jae Kim

    (Monash University)

Abstract

A bootstrap bias-correction method is applied to statistical inference in the regression model with autocorrelated errors. It is found that this method substantially reduces small-sample size distortions relative to alternative methods proposed in the literature.

Suggested Citation

  • Jae Kim, 2005. "Bias-Corrected Bootstrap Inference for Regression Models with Autocorrelated Errors," Economics Bulletin, AccessEcon, vol. 3(44), pages 1-8.
    • Handle: RePEc:ebl:ecbull:eb-05c20017
    as

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    References listed on IDEAS

    as
    1. Rayner, Robert K., 1991. "Resampling methods for tests in regression models with autocorrelated errors," Economics Letters, Elsevier, vol. 36(3), pages 281-284, July.
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    7. van Giersbergen, Noud P. A. & Kiviet, Jan F., 2002. "How to implement the bootstrap in static or stable dynamic regression models: test statistic versus confidence region approach," Journal of Econometrics, Elsevier, vol. 108(1), pages 133-156, May.
    8. King, M.L. & Giles, D.E.A., 1984. "Autocorrelation pre-testing in the linear model: Estimation, testing and prediction," Journal of Econometrics, Elsevier, vol. 25(1-2), pages 35-48.
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    More about this item

    Keywords

    Bias-correction;

    JEL classification:

    • C2 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables

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