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Bootstrapping and hypothesis testing in non-stationary panel data

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  • Jamie Emerson
  • Chihwa Kao

Abstract

This paper uses the wild bootstrap to compute empirically relevant critical values for the test statistics proposed by Emerson and Kao (2001). Monte Carlo simulations were then performed to evaluate the size and power properties of the bootstrapped tests.

Suggested Citation

  • Jamie Emerson & Chihwa Kao, 2005. "Bootstrapping and hypothesis testing in non-stationary panel data," Applied Economics Letters, Taylor & Francis Journals, vol. 12(5), pages 313-318.
  • Handle: RePEc:taf:apeclt:v:12:y:2005:i:5:p:313-318
    DOI: 10.1080/13504850500043965
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    References listed on IDEAS

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    1. Davidson, Russell & Flachaire, Emmanuel, 2008. "The wild bootstrap, tamed at last," Journal of Econometrics, Elsevier, vol. 146(1), pages 162-169, September.
    2. Horowitz, Joel L., 1994. "Bootstrap-based critical values for the information matrix test," Journal of Econometrics, Elsevier, vol. 61(2), pages 395-411, April.
    3. Li, Q. & Wang, Suojin, 1998. "A simple consistent bootstrap test for a parametric regression function," Journal of Econometrics, Elsevier, vol. 87(1), pages 145-165, August.
    4. Joel L. Horowitz, 1996. "Bootstrap Methods in Econometrics: Theory and Numerical Performance," Econometrics 9602009, EconWPA, revised 05 Mar 1996.
    5. Horowitz, Joel L. & Savin, N. E., 2000. "Empirically relevant critical values for hypothesis tests: A bootstrap approach," Journal of Econometrics, Elsevier, vol. 95(2), pages 375-389, April.
    6. Whang, Yoon-Jae, 2000. "Consistent bootstrap tests of parametric regression functions," Journal of Econometrics, Elsevier, vol. 98(1), pages 27-46, September.
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