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Testing linear restrictions in linear models with empirical likelihood

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  • Francesco Bravo

    (Department of Economics and Related Studies, University of York, UK)

Abstract

In this paper we analyse the higher order asymptotic behaviour of a profiled empirical likelihood ratio which can be used to test a set of linear restrictions in linear regression models. We show that the resulting profiled empirical likelihood ratio admits a Bartlett correction which can be used to improve to third order the accuracy of commonly used tests in applied research without any distributional assumptions about the error process. Copyright Royal Economic Society 2002

Suggested Citation

  • Francesco Bravo, 2002. "Testing linear restrictions in linear models with empirical likelihood," Econometrics Journal, Royal Economic Society, vol. 5(1), pages 104-130, June.
    • Handle: RePEc:ect:emjrnl:v:5:y:2002:i:1:p:104-130
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    Cited by:

    1. Daniel Nordman, 2008. "An empirical likelihood method for spatial regression," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 68(3), pages 351-363, November.
    2. Whang, Yoon-Jae, 2006. "Smoothed Empirical Likelihood Methods For Quantile Regression Models," Econometric Theory, Cambridge University Press, vol. 22(2), pages 173-205, April.

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