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Approximate Power Functions for Some Robust Tests of Regression Coefficients

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  • Rothenberg, Thomas J
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    Abstract

    Edgeworth approximations are developed for the distribution functio ns of some statistics for testing a linear hypothesis on the coefficient s in a regression model with an unknown error covariance matrix. Adjust ments to the asymptotic critical values are found to insure that the tests have correct size to second order of approximation. The power loss due to the estimation of the error covariance matrix is calculated. Some examples involving heteroskedasticity and autocorrelation suggest that the null rejection probabilities of common robust regression tests are often considerably greater than their nominal level. Moreover, the cost of not knowing the error covariance matrix can be substantial. Copyright 1988 by The Econometric Society.

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    Bibliographic Info

    Article provided by Econometric Society in its journal Econometrica.

    Volume (Year): 56 (1988)
    Issue (Month): 5 (September)
    Pages: 997-1019

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    Handle: RePEc:ecm:emetrp:v:56:y:1988:i:5:p:997-1019

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    Cited by:
    1. Linton, Oliver, 1997. "An Asymptotic Expansion in the GARCH(l, 1) Model," Econometric Theory, Cambridge University Press, vol. 13(04), pages 558-581, August.
    2. A. Colin Cameron & Jonah B. Gelbach & Douglas L. Miller, 2008. "Bootstrap-Based Improvements for Inference with Clustered Errors," The Review of Economics and Statistics, MIT Press, vol. 90(3), pages 414-427, August.
    3. Hausman, Jerry & Kuersteiner, Guido, 2008. "Difference in difference meets generalized least squares: Higher order properties of hypotheses tests," Journal of Econometrics, Elsevier, vol. 144(2), pages 371-391, June.
    4. Jerry A. Hausman & Christopher J. Palmer, 2011. "Heteroskedasticity-Robust Inference in Finite Samples," NBER Working Papers 17698, National Bureau of Economic Research, Inc.
    5. Magdalinos, Michael A. & Symeonides, Spyridon D., 1995. "Alternative size corrections for some GLS test statistics the case of the AR(1) model," Journal of Econometrics, Elsevier, vol. 66(1-2), pages 35-59.
    6. Banerjee, Anurag N. & Magnus, Jan R., 2000. "On the sensitivity of the usual t- and F-tests to covariance misspecification," Journal of Econometrics, Elsevier, vol. 95(1), pages 157-176, March.
    7. Spyridon D. Symeondes & Yiannis Karavias & Elias Tzavalis, . "Size corrected significance tests in Seemingly Unrelated Regressions with autocorrelated errors," Discussion Papers 14/01, University of Nottingham, Granger Centre for Time Series Econometrics.
    8. Steigerwald, Douglas G & Erb, Jack, 2007. "Accurately Sized Test Statistics with Misspecified Conditional Homoskedasticity," University of California at Santa Barbara, Economics Working Paper Series qt5rv0z5dz, Department of Economics, UC Santa Barbara.
    9. Linton, Oliver, 1995. "Second Order Approximation in the Partially Linear Regression Model," Econometrica, Econometric Society, vol. 63(5), pages 1079-1112, September.
    10. Hidehiko Ichimura & Oliver Linton, 2003. "Asymptotic Expansions for Some Semiparametric Program Evaluation Estimators," STICERD - Econometrics Paper Series /2003/451, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    11. Oliver Linton, 1997. "Second Order Approximation in a Linear Regression with Heteroskedasticity for Unknown Form," Cowles Foundation Discussion Papers 1151, Cowles Foundation for Research in Economics, Yale University.
    12. Johansen, Soren, 2002. "A small sample correction for tests of hypotheses on the cointegrating vectors," Journal of Econometrics, Elsevier, vol. 111(2), pages 195-221, December.
    13. Rayner, Robert K., 1991. "Resampling methods for tests in regression models with autocorrelated errors," Economics Letters, Elsevier, vol. 36(3), pages 281-284, July.
    14. Moreira, Marcelo J. & Porter, Jack R. & Suarez, Gustavo A., 2009. "Bootstrap validity for the score test when instruments may be weak," Journal of Econometrics, Elsevier, vol. 149(1), pages 52-64, April.

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