The Asymptotic Distribution of the F-Test Statistic for Individual Effects
Abstract(the number of cross-sections) and T is fixed (the number of time periods). Three theoretical results emerge: (i) the standard F-test procedure will still deliver asymptotically valid inferences; (ii) under (pure) local random effects, the F-test and random effects test procedures have identical asymptotic power; (iii) under local fixed, or random effects which are correlated with the regressors, the F-test will have higher asymptotic power than the random effects test. Copyright Royal Economic Society 2006
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Date of creation: 2006
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- Chris D. Orme & Takashi Yamagata, 2006. "The asymptotic distribution of the F-test statistic for individual effects," Econometrics Journal, Royal Economic Society, vol. 9(3), pages 404-422, November.
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- Moulton, Brent R & Randolph, William C, 1989. "Alternative Tests of the Error Components Model," Econometrica, Econometric Society, vol. 57(3), pages 685-93, May.
- Chesher, Andrew D, 1984. "Testing for Neglected Heterogeneity," Econometrica, Econometric Society, vol. 52(4), pages 865-72, July.
- Baltagi, Badi H. & Chang, Young-Jae & Li, Qi, 1992. "Monte Carlo results on several new and existing tests for the error component model," Journal of Econometrics, Elsevier, vol. 54(1-3), pages 95-120.
- Breusch, T S & Pagan, A R, 1980. "The Lagrange Multiplier Test and Its Applications to Model Specification in Econometrics," Review of Economic Studies, Wiley Blackwell, vol. 47(1), pages 239-53, January.
- Marc Nerlove, 1968.
"Further Evidence on the Estimation of Dynamic Economic Relations from a Time Series of Cross-Sections,"
Cowles Foundation Discussion Papers
257, Cowles Foundation for Research in Economics, Yale University.
- Nerlove, Marc, 1971. "Further Evidence on the Estimation of Dynamic Economic Relations from a Time Series of Cross Sections," Econometrica, Econometric Society, vol. 39(2), pages 359-82, March.
- Ali, Mukhtar M. & Sharma, Subhash C., 1996. "Robustness to nonnormality of regression F-tests," Journal of Econometrics, Elsevier, vol. 71(1-2), pages 175-205.
- Qin, Huaizhen & Wan, Alan T.K., 2004. "ON THE PROPERTIES OF THE t- AND F-RATIOS IN LINEAR REGRESSIONS WITH NONNORMAL ERRORS," Econometric Theory, Cambridge University Press, vol. 20(04), pages 690-700, August.
- Leslie G. Godfrey & Chris D. Orme, 2000. "Controlling the significance levels of prediction error tests for linear regression models," Econometrics Journal, Royal Economic Society, vol. 3(1), pages 66-83.
- Calhoun, Gray, 2010. "Hypothesis Testing in Linear Regression when K/N is Large," Staff General Research Papers 32216, Iowa State University, Department of Economics.
- Chris D. Orme & Takashi Yamagata, 2011. "A Heteroskedasticity-Robust F-Test Statistic for Individual Effects," The School of Economics Discussion Paper Series 1124, Economics, The University of Manchester.
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