Fixed and random effects in Classical and Bayesian regression
This paper proposes a common and tractable framework for analyzing different definitions of fixed and random effects in a contant-slope variable-intercept model. It is shown that, regardless of whether effects (i) are treated as parameters or as an error term, (ii) are estimated in different stages of a hierarchical model, or whether (iii) correlation between effects and regressors is allowed, when the same information on effects is introduced into all estimation methods, the resulting slope estimator is also the same across methods. If different methods produce different results, it is ultimately because different information is being used for each methods.
References listed on IDEAS
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- Chamberlain, Gary, 1984. "Panel data," Handbook of Econometrics,in: Z. Griliches† & M. D. Intriligator (ed.), Handbook of Econometrics, edition 1, volume 2, chapter 22, pages 1247-1318 Elsevier.
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"Essays in Panel Data Econometrics,"
Cambridge University Press, number 9780521022460, August.
- Nerlove,Marc, 2002. "Essays in Panel Data Econometrics," Cambridge Books, Cambridge University Press, number 9780521815345, September.
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- Wallace, T D & Hussain, Ashiq, 1969. "The Use of Error Components Models in Combining Cross Section with Time Series Data," Econometrica, Econometric Society, vol. 37(1), pages 55-72, January.
- Boozer, Michael A., 1997. "Econometric Analysis of Panel Data Badi H. Baltagi Wiley, 1995," Econometric Theory, Cambridge University Press, vol. 13(05), pages 747-754, October. Full references (including those not matched with items on IDEAS)
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