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Within and between estimates in random-effects models: Advantages and drawbacks of correlated random effects and hybrid models

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  • Reinhard Schunck

    (University of Bielefeld)

Abstract

Correlated random-effects (Mundlak, 1978, Econometrica 46: 69–85; Wooldridge, 2010, Econometric Analysis of Cross Section and Panel Data [MIT Press]) and hybrid models (Allison, 2009, Fixed Effects Regression Models [Sage]) are attractive alternatives to standard random-effects and fixed-effects models because they provide within estimates of level 1 variables and allow for the inclusion of level 2 variables. I discuss these models, give estimation examples, and address some complications that arise when interaction effects are included. Copyright 2013 by StataCorp LP.

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  • Reinhard Schunck, 2013. "Within and between estimates in random-effects models: Advantages and drawbacks of correlated random effects and hybrid models," Stata Journal, StataCorp LP, vol. 13(1), pages 65-76, March.
    • Handle: RePEc:tsj:stataj:v:13:y:2013:i:1:p:65-76
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    References listed on IDEAS

    as
    1. Jason Abrevaya, 2006. "Estimating the effect of smoking on birth outcomes using a matched panel data approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(4), pages 489-519, May.
    2. Robert L. Kaufman, 1993. "Decomposing Longitudinal from Cross-Unit Effects in Panel and Pooled Cross-Sectional Designs," Sociological Methods & Research, , vol. 21(4), pages 482-504, May.
    3. Jeffrey M Wooldridge, 2010. "Econometric Analysis of Cross Section and Panel Data," MIT Press Books, The MIT Press, edition 2, volume 1, number 0262232588, December.
    4. Mundlak, Yair, 1978. "On the Pooling of Time Series and Cross Section Data," Econometrica, Econometric Society, vol. 46(1), pages 69-85, January.
    5. Hausman, Jerry A. & Taylor, William E., 1981. "A generalized specification test," Economics Letters, Elsevier, vol. 8(3), pages 239-245.
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