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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.

Suggested Citation

  • Reinhard Schunck, 2013. "Within and between estimates in random-effects models: Advantages and drawbacks of correlated random effects and hybrid models," Stata Journal, StataCorp LLC, 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. Mundlak, Yair, 1978. "On the Pooling of Time Series and Cross Section Data," Econometrica, Econometric Society, vol. 46(1), pages 69-85, January.
    2. 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.
    3. Hausman, Jerry A. & Taylor, William E., 1981. "A generalized specification test," Economics Letters, Elsevier, vol. 8(3), pages 239-245.
    4. 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.
    5. 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.
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