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Estimating multiway error-components models with correlated effects in Stata

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  • Giovanni Bruno

    (Università Bocconi)

Abstract

I derive new estimators and tests of correlated effects for the (possibly) unbalanced multiway error component model (ECM), extending existing results in various aspects. The results by Kang (1985) on specification tests, who extended Hausman and Taylor (1981) and Mundlak (1978) to the two-way balanced model, emerge as particular cases of the present analysis. Davis (2002), who extends the analysis of Wansbeek and Kaptein (1989) to the multiway unbalanced model does not consider the cases of either correlated effects or specification tests. I also uncover new algebraic properties of the multiway ECM covariance matrix that prove useful for both computational and analytical purposes. Finally, I provide some examples using Stata.

Suggested Citation

  • Giovanni Bruno, 2009. "Estimating multiway error-components models with correlated effects in Stata," Italian Stata Users' Group Meetings 2008 06, Stata Users Group.
    • Handle: RePEc:boc:isug08:06
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    References listed on IDEAS

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    1. Hausman, Jerry A & Taylor, William E, 1981. "Panel Data and Unobservable Individual Effects," Econometrica, Econometric Society, vol. 49(6), pages 1377-1398, November.
    2. Kang, Suk, 1985. "A note on the equivalence of specification tests in the two-factor multivariate variance components model," Journal of Econometrics, Elsevier, vol. 28(2), pages 193-203, May.
    3. Mundlak, Yair, 1978. "On the Pooling of Time Series and Cross Section Data," Econometrica, Econometric Society, vol. 46(1), pages 69-85, January.
    4. Davis, Peter, 2002. "Estimating multi-way error components models with unbalanced data structures," Journal of Econometrics, Elsevier, vol. 106(1), pages 67-95, January.
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