Estimating multiway error-components models with correlated effects in Stata
AbstractI 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.
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Bibliographic InfoPaper provided by Stata Users Group in its series Italian Stata Users' Group Meetings 2008 with number 06.
Date of creation: 19 Jan 2009
Date of revision:
This paper has been announced in the following NEP Reports:
- NEP-ALL-2009-01-31 (All new papers)
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- Hausman, Jerry A & Taylor, William E, 1981.
"Panel Data and Unobservable Individual Effects,"
Econometric Society, vol. 49(6), pages 1377-98, November.
- Davis, Peter, 2002. "Estimating multi-way error components models with unbalanced data structures," Journal of Econometrics, Elsevier, vol. 106(1), pages 67-95, January.
- Mundlak, Yair, 1978. "On the Pooling of Time Series and Cross Section Data," Econometrica, Econometric Society, vol. 46(1), pages 69-85, January.
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