Cluster effects and simultaneity in multilevel models
AbstractFor small group sizes, the GLS estimator in multilevel models is biased and inconsistent when the random cluster effects are correlated with the regressors. A fixed effects approach, conditioning on the cluster effects, provides consistent estimates for the slope parameters. The two estimators are equivalent when group sizes are large. The same results obtain for two-stage estimation procedures that allow for some of the regressors to be simultaneously determined with the dependent variable. The GLS and fixed effects estimators are applied to data on acute care hospital utilization in the UK, allowing for health authority district effects. © 1997 John Wiley & Sons, Ltd.
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Bibliographic InfoArticle provided by John Wiley & Sons, Ltd. in its journal Health Economics.
Volume (Year): 6 (1997)
Issue (Month): 4 ()
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- Richard Blundell & Frank Windmeijer, 1997. "Cluster effects and simultaneity in multilevel models," IFS Working Papers W97/05, Institute for Fiscal Studies.
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