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Cluster effects and simultaneity in multilevel models

Author

Listed:
  • Richard Blundell

    (Department of Economics, University College London and Institute for Fiscal Studies, London, UK)

  • Frank Windmeijer

    (Institute for Fiscal Studies, London, UK)

Abstract

For 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.

Suggested Citation

  • Richard Blundell & Frank Windmeijer, 1997. "Cluster effects and simultaneity in multilevel models," Health Economics, John Wiley & Sons, Ltd., vol. 6(4), pages 439-443.
  • Handle: RePEc:wly:hlthec:v:6:y:1997:i:4:p:439-443
    DOI: 10.1002/(SICI)1099-1050(199707)6:4<439::AID-HEC276>3.0.CO;2-B
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    Cited by:

    1. Luisa Corrado & Bernard Fingleton, 2012. "Where Is The Economics In Spatial Econometrics?," Journal of Regional Science, Wiley Blackwell, vol. 52(2), pages 210-239, May.
    2. Richard Blundell & Frank Windmeijer, 2000. "Identifying demand for health resources using waiting times information," Health Economics, John Wiley & Sons, Ltd., vol. 9(6), pages 465-474.
    3. Roy Carr-Hill & Paul Dixon & Russell Mannion & Nigel Rice & Kai Rudat & Ruth Sinclair & Peter Smith, 1997. "A model of the determinants of expenditure on children's personal social services," Working Papers 030cheop, Centre for Health Economics, University of York.
    4. Rabe-Hesketh, Sophia & Skrondal, Anders & Pickles, Andrew, 2005. "Maximum likelihood estimation of limited and discrete dependent variable models with nested random effects," Journal of Econometrics, Elsevier, vol. 128(2), pages 301-323, October.
    5. Marc Saez & Carme Saurina & Germà Coenders & Sònia González-Raya, 2006. "Use of primary health care services according to the different degrees of obesity in the Girona Health Region, Spain," Health Economics, John Wiley & Sons, Ltd., vol. 15(2), pages 173-193.
    6. Thompson, Simon G. & Nixon, Richard M. & Grieve, Richard, 2006. "Addressing the issues that arise in analysing multicentre cost data, with application to a multinational study," Journal of Health Economics, Elsevier, vol. 25(6), pages 1015-1028, November.
    7. Bache, Stefan Holst Milton & Kristensen, Troels, 2013. "A simple but efficient approach to the analysis of multilevel data," COHERE Working Paper 2013:6, University of Southern Denmark, COHERE - Centre of Health Economics Research.
    8. Guillem López-Casasnovas & Marc Saez, 2007. "A multilevel analysis on the determinants of regional health care expenditure: a note," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 8(1), pages 59-65, March.
    9. Nigel Rice & Paul Dixon & David Lloyd & David Roberts, 1999. "Derivation of a needs based capitation formula for allocation prescribing budgets," Working Papers 034cheop, Centre for Health Economics, University of York.
    10. Kathleen Carey, 2000. "A multilevel modelling approach to analysis of patient costs under managed care," Health Economics, John Wiley & Sons, Ltd., vol. 9(5), pages 435-446.
    11. Matthew Sutton & Peter Lock, 2000. "Regional differences in health care delivery: implications for a national resource allocation formula," Health Economics, John Wiley & Sons, Ltd., vol. 9(6), pages 547-559.

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