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Hierarchical Bayesian Estimation of the Number of Visits to the Generalist in 2002/2003 French Health Survey

Author

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  • Stefan, Marius

    (Polytechnic University Bucharest)

Abstract

In our paper we show how to construct a model for one variable in the French Health Survey data set: the number of times an individual visited a generalist in the last twelve months, for which we are interested in estimating the regional means. Then, we test the fit of the model to the data and compare it to other two alternative models. We derive theoretical formulas for the estimates of the twenty-two regional means along with their standard deviations. We compare this to the design-based estimations obtained by INSEE in the case of the five regions with extra sample. We discuss some alternative for future research.

Suggested Citation

  • Stefan, Marius, 2008. "Hierarchical Bayesian Estimation of the Number of Visits to the Generalist in 2002/2003 French Health Survey," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 5(2), pages 67-91, June.
    • Handle: RePEc:rjr:romjef:v:5:y:2008:i:2:p:67-91
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    File URL: http://www.ipe.ro/rjef/rjef2_08/rjef2_08_5.pdf
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    Cited by:

    1. Mau, Vladimir (Мау, Владимир), 2015. "Economic Crises in Post-Communist Russia [Экономические Кризисы В Новейшей Истории России]," Ekonomicheskaya Politika / Economic Policy, Russian Presidential Academy of National Economy and Public Administration, vol. 2, pages 7-19.

    More about this item

    Keywords

    small areas; direct and indirect estimations; Markov chains; Gibbs sampling; Metropolis-Hastings algorithm;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C46 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Specific Distributions

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