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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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    References listed on IDEAS

    as
    1. Ciuiu, Daniel, 2008. "Pattern classification using polynomial and linear regression," MPRA Paper 15355, University Library of Munich, Germany.
    2. Ciuiu, Daniel & Costinescu, Cristian, 2008. "The Monte Carlo method to find eigenvalues and eigenvectors," MPRA Paper 15362, University Library of Munich, Germany.
    3. Nastac, Iulian & Dobrescu, Emilian & Pelinescu, Elena, 2007. "Neuro-Adaptive Model for Financial Forecasting," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 4(3), pages 19-41, September.
    4. Ciuiu, Daniel, 2008. "Pattern classification using principal components regression," MPRA Paper 15360, University Library of Munich, Germany.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

    small areas; direct and indirect estimations; Markov chains; Gibbs sampling; Metropolis-Hastings algorithm;

    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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