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Assessment of a spatial panel model for the efficiency analysis of the heterogonous healthcare systems in the world

Author

Listed:
  • Vahidin Jeleskovic

    () (University of Kassel)

  • Benjamin Schwanebeck

    () (University of Kassel)

Abstract

Various panel models were presented to resolve the ranking of global health care systems according to efficiency. However, in terms of the spatial distribution of statistical units, spatial dependence as a result of various forms of spatial interactions caused biased estimators in classical regression. To our knowledge, this is the first paper which analyzes the healthcare systems of WHO members with regard to spatial dependencies while distinguishing between heterogeneity and inefficiency. It was possible to determine a significant spatial autocorrelation. Therefore one have to consider these spatial spillovers when assessing the performance of healthcare systems. The most meaningful way of implementing these effects appears to be by regressing the health output on various explanatory variables through a combination of the fixed effects spatial lag and the fixed effects cross regressive model. This allows spatial spillovers due to level of education, healthcare expenditure, and the quality of the healthcare system itself, to be diagnosed. Modeling these spatial effects allows previous results to be given more precision with regard to the quality of the healthcare systems of WHO members.

Suggested Citation

  • Vahidin Jeleskovic & Benjamin Schwanebeck, 2012. "Assessment of a spatial panel model for the efficiency analysis of the heterogonous healthcare systems in the world," MAGKS Papers on Economics 201248, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
  • Handle: RePEc:mar:magkse:201248
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    File URL: https://www.uni-marburg.de/fb02/makro/forschung/magkspapers/48-2012_jeleskovic.pdf
    File Function: First version, 2012
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    References listed on IDEAS

    as
    1. Göran Therborn & K.C. Ho, 2009. "Introduction," City, Taylor & Francis Journals, vol. 13(1), pages 53-62, March.
    2. Debarsy, Nicolas & Ertur, Cem, 2010. "Testing for spatial autocorrelation in a fixed effects panel data model," Regional Science and Urban Economics, Elsevier, vol. 40(6), pages 453-470, November.
    3. Kruk, Margaret Elizabeth & Freedman, Lynn P., 2008. "Assessing health system performance in developing countries: A review of the literature," Health Policy, Elsevier, vol. 85(3), pages 263-276, March.
    4. Schmidt, Peter & Sickles, Robin C, 1984. "Production Frontiers and Panel Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 2(4), pages 367-374, October.
    5. J. Barkley Rosser, 2009. "Introduction," Chapters,in: Handbook of Research on Complexity, chapter 1 Edward Elgar Publishing.
    6. Cornwell, Christopher & Schmidt, Peter & Sickles, Robin C., 1990. "Production frontiers with cross-sectional and time-series variation in efficiency levels," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 185-200.
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    Citations

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    Cited by:

    1. Tolga Ülkü & Vahidin Jeleskovic & Jürgen Müller, 2014. "How scale and institutional setting explain the costs of small airports? -An application of spatial regression analysis," MAGKS Papers on Economics 201435, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    2. Vidoli, Francesco & Cardillo, Concetta & Fusco, Elisa & Canello, Jacopo, 2016. "Spatial nonstationarity in the stochastic frontier model: An application to the Italian wine industry," Regional Science and Urban Economics, Elsevier, vol. 61(C), pages 153-164.

    More about this item

    Keywords

    panel data; fixed effects; production of health; efficiency measurement; heterogeneity; spatial effects; spatial autocorrelation;

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • I12 - Health, Education, and Welfare - - Health - - - Health Behavior

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