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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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    References listed on IDEAS

    as
    1. William Greene, 2004. "Distinguishing between heterogeneity and inefficiency: stochastic frontier analysis of the World Health Organization's panel data on national health care systems," Health Economics, John Wiley & Sons, Ltd., vol. 13(10), pages 959-980, October.
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    3. 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.
    4. Willam Greene, 2005. "Fixed and Random Effects in Stochastic Frontier Models," Journal of Productivity Analysis, Springer, vol. 23(1), pages 7-32, January.
    5. 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.
    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.
    Full references (including those not matched with items on IDEAS)

    Citations

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    Cited by:

    1. Bergantino, Angela Stefania & Intini, Mario & Volta, Nicola, 2021. "The spatial dimension of competition among airports at the worldwide level: a spatial stochastic frontier analysis," European Journal of Operational Research, Elsevier, vol. 295(1), pages 118-130.
    2. Jacopo Canello & Francesco Vidoli, 2020. "Investigating space‐time patterns of regional industrial resilience through a micro‐level approach: An application to the Italian wine industry," Journal of Regional Science, Wiley Blackwell, vol. 60(4), pages 653-676, September.
    3. Fusco, Elisa & Allegrini, Veronica, 2020. "The role of spatial interdependence in local government cost efficiency: An application to waste Italian sector," Socio-Economic Planning Sciences, Elsevier, vol. 69(C).
    4. Leonardo Rodriguez-Pineda & Andres Felipe Sanchez-Saldarriaga & Helena María Cancelado-Carretero, 2020. "Spatial Dynamic Effects in the Colombian Health System," Lecturas de Economía, Universidad de Antioquia, Departamento de Economía, issue 92, pages 201-222, Enero-Jun.
    5. Bergantino, Angela Stefania & Intini, Mario & Volta, Nicola, 2020. "Spatial competition and efficiency: an investigation in the airport sector," The Warwick Economics Research Paper Series (TWERPS) 1287, University of Warwick, Department of Economics.
    6. 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).
    7. Xueqian Song & Yongping Wei & Wei Deng & Shaoyao Zhang & Peng Zhou & Ying Liu & Jiangjun Wan, 2019. "Spatio-Temporal Distribution, Spillover Effects and Influences of China’s Two Levels of Public Healthcare Resources," IJERPH, MDPI, vol. 16(4), pages 1-18, February.
    8. 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.

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    More about this item

    Keywords

    panel data; fixed effects; production of health; efficiency measurement; heterogeneity; spatial effects; spatial autocorrelation;
    All these keywords.

    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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