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La spesa sanitaria delle Regioni in Italia - Saniregio 2015

Author

Listed:
  • Fabio Pammolli

    (Politecnico di Milano and CERM Foundation - Competitività, Regole, Mercati)

  • Francesco Porcelli

    (Department of Economics Business School University of Exeters and CERM Foundation - Competitività, Regole, Mercati)

  • Francesco Vidoli

    (Dipartimento di Istituzioni Pubbliche Economia e Società Università degli Studi di Roma 3 and CERM Foundation - Competitività, Regole, Mercati)

  • Guido Borà

    (Dipartimento di Scienze Politiche e Cognitive Università degli Studi di Siena and CERM Foundation - Competitività, Regole, Mercati)

Abstract

Saniregio 2015 fornisce un'analisi della spesa sanitaria corrente delle singole Regioni italiane. Introduciamo un meccanismo di calcolo del fabbisogno standard basato sulla stima di una funzione di spesa, un modello empirico derivato dalla funzione di costo dei servizi sanitari, che vede come variabile dipendente la spesa storica corrente di ogni Regione e tra i principali driver del fabbisogno variabili di contesto socio-economico, con un ruolo fondamentale giocato dalla numerosità e dalla composizione per età della popolazione residente. Tra le principali novità metodologiche di Saniregio 2015, oltre alla popolazione, tra i principali driver dei fabbisogni standard, sono state inserite due variabili che misurano la quota di spesa riconducibile all'adeguatezza dei servizi erogati e all'efficienza con cui questi ultimi sono stati prodotti.

Suggested Citation

  • Fabio Pammolli & Francesco Porcelli & Francesco Vidoli & Guido Borà, 2015. "La spesa sanitaria delle Regioni in Italia - Saniregio 2015," Working Papers CERM 01-2015, Competitività, Regole, Mercati (CERM), revised 04 Jan 2016.
    • Handle: RePEc:ern:wpaper:01-2015
    Note: In queste pagine possono essere consultati i principali risultati del paper in maniera dinamica e interattiva: https://fondazionecerm.it/SaniRegio2015/
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    References listed on IDEAS

    as
    1. PARK, Byeong & SIMAR, Léopold, 1992. "Efficient semiparametric estimation in stochastic frontier model," LIDAM Discussion Papers CORE 1992013, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    2. Cinzia Daraio & Léopold Simar, 2005. "Introducing Environmental Variables in Nonparametric Frontier Models: a Probabilistic Approach," Journal of Productivity Analysis, Springer, vol. 24(1), pages 93-121, September.
    3. Francesco Vidoli & Giancarlo Ferrara, 2015. "Analyzing Italian citrus sector by semi-nonparametric frontier efficiency models," Empirical Economics, Springer, vol. 49(2), pages 641-658, September.
    4. Badin, Luiza & Daraio, Cinzia & Simar, Léopold, 2010. "Optimal bandwidth selection for conditional efficiency measures: A data-driven approach," European Journal of Operational Research, Elsevier, vol. 201(2), pages 633-640, March.
    5. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    6. De Witte, K. & Rogge, N., 2009. "Accounting for exogenous influences in a benevolent performance evaluation of teachers," Working Papers 15, Top Institute for Evidence Based Education Research.
    7. Cinzia Daraio & Léopold Simar, 2007. "Conditional nonparametric frontier models for convex and nonconvex technologies: a unifying approach," Journal of Productivity Analysis, Springer, vol. 28(1), pages 13-32, October.
    8. Pasquale De Muro & Matteo Mazziotta & Adriano Pareto, 2011. "Composite Indices of Development and Poverty: An Application to MDGs," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 104(1), pages 1-18, October.
    9. Cazals, Catherine & Florens, Jean-Pierre & Simar, Leopold, 2002. "Nonparametric frontier estimation: a robust approach," Journal of Econometrics, Elsevier, vol. 106(1), pages 1-25, January.
    10. Michela Nardo & Michaela Saisana & Andrea Saltelli & Stefano Tarantola & Anders Hoffman & Enrico Giovannini, 2005. "Handbook on Constructing Composite Indicators: Methodology and User Guide," OECD Statistics Working Papers 2005/3, OECD Publishing.
    11. Fabio Pammolli & Nicola Carmine Salerno, 2011. "Le differenze regionali nella governance della spesa sanitaria - SaniRegio-2011," Working Papers CERM 02-2011, Competitività, Regole, Mercati (CERM).
    12. Cherchye, Laurens & Knox Lovell, C.A. & Moesen, Wim & Van Puyenbroeck, Tom, 2007. "One market, one number? A composite indicator assessment of EU internal market dynamics," European Economic Review, Elsevier, vol. 51(3), pages 749-779, April.
    13. Simar, Leopold & Wilson, Paul W., 2007. "Estimation and inference in two-stage, semi-parametric models of production processes," Journal of Econometrics, Elsevier, vol. 136(1), pages 31-64, January.
    14. Laurens Cherchye & Wim Moesen & Tom Van Puyenbroeck, 2004. "Legitimately Diverse, yet Comparable: On Synthesizing Social Inclusion Performance in the EU," Journal of Common Market Studies, Wiley Blackwell, vol. 42(5), pages 919-955, December.
    15. Soonman Kwon, 2003. "Health and Health Care," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 62(1), pages 171-186, April.
    16. Despotis, D.K., 2005. "Measuring human development via data envelopment analysis: the case of Asia and the Pacific," Omega, Elsevier, vol. 33(5), pages 385-390, October.
    17. P.C. Smith, 2002. "Measuring health system performance," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 3(3), pages 145-148, September.
    18. Meeusen, Wim & van den Broeck, Julien, 1977. "Efficiency Estimation from Cobb-Douglas Production Functions with Composed Error," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 18(2), pages 435-444, June.
    19. Park, Byeong U. & Sickles, Robin C. & Simar, Leopold, 2007. "Semiparametric efficient estimation of dynamic panel data models," Journal of Econometrics, Elsevier, vol. 136(1), pages 281-301, January.
    20. Jenni P䤫könen & Timo T. Sepp䬤, 2014. "Using composite indicators to evaluate the efficiency of health care system," Applied Economics, Taylor & Francis Journals, vol. 46(19), pages 2242-2250, July.
    21. Andrew Johnson & Timo Kuosmanen, 2011. "One-stage estimation of the effects of operational conditions and practices on productive performance: asymptotically normal and efficient, root-n consistent StoNEZD method," Journal of Productivity Analysis, Springer, vol. 36(2), pages 219-230, October.
    22. Aigner, Dennis & Lovell, C. A. Knox & Schmidt, Peter, 1977. "Formulation and estimation of stochastic frontier production function models," Journal of Econometrics, Elsevier, vol. 6(1), pages 21-37, July.
    23. Storrie, Donald & Bjurek, Hans, 2000. "Benchmarking European labour market performance with efficiency frontier techniques," Discussion Papers, Research Unit: Labor Market Policy and Employment FS I 00-211, WZB Berlin Social Science Center.
    24. Timo Kuosmanen & Mika Kortelainen, 2012. "Stochastic non-smooth envelopment of data: semi-parametric frontier estimation subject to shape constraints," Journal of Productivity Analysis, Springer, vol. 38(1), pages 11-28, August.
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    Cited by:

    1. Dino Rizzi & Michele Zanette, 2021. "Potential efficiency gains and expenditure savings in the Italian Regional Healthcare Systems," Politica economica, Società editrice il Mulino, issue 2, pages 187-214.

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    More about this item

    Keywords

    federalismo; spesa sanitaria; piani di rientro; riparto fsn; proiezioni; regioni; sostenibilità; demografia; finanza pubblica; efficientamento spesa pubblica;
    All these keywords.

    JEL classification:

    • D60 - Microeconomics - - Welfare Economics - - - General
    • D61 - Microeconomics - - Welfare Economics - - - Allocative Efficiency; Cost-Benefit Analysis
    • H50 - Public Economics - - National Government Expenditures and Related Policies - - - General
    • H51 - Public Economics - - National Government Expenditures and Related Policies - - - Government Expenditures and Health
    • H70 - Public Economics - - State and Local Government; Intergovernmental Relations - - - General
    • H75 - Public Economics - - State and Local Government; Intergovernmental Relations - - - State and Local Government: Health, Education, and Welfare
    • H77 - Public Economics - - State and Local Government; Intergovernmental Relations - - - Intergovernmental Relations; Federalism
    • I10 - Health, Education, and Welfare - - Health - - - General
    • I11 - Health, Education, and Welfare - - Health - - - Analysis of Health Care Markets
    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health
    • I30 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - General
    • I31 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - General Welfare, Well-Being
    • I38 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Government Programs; Provision and Effects of Welfare Programs

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