IDEAS home Printed from https://ideas.repec.org/p/ern/wpaper/01-2015.html
   My bibliography  Save this paper

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/
    as

    Download full text from publisher

    File URL: https://fondazionecerm.it/wp-content/uploads/wp/wpcerm-2015-01.pdf
    File Function: First version, 2015
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. 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.
    3. 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).
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. 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).
    11. 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.
    12. 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.
    13. 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.
    14. 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.
    15. 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.
    16. 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.
    17. 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.
    18. 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.
    19. 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.
    20. 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.
    21. 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.
    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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Fabio Pammolli & Francesco Porcelli & Francesco Vidoli & Guido Borà, 2014. "La spesa sanitaria delle Regioni in Italia - Saniregio 3," Working Papers CERM 02-2014, Competitività, Regole, Mercati (CERM).
    2. Fabio Pammolli & Francesco Porcelli & Francesco Vidoli & Monica Auteri & Guido Borà, 2017. "La spesa sanitaria delle Regioni in Italia - Saniregio2017," Working Papers CERM 01-2017, Competitività, Regole, Mercati (CERM).
    3. Francesco Vidoli & Elisa Fusco & Claudio Mazziotta, 2015. "Non-compensability in Composite Indicators: A Robust Directional Frontier Method," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 122(3), pages 635-652, July.
    4. Léopold Simar & Paul W. Wilson, 2015. "Statistical Approaches for Non-parametric Frontier Models: A Guided Tour," International Statistical Review, International Statistical Institute, vol. 83(1), pages 77-110, April.
    5. Gil, Guilherme Dôco Roberti & Costa, Marcelo Azevedo & Lopes, Ana Lúcia Miranda & Mayrink, Vinícius Diniz, 2017. "Spatial statistical methods applied to the 2015 Brazilian energy distribution benchmarking model: Accounting for unobserved determinants of inefficiencies," Energy Economics, Elsevier, vol. 64(C), pages 373-383.
    6. Fusco, Elisa & Vidoli, Francesco & Sahoo, Biresh K., 2018. "Spatial heterogeneity in composite indicator: A methodological proposal," Omega, Elsevier, vol. 77(C), pages 1-14.
    7. Bjørndal, Endre & Bjørndal, Mette & Cullmann, Astrid & Nieswand, Maria, 2018. "Finding the right yardstick: Regulation of electricity networks under heterogeneous environments," European Journal of Operational Research, Elsevier, vol. 265(2), pages 710-722.
    8. Nieswand, Maria & Seifert, Stefan, 2018. "Environmental factors in frontier estimation – A Monte Carlo analysis," European Journal of Operational Research, Elsevier, vol. 265(1), pages 133-148.
    9. Fusco, Elisa, 2015. "Enhancing non-compensatory composite indicators: A directional proposal," European Journal of Operational Research, Elsevier, vol. 242(2), pages 620-630.
    10. Maria Nieswand & Stefan Seifert, 2016. "Operational Conditions in Regulatory Benchmarking Models: A Monte Carlo Analysis," Discussion Papers of DIW Berlin 1585, DIW Berlin, German Institute for Economic Research.
    11. De la Cruz, Marco & Mergoni, Anna, 2024. "Assessing the performance of Peruvian education system from a governance perspective," Socio-Economic Planning Sciences, Elsevier, vol. 93(C).
    12. Kristof Witte & Nicky Rogge, 2010. "To publish or not to publish? On the aggregation and drivers of research performance," Scientometrics, Springer;Akadémiai Kiadó, vol. 85(3), pages 657-680, December.
    13. Isabel Narbón-Perpiñá & Kristof De Witte, 2016. "Local governments’ efficiency: A systematic literature review – Part I," Working Papers 2016/20, Economics Department, Universitat Jaume I, Castellón (Spain).
    14. Nguyen, Trang T.T. & Prior, Diego & Van Hemmen, Stefan, 2020. "Stochastic semi-nonparametric frontier approach for tax administration efficiency measure: Evidence from a cross-country study," Economic Analysis and Policy, Elsevier, vol. 66(C), pages 137-153.
    15. Agasisti, Tommaso & Egorov, Aleksei & Serebrennikov, Pavel, 2023. "Universities’ efficiency and the socioeconomic characteristics of their environment — Evidence from an empirical analysis," Socio-Economic Planning Sciences, Elsevier, vol. 85(C).
    16. Jose M. Cordero & Cristina Polo & Daniel Santín, 2020. "Assessment of new methods for incorporating contextual variables into efficiency measures: a Monte Carlo simulation," Operational Research, Springer, vol. 20(4), pages 2245-2265, December.
    17. Massimo Finocchiaro Castro & Calogero Guccio & Ilde Rizzo, 2014. "An assessment of the waste effects of corruption on infrastructure provision," International Tax and Public Finance, Springer;International Institute of Public Finance, vol. 21(4), pages 813-843, August.
    18. Eskelinen, Juha & Kuosmanen, Timo, 2013. "Intertemporal efficiency analysis of sales teams of a bank: Stochastic semi-nonparametric approach," Journal of Banking & Finance, Elsevier, vol. 37(12), pages 5163-5175.
    19. Ferrara, Giancarlo & Vidoli, Francesco, 2017. "Semiparametric stochastic frontier models: A generalized additive model approach," European Journal of Operational Research, Elsevier, vol. 258(2), pages 761-777.
    20. José Manuel Cordero & Cristina Polo & Daniel Santín & Gabriela Sicilia, 2016. "Monte-Carlo Comparison of Conditional Nonparametric Methods and Traditional Approaches to Include Exogenous Variables," Pacific Economic Review, Wiley Blackwell, vol. 21(4), pages 483-497, October.

    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

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ern:wpaper:01-2015. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Guido Bora` (email available below). General contact details of provider: https://edirc.repec.org/data/cermmit.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.