IDEAS home Printed from https://ideas.repec.org/a/spr/empeco/v56y2019i3d10.1007_s00181-017-1372-9.html
   My bibliography  Save this article

The determinants of individual health care expenditures in the Italian region of Friuli Venezia Giulia: evidence from a hierarchical spatial model estimation

Author

Listed:
  • Luca Grassetti

    (University of Udine)

  • Laura Rizzi

    (University of Udine)

Abstract

This work investigates the determinants of health care expenditures, such as drug prescriptions, inpatient care, and outpatient care, of the resident population of the Region of Friuli Venezia Giulia (Italy). The phenomenon of interest is examined here by considering a cross-sectional register-based dataset on individual expenditures exhibiting a cross-classified hierarchical structure. In fact, patients (about 1,000,000) are grouped by general practitioners and municipalities. Does the evidence in individual data analyses support the results of the micro- and macroeconomic literature? The adoption of disaggregated data allows us to disentangle the role of the micro- and macroeconomic determinants of the expenditures. Moreover, the degree of interdependence between neighbouring municipalities is measured by accounting for the spatial correlation in the error convolution. A feasible two-stage Heckit method has to be adapted to encompass the zero-inflation issue, to consider the hierarchical structure of data and to study the spatial diffusion process of the expenditures in the sample selection model framework. The main results on the determinants of health care expenditures at the macro-level are confirmed in our analysis on disaggregated data. On the contrary, however, the substitution effect, which is typically observed in aggregated data, has not been confirmed by the present research. Moreover, the selection process appears to be relevant in drug prescriptions and outpatient care expenditures and a significant spatial correlation in both the selection and the outcome equations emerges from the structure of error components.

Suggested Citation

  • Luca Grassetti & Laura Rizzi, 2019. "The determinants of individual health care expenditures in the Italian region of Friuli Venezia Giulia: evidence from a hierarchical spatial model estimation," Empirical Economics, Springer, vol. 56(3), pages 987-1009, March.
  • Handle: RePEc:spr:empeco:v:56:y:2019:i:3:d:10.1007_s00181-017-1372-9
    DOI: 10.1007/s00181-017-1372-9
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s00181-017-1372-9
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s00181-017-1372-9?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Gerdtham, Ulf-G. & Jonsson, Bengt, 2000. "International comparisons of health expenditure: Theory, data and econometric analysis," Handbook of Health Economics, in: A. J. Culyer & J. P. Newhouse (ed.), Handbook of Health Economics, edition 1, volume 1, chapter 1, pages 11-53, Elsevier.
    2. Margherita Giannoni & Theodore Hitiris, 2002. "The regional impact of health care expenditure: the case of Italy," Applied Economics, Taylor & Francis Journals, vol. 34(14), pages 1829-1836.
    3. Albouy, Valerie & Davezies, Laurent & Debrand, Thierry, 2010. "Health expenditure models: A comparison using panel data," Economic Modelling, Elsevier, vol. 27(4), pages 791-803, July.
    4. Joan Costa‐Font & Jordi Pons‐Novell, 2007. "Public health expenditure and spatial interactions in a decentralized national health system," Health Economics, John Wiley & Sons, Ltd., vol. 16(3), pages 291-306, March.
    5. Partha Deb & Murat K. Munkin & Pravin K. Trivedi, 2006. "Bayesian analysis of the two‐part model with endogeneity: application to health care expenditure," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(7), pages 1081-1099, November.
    6. Martins, Thiago G. & Simpson, Daniel & Lindgren, Finn & Rue, Håvard, 2013. "Bayesian computing with INLA: New features," Computational Statistics & Data Analysis, Elsevier, vol. 67(C), pages 68-83.
    7. Rainer Winkelmann, 2012. "Copula Bivariate Probit Models: With An Application To Medical Expenditures," Health Economics, John Wiley & Sons, Ltd., vol. 21(12), pages 1444-1455, December.
    8. Jay Helms & Jospeh P. Newhouse & Charles E. Phelps, 1978. "Copayments and Demand for Medical Care: The California Medicaid Experience," Bell Journal of Economics, The RAND Corporation, vol. 9(1), pages 192-208, Spring.
    9. Heckman, James, 2013. "Sample selection bias as a specification error," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 31(3), pages 129-137.
    10. Baltagi, Badi H. & Moscone, Francesco, 2010. "Health care expenditure and income in the OECD reconsidered: Evidence from panel data," Economic Modelling, Elsevier, vol. 27(4), pages 804-811, July.
    11. Gerdtham, Ulf-G. & Sogaard, Jes & Andersson, Fredrik & Jonsson, Bengt, 1992. "An econometric analysis of health care expenditure: A cross-section study of the OECD countries," Journal of Health Economics, Elsevier, vol. 11(1), pages 63-84, May.
    12. Donald Freeman, 2003. "Is health care a necessity or a luxury? Pooled estimates of income elasticity from US state-level data," Applied Economics, Taylor & Francis Journals, vol. 35(5), pages 495-502.
    13. Madden, David, 2008. "Sample selection versus two-part models revisited: The case of female smoking and drinking," Journal of Health Economics, Elsevier, vol. 27(2), pages 300-307, March.
    14. Eibich, Peter & Ziebarth, Nicolas, 2014. "Examining the Structure of Spatial Health Effects in Germany Using Hierarchical Bayes Models," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 49, pages 305-320.
    15. Joseph P. Newhouse, 1992. "Medical Care Costs: How Much Welfare Loss?," Journal of Economic Perspectives, American Economic Association, vol. 6(3), pages 3-21, Summer.
    16. Julian Besag & Jeremy York & Annie Mollié, 1991. "Bayesian image restoration, with two applications in spatial statistics," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 43(1), pages 1-20, March.
    17. Moscone, Francesco & Knapp, Martin & Tosetti, Elisa, 2007. "Mental health expenditure in England: A spatial panel approach," Journal of Health Economics, Elsevier, vol. 26(4), pages 842-864, July.
    18. Andreas Werblow & Stefan Felder & Peter Zweifel, 2007. "Population ageing and health care expenditure: a school of ‘red herrings’?," Health Economics, John Wiley & Sons, Ltd., vol. 16(10), pages 1109-1126, October.
    19. Albert Wong & Pieter H. M. van Baal & Hendriek C. Boshuizen & Johan J. Polder, 2011. "Exploring the influence of proximity to death on disease‐specific hospital expenditures: a carpaccio of red herrings," Health Economics, John Wiley & Sons, Ltd., vol. 20(4), pages 379-400, April.
    20. Deb, Partha & Trivedi, Pravin K., 2002. "The structure of demand for health care: latent class versus two-part models," Journal of Health Economics, Elsevier, vol. 21(4), pages 601-625, July.
    21. Leung, Siu Fai & Yu, Shihti, 1996. "On the choice between sample selection and two-part models," Journal of Econometrics, Elsevier, vol. 72(1-2), pages 197-229.
    22. Håvard Rue & Sara Martino & Nicolas Chopin, 2009. "Approximate Bayesian inference for latent Gaussian models by using integrated nested Laplace approximations," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 71(2), pages 319-392, April.
    23. Angulo, Ana María & Barberán, Ramón & Egea, Pilar & Mur, Jesús, 2011. "An analysis of health expenditure on a microdata population basis," Economic Modelling, Elsevier, vol. 28(1-2), pages 169-180, January.
    24. Frank R. Lichtenberg, 2007. "The Impact of New Drugs on US Longevity and Medical Expenditure, 1990–2003: Evidence from Longitudinal, Disease-Level Data," American Economic Review, American Economic Association, vol. 97(2), pages 438-443, May.
    25. Guillem Lopez‐Casasnovas & Joan Costa‐Font & Ivan Planas, 2005. "Diversity and regional inequalities in the Spanish ‘system of health care services’," Health Economics, John Wiley & Sons, Ltd., vol. 14(S1), pages 221-235, September.
    26. Anselin, Luc, 2002. "Under the hood : Issues in the specification and interpretation of spatial regression models," Agricultural Economics, Blackwell, vol. 27(3), pages 247-267, November.
    27. Francesco Moscone, 2011. "Geographical variations in expenditure of learning disability services in England," Applied Economics, Taylor & Francis Journals, vol. 43(23), pages 2997-3005.
    28. Getzen, Thomas E., 2000. "Health care is an individual necessity and a national luxury: applying multilevel decision models to the analysis of health care expenditures," Journal of Health Economics, Elsevier, vol. 19(2), pages 259-270, March.
    29. Di Matteo, Livio & Di Matteo, Rosanna, 1998. "Evidence on the determinants of Canadian provincial government health expenditures: 1965-1991," Journal of Health Economics, Elsevier, vol. 17(2), pages 211-228, April.
    30. David J. Spiegelhalter & Nicola G. Best & Bradley P. Carlin & Angelika Van Der Linde, 2002. "Bayesian measures of model complexity and fit," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(4), pages 583-639, October.
    31. Zijun Wang, 2009. "The determinants of health expenditures: evidence from US state-level data," Applied Economics, Taylor & Francis Journals, vol. 41(4), pages 429-435.
    32. Moulton, Brent R, 1990. "An Illustration of a Pitfall in Estimating the Effects of Aggregate Variables on Micro Unit," The Review of Economics and Statistics, MIT Press, vol. 72(2), pages 334-338, May.
    33. Deb, Partha & Trivedi, Pravin K, 1997. "Demand for Medical Care by the Elderly: A Finite Mixture Approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 12(3), pages 313-336, May-June.
    34. Buntin, Melinda Beeuwkes & Zaslavsky, Alan M., 2004. "Too much ado about two-part models and transformation?: Comparing methods of modeling Medicare expenditures," Journal of Health Economics, Elsevier, vol. 23(3), pages 525-542, May.
    Full references (including those not matched with items on IDEAS)

    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. Caravaggio, Nicola & Resce, Giuliano, 2023. "Enhancing Healthcare Cost Forecasting: A Machine Learning Model for Resource Allocation in Heterogeneous Regions," Economics & Statistics Discussion Papers esdp23090, University of Molise, Department of Economics.
    2. Joan Costa-Font & Marin Gemmill & Gloria Rubert, 2008. "Re-visiting the Health Care Luxury Good Hypothesis: Aggregation, Precision, and Publication Biases?," Working Papers in Economics 197, Universitat de Barcelona. Espai de Recerca en Economia.
    3. Vandersteegen, Tom & Marneffe, Wim & Cleemput, Irina & Vereeck, Lode, 2015. "The impact of no-fault compensation on health care expenditures: An empirical study of OECD countries," Health Policy, Elsevier, vol. 119(3), pages 367-374.
    4. Felipa de Mello-Sampayo & Sofia de Sousa-Vale, 2014. "Financing Health Care Expenditure in the OECD Countries: Evidence from a Heterogeneous, Cross-Sectional Dependent Panel," Panoeconomicus, Savez ekonomista Vojvodine, Novi Sad, Serbia, vol. 61(2), pages 207-225.
    5. Muhammad Arshad Khan & Muhammad Iftikhar Ul Husnain, 2019. "Is health care a luxury or necessity good? Evidence from Asian countries," International Journal of Health Economics and Management, Springer, vol. 19(2), pages 213-233, June.
    6. Eibich, Peter & Ziebarth, Nicolas, 2014. "Examining the Structure of Spatial Health Effects in Germany Using Hierarchical Bayes Models," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 49, pages 305-320.
    7. Felipa de Mello-Sampayo & Sofia de Sousa-Vale, 2014. "Financing Health Care Expenditure in the OECD Countries: Evidence from a Heterogeneous, Cross-Sectional Dependent Panel," Panoeconomicus, Savez ekonomista Vojvodine, Novi Sad, Serbia, vol. 61(2), pages 207-225, March.
    8. Badi H. Baltagi & Raffaele Lagravinese & Francesco Moscone & Elisa Tosetti, 2017. "Health Care Expenditure and Income: A Global Perspective," Health Economics, John Wiley & Sons, Ltd., vol. 26(7), pages 863-874, July.
    9. Yihua Yu & Li Zhang & Fanghua Li & Xinye Zheng, 2013. "Strategic interaction and the determinants of public health expenditures in China: a spatial panel perspective," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 50(1), pages 203-221, February.
    10. Di Matteo, Livio & Cantarero-Prieto, David, 2018. "The Determinants of Public Health Expenditures: Comparing Canada and Spain," MPRA Paper 87800, University Library of Munich, Germany.
    11. Baltagi, Badi H. & Moscone, Francesco, 2010. "Health care expenditure and income in the OECD reconsidered: Evidence from panel data," Economic Modelling, Elsevier, vol. 27(4), pages 804-811, July.
    12. Nilgun Yavuz & Veli Yilanci & Zehra Ozturk, 2013. "Is health care a luxury or a necessity or both? Evidence from Turkey," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 14(1), pages 5-10, February.
    13. Hartwig, Jochen, 2008. "What drives health care expenditure?--Baumol's model of 'unbalanced growth' revisited," Journal of Health Economics, Elsevier, vol. 27(3), pages 603-623, May.
    14. Yuping Tsai, 2018. "Social Security Income and Health Care Spending: Evidence from the Social Security Notch," Scandinavian Journal of Economics, Wiley Blackwell, vol. 120(2), pages 440-464, April.
    15. Ben Brewer & Karen Smith Conway & Deniz Ozabaci & Robert S. Woodward, 2022. "US Health Care Expenditures, GDP and Health Policy Reforms: Evidence from End-of-Sample Structural Break Tests," Eastern Economic Journal, Palgrave Macmillan;Eastern Economic Association, vol. 48(4), pages 451-487, October.
    16. Mehdi Barati & Hadiseh Fariditavana, 2020. "Asymmetric effect of income on the US healthcare expenditure: evidence from the nonlinear autoregressive distributed lag (ARDL) approach," Empirical Economics, Springer, vol. 58(4), pages 1979-2008, April.
    17. Vitor Castro, 2017. "Pure, White and Deadly… Expensive: A Bitter Sweetness in Health Care Expenditure," Health Economics, John Wiley & Sons, Ltd., vol. 26(12), pages 1644-1666, December.
    18. Barkat, Karim & Sbia, Raschid & Maouchi, Youcef, 2019. "Empirical evidence on the long and short run determinants of health expenditure in the Arab world," The Quarterly Review of Economics and Finance, Elsevier, vol. 73(C), pages 78-87.
    19. repec:dau:papers:123456789/7972 is not listed on IDEAS
    20. Jin Feng & Pingyi Lou & Yangyang Yu, 2015. "Health Care Expenditure over Life Cycle in the People's Republic of China," Asian Development Review, MIT Press, vol. 32(1), pages 167-195, March.
    21. DO ANGO, Simplicio & AMBA OYON, Claude Marius, 2016. "Health expenditure and Real disposable Income in the ECCAS: A Causal Study using spatial panel approach," MPRA Paper 79684, University Library of Munich, Germany.

    More about this item

    Keywords

    Health care expenditures; Health econometrics; INLA; Multilevel models; Sample selection; Spatial econometrics;
    All these keywords.

    JEL classification:

    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • H75 - Public Economics - - State and Local Government; Intergovernmental Relations - - - State and Local Government: Health, Education, and Welfare
    • I11 - Health, Education, and Welfare - - Health - - - Analysis of Health Care Markets
    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health

    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:spr:empeco:v:56:y:2019:i:3:d:10.1007_s00181-017-1372-9. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.