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A multilevel analysis on the determinants of regional health care expenditure. A note

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Abstract

We apply a multilevel hierarchical model to explore whether an aggregation fallacy exists in estimating the income elasticity of health expenditure by ignoring the regional composition of national health expenditure figures. We use data for 110 regions in eight OECD countries in 1997: Australia, Canada, France, Germany, Italy, Spain, Sweden and United Kingdom. In doing this we have tried to identify two sources of random variation: within countries and between-countries. Our results show that: 1- Variability between countries amounts to (SD) 0.5433, and just 13% of that can be attributed to income elasticity and the remaining 87% to autonomous health expenditure; 2- Within countries, variability amounts to (SD) 1.0249; and 3- The intra-class correlation is 0.5300. We conclude that we have to take into account the degree of fiscal decentralisation within countries in estimating income elasticity of health expenditure. Two reasons lie behind this: a) where there is decentralisation to the regions, policies aimed at emulating diversity tend to increase national health care expenditure; and b) without fiscal decentralisation, central monitoring of finance tends to reduce regional diversity and therefore decrease national health expenditure.

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  • Guillem López & Marc Sáez, 2001. "A multilevel analysis on the determinants of regional health care expenditure. A note," Working Papers, Research Center on Health and Economics 572, Department of Economics and Business, Universitat Pompeu Fabra.
    • Handle: RePEc:upf:upfses:572
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    1. Andree Ehlert & Dirk Oberschachtsiek & Stefan Prawda, 2013. "Cost Containment and Managed Care: Evidence from German Macro Data," Working Paper Series in Economics 284, University of Lüneburg, Institute of Economics.
    2. 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.
    3. Pelin Varol İYIDOĞAN & Eda BALIKÇIOĞLU & H. Hakan YILMAZ, 2017. "The Tax Effects of Health Expenditures on Aging Economies: Empirical Evidence on Selected OECD Countries," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 116-127, March.
    4. Giardina, Emilio & Cavalieri, Marina & Guccio, Calogero & Mazza, Isidoro, 2009. "Federalism, Party Competition and Budget Outcome: Empirical Findings on Regional Health Expenditure in Italy," MPRA Paper 16437, University Library of Munich, Germany.
    5. Engy Raouf, 2023. "Green Hydrogen Production and Public Health Expenditure in Hydrogen-Exporting Countries," International Journal of Energy Economics and Policy, Econjournals, vol. 13(6), pages 36-44, November.
    6. Jorgen Lauridsen & Mariluz Sánchez & Mickael Bech, 2010. "Public pharmaceutical expenditure: identification of spatial effects," Journal of Geographical Systems, Springer, vol. 12(2), pages 175-188, June.
    7. repec:rre:publsh:v:38:y:2008:i:1:p:89-103 is not listed on IDEAS
    8. Yonsu Kim & Jae Hong Kim, 2022. "What drives variations in public health and social services expenditures? the association between political fragmentation and local expenditure patterns," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 23(5), pages 781-789, July.
    9. 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.
    10. Andree Ehlert & Dirk Oberschachtsiek, 2014. "Does managed care reduce health care expenditure? Evidence from spatial panel data," International Journal of Health Economics and Management, Springer, vol. 14(3), pages 207-227, September.
    11. 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.
    12. Alessandra Cepparulo & Luisa Giuriato, 2022. "The residential healthcare for the elderly in Italy: some considerations for post-COVID-19 policies," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 23(4), pages 671-685, June.
    13. 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.
    14. David Prieto & Santiago Lago-Peñas, 2012. "Decomposing the determinants of health care expenditure: the case of Spain," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 13(1), pages 19-27, February.
    15. Jorgen Lauridsen & Mickael Bech & Fernando López & Mariluz Sánchez, 2010. "A spatiotemporal analysis of public pharmaceutical expenditure," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 44(2), pages 299-314, April.

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    More about this item

    Keywords

    OECD health expenditure; fiscal federalism; multilevel hierarchical models;
    All these keywords.

    JEL classification:

    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health
    • H51 - Public Economics - - National Government Expenditures and Related Policies - - - Government Expenditures and Health
    • E62 - Macroeconomics and Monetary Economics - - Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook - - - Fiscal Policy; Modern Monetary Theory
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation

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