IDEAS home Printed from https://ideas.repec.org/a/rfa/aefjnl/v4y2017i6p1-16.html
   My bibliography  Save this article

What Determines the Health Care Expenditure of High Income Countries? A Dynamic Estimation

Author

Listed:
  • Yan Feng
  • Toby Watt
  • Anita Charlesworth
  • Grace Marsden
  • Adam Roberts
  • Jon Sussex

Abstract

Constraining the rise in costs continues to be a major focus of health care policy in high income countries. It is important for governments to understand what is driving the rise in health care expenditure and what the impact will be over the coming years. This paper aims to provide an alternative econometric model to ascertain the determinants of health expenditure. Data from the OECD and IMS data bases for 18 OECD countries between 1988 and 2012 is collected. The analysis is at the year and country level. This study applies three methods: (1) panel data models with country fixed effects; (2) a first difference model; (3) a Vector Error Correction Model to account for the long run and short run effects as well as the endogeneity of the explanatory variables. The empirical results suggest that the use of different econometric specifications has a significant impact on both establishing the determinants of health expenditure and their magnitudes. Based on results from the Vector Error Correction Model, the GDP is considered as the only driver for country level health care expenditure growth. A 1% increase in the GDP is associated with a 1.1% increase in the health care expenditure.

Suggested Citation

  • Yan Feng & Toby Watt & Anita Charlesworth & Grace Marsden & Adam Roberts & Jon Sussex, 2017. "What Determines the Health Care Expenditure of High Income Countries? A Dynamic Estimation," Applied Economics and Finance, Redfame publishing, vol. 4(6), pages 1-16, November.
  • Handle: RePEc:rfa:aefjnl:v:4:y:2017:i:6:p:1-16
    as

    Download full text from publisher

    File URL: http://redfame.com/journal/index.php/aef/article/view/2586/2792
    Download Restriction: no

    File URL: http://redfame.com/journal/index.php/aef/article/view/2586
    Download Restriction: no

    References listed on IDEAS

    as
    1. Christine de la Maisonneuve & Rodrigo Moreno-Serra & Fabrice Murtin & Joaquim Oliveira Martins, 2016. "The drivers of public health spending: Integrating policies and institutions," OECD Economics Department Working Papers 1283, OECD Publishing.
    2. Dandan Liu & Rui Li & Zijun Wang, 2011. "Testing for structural breaks in panel varying coefficient models: with an application to OECD health expenditure," Empirical Economics, Springer, vol. 40(1), pages 95-118, February.
    3. 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.
    4. Hansen, Paul & King, Alan, 1996. "The determinants of health care expenditure: A cointegration approach," Journal of Health Economics, Elsevier, vol. 15(1), pages 127-137, February.
    5. Engle, Robert & Granger, Clive, 2015. "Co-integration and error correction: Representation, estimation, and testing," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 39(3), pages 106-135.
    6. Anindya Sen, 2005. "Is Health Care a Luxury? New Evidence from OECD Data," International Journal of Health Economics and Management, Springer, vol. 5(2), pages 147-164, June.
    7. Blomqvist, A. G. & Carter, R. A. L., 1997. "Is health care really a luxury?," Journal of Health Economics, Elsevier, vol. 16(2), pages 207-229, April.
    8. Christine de la Maisonneuve & Joaquim Oliveira Martins, 2013. "A Projection Method for Public Health and Long-Term Care Expenditures," OECD Economics Department Working Papers 1048, OECD Publishing.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

    health expenditure; OECD countries; time-series; vector error correction model;

    JEL classification:

    • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General
    • Z0 - Other Special Topics - - General

    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:rfa:aefjnl:v:4:y:2017:i:6:p:1-16. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Redfame publishing). General contact details of provider: http://edirc.repec.org/data/cepflch.html .

    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 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.