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Is Post‐Communist Health Spending Unusual?

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  • János Kornai
  • John McHale

Abstract

What factors determine a country's spending on health? And what factors determine the share of spending financed by the public sector? Taking these factors into account, is post‐communist health spending unusual? For the OECD economies, we find that per capita health spending is strongly related to per capita income, with an elasticity of about 1.5. The elasticity for developing economies is close to one. Spending is also positively related to the elderly dependency rate, but the relationship is weaker than a static comparison of spending by the elderly and non‐elderly would suggest. Even though health spending as a share of GDP in the post‐communist countries of eastern and central Europe is below the OECD average, there is evidence of above normal health spending in most countries when we control for income and demographics. For Hungary, the ‘excess’ spending reached over three percentage points of GDP in 1994. For the OECD sample, four development indicators account for half the variation in the public sector share of total health spending. Political variables help explain the remainder. If the post‐communist countries converge to the market economy pattern, the share of public financing will fall, yet still remain well above half.

Suggested Citation

  • János Kornai & John McHale, 2000. "Is Post‐Communist Health Spending Unusual?," The Economics of Transition, The European Bank for Reconstruction and Development, vol. 8(2), pages 369-399, July.
  • Handle: RePEc:bla:etrans:v:8:y:2000:i:2:p:369-399
    DOI: 10.1111/1468-0351.00048
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    Cited by:

    1. John McHale, 2001. "The Risk of Social Security Benefit-Rule Changes: Some International Evidence," NBER Chapters, in: Risk Aspects of Investment-Based Social Security Reform, pages 247-290, National Bureau of Economic Research, Inc.
    2. Lackó, Mária, 2020. "Korai és időskori halálozások különbségei Európában a 2000-es évek első évtizedében [Disparities in Europes premature and old-age mortality in the first decade of the 2000s]," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(10), pages 957-992.
    3. Mária Lackó, 2016. "Disparities in Mortality Rates of Working-Age Population in Eastern, Central and Western Europe - A Comparative Quantitative Analysis," DANUBE: Law and Economics Review, European Association Comenius - EACO, issue 4, pages 193-213, December.
    4. Lackó, Mária, 2016. "Eltérések a kelet-közép- és a nyugat-európai országok halálozási rátái között. A meghatározó okok kvantitatív elemzése [Differences in death rates between East-Central and Western European countrie," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(12), pages 1324-1347.
    5. Dov Chernichovsky, 2001. "A Fuzzy Logic Approach Toward Solving the Analytic Maze of Health System Financing," NBER Working Papers 8470, National Bureau of Economic Research, Inc.

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