For policy purposes expenditure in health systems of extremely different natures are often compared without having a clear question to be addressed in such a comparison. For instance, comparisons made among OECD countries which have differing levels of development, and/or where the fusion of public and private finance differ; along with their sources of revenue, their finance levels and their degree of taxes and co-payments. Our objective in this paper is to analyze the factors that complicate international ...
For policy purposes expenditure in health systems of extremely different natures are often compared without having a clear question to be addressed in such a comparison. For instance, comparisons made among OECD countries which have differing levels of development, and/or where the fusion of public and private finance differ; along with their sources of revenue, their finance levels and their degree of taxes and co-payments. Our objective in this paper is to analyze the factors that complicate international comparisons of health care expenditure across countries. We comment on some of these issues and shows how results and the interpretation of the gaps differ according to the refinements we make to the sampling and sub-sampling, as well as the definition of the variables we adopt. We considered as dependent variables total and health care expenditure per capita and as a percentage of GDP with and without out-of-pocket payments. We analyse the (complete) OECD sample for the period 2000–2010, as well as three sub-samples (European Union, countries with the Bismark model and countries with the Beveridge model). After calculating the means of the dependent variables, both without weights and weighting by GDP and population, we specified two different panel data models to explain the variation in the dependent variables, including as explanatory variables those that are most likely to affect health expenditure. Although other countries are mentioned in this paper, we take Spain as our example. We show how the results and the consequent interpretations of the gaps can differ according to the refinements we introduce into the sample and sub-samples; akin to the adjustments we are willing to make to the definition of the variables we choose to adopt. We show how Spanish ratios, as example, are generally well above those expected. In conclusion, there is a need for a better understanding of the settings of any comparison, along with a more appropriate sub sampling of the systems being analyzed in order to align any demand to the financial capabilities of the health care sector.
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