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Does voluntary health insurance improve health and longevity? Evidence from European OECD countries

The European Journal of Health Economics volume 23, pages 1397–1411 (2022)Cite this article

Abstract

The financing structure of the healthcare system and, particularly, the voluntary health insurance (VHI) constituent, has been a vital pillar in improving the overall quality of life. Consequently, this study aims to shed light on the effect of VHI on the population’s health and longevity in a sample of 26 European OECD countries. The methodology employed covers both hierarchical clustering and the novel dynamic panel threshold technique. First, the descriptive cluster analysis unveils a delimitation of the countries into four main groups with respect to a broad set of health status indicators. Second, the estimates show that VHI is a significant determinant of health and longevity. More specifically, we find that the relationship between variables is characterized by a threshold effect, whose estimated value is roughly 6.3% of the total healthcare financing. Also, the heterogeneity analysis unveils consistent differences regarding the impact of VHI on health and longevity for the supplementary and complementary types of VHI. Overall, results are strongly robust, the signs and the significance of the coefficients being preserved in the presence of several additional control factors. From a policy perspective, the study’s findings can be used nationwide to stimulate regulatory policies to encourage the achievement of a satisfactory level of private health insurance.

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Fig. 1

Notes

  1. For example, on the one hand, in OECD countries one of the most well-known National Health Service (NHS) is found in the UK, where English residents receive free healthcare services. On the other hand, the first social health insurance system in the world emerged in Germany, being characterized by the solidarity principle. Also, social health insurance schemes do exist in OECD countries such as Austria, France, and the Slovak Republic, among others.

  2. Due to the lack of sufficient available data, we are not able to control for smoking.

  3. Highest mean Rand index, measure of similarity between two data clustering.

  4. Average linkage, single linkage, or complete linkage.

  5. Except when there are large differences among cluster size.

  6. The analysis of variance (ANOVA).

  7. Although the variable VEGETABLES would have been of real interest as a control factor, we preferred not to introduce it in the regressions due to data inconsistency. For some countries, there are very severe/sharp increases or decreases from one year to another. Indeed, these fluctuations are quite difficult to explain and are rather due to changes in the estimation methodology for the national supply. Thus, given that the dependent variable does not encounter such unexpected annual variations, their presence for the VEGETABLES variable could considerably skew the panel data estimates. However, in the cluster analysis this inconvenience is diminished, as we used the multiannual averages of the variables for the analyzed period.

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Acknowledgements

We are grateful to the editor (Wolfgang Greiner) and two anonymous referees for very valuable comments and suggestions. All the remaining errors are ours. Usual disclaimers apply.

Funding

This work was funded by a grant of the Romanian Ministry of Education and Research, CNCS-UEFISCDI, project number PN-III-P1-1.1-TE-2019-0554, within PNCDI III.

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Authors and Affiliations

  1. Department of Finance, Faculty of Economics and Business Administration, Babeș-Bolyai University, 58-60, Teodor Mihali str., 400591, Cluj-Napoca, Romania

    Simona Laura Dragos & Gabriela Mihaela Muresan

  2. Department of Statistics-Forecasts-Mathematics, Faculty of Economics and Business Administration, Babeș-Bolyai University, 58-60, Teodor Mihali str., 400591, Cluj-Napoca, Romania

    Codruta Mare, Cristian Mihai Dragos & Alexandra-Anca Purcel

  3. Interdisciplinary Centre for Data Science, Babeș-Bolyai University, 68, Avram Iancu str., 4th floor, 400083, Cluj-Napoca, Romania

    Codruta Mare

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  1. Simona Laura Dragos
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  2. Codruta Mare
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Correspondence to Codruta Mare.

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No conflict of interest arose in relationship to the present research. All data used are publicly privided by international institutions (we provide the sources of data in the article) and are available upon request. We use a publicly available application—the dtp package in R, developed for dynamic threshold panel.

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Dragos, S.L., Mare, C., Dragos, C.M. et al. Does voluntary health insurance improve health and longevity? Evidence from European OECD countries. Eur J Health Econ 23, 1397–1411 (2022). https://doi.org/10.1007/s10198-022-01439-9

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  • DOI: https://doi.org/10.1007/s10198-022-01439-9

Keywords

  • Private health insurance
  • Health financing
  • Burden of disease (DALY)
  • Life expectancy
  • Corruption
  • Risk factors

JEL Classification

  • I130
  • I120
  • C23