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The Impact Of Income Inequality On Mortality In The European Union

Author

Listed:
  • Gheorghița Dincă

    (Transilvania University of Brasov, Faculty of Economic Sciences and Business Administration, Brasov, Romania)

  • Camelia Negri

    (Transilvania University of Brasov, Faculty of Economic Sciences and Business Administration, Brasov, Romania)

  • Mariana Cassiana Ioniță

    (Transilvania University of Brasov, Faculty of Economic Sciences and Business Administration, Brasov, Romania)

Abstract

Our paper aims to determine the correlation between income inequality and mortality, within the European Union, using a fixed-effects regression model. We studied the influence of inequality on population health using a panel database, which includes the 28 Member States of the European Union, for the 2000-2018 period. After regressing our logarithmic variables and performing the main statistical tests, we determined that, as a whole, the explanatory variables considered in our model significantly influence life expectancy at birth, while at an individual level, only GDP per capita and the level of education have a significant influence on life expectancy variable. The statistical tests’ results show that, from a mathematical point of view, the Gini coefficient, which reflects income inequality, does not influence life expectancy at birth. However, the Gini coefficient was not excluded from the model, given the importance it has from a theoretical point of view.

Suggested Citation

  • Gheorghița Dincă & Camelia Negri & Mariana Cassiana Ioniță, 2020. "The Impact Of Income Inequality On Mortality In The European Union," Annals of University of Craiova - Economic Sciences Series, University of Craiova, Faculty of Economics and Business Administration, vol. 2(48), pages 5-17, December.
    • Handle: RePEc:aio:aucsse:v:2:y:2020:i:48:p:5-17
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    File URL: http://feaa.ucv.ro/annals/v2_2020/001.pdf
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    References listed on IDEAS

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    More about this item

    Keywords

    Income inequality; mortality; Gini coefficient; panel data; fixed effects regression;
    All these keywords.

    JEL classification:

    • I14 - Health, Education, and Welfare - - Health - - - Health and Inequality
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

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