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Relationships between Renewable Energy and the Prevalence of Morbidity in the Countries of the European Union: A Panel Regression Approach

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  • Robert Stefko

    (Faculty of Management, University of Prešov in Prešov, Konštantínova 16, 080 01 Prešov, Slovakia)

  • Beata Gavurova

    (Center for Applied Economic Research, Faculty of Management and Economics, Tomas Bata University in Zlín, Mostní 5139, 760 00 Zlín, Czech Republic)

  • Miroslav Kelemen

    (Faculty of Aeronautics, Technical University of Kosice, 041 21 Kosice, Slovakia)

  • Martin Rigelsky

    (Faculty of Management, University of Prešov in Prešov, Konštantínova 16, 080 01 Prešov, Slovakia)

  • Viera Ivankova

    (Faculty of Management, University of Prešov in Prešov, Konštantínova 16, 080 01 Prešov, Slovakia)

Abstract

The main objective of the presented study was to examine the associations between the use of renewable energy sources in selected sectors (transport, electricity, heating, and cooling) and the prevalence of selected groups of diseases in the European Union, with an emphasis on the application of statistical methods considering the structure of data. The analyses included data on 27 countries of the European Union from 2010 to 2019 published in the Eurostat database and the Global Burden of Disease Study. Panel regression models (pooling model, fixed (within) effects model, random effects model) were primarily used in analytical procedures, in which a panel variable was represented by countries. In most cases, positive and significant associations between the use of renewable energy sources and the prevalence of diseases were confirmed. The results of panel regression models could be generally interpreted as meaning that renewable energy sources are associated with the prevalence of diseases such as cardiovascular diseases, diabetes and kidney diseases, digestive diseases, musculoskeletal disorders, neoplasms, sense organ diseases, and skin and subcutaneous diseases at a significance level (α) of 0.05 and lower. These findings could be explained by the awareness of the health problem and the response in the form of preference for renewable energy sources. Regarding statistical methods used for country data or for data with a specific structure, it is recommended to use the methods that take this structure into account. The absence of these methods could lead to misleading conclusions.

Suggested Citation

  • Robert Stefko & Beata Gavurova & Miroslav Kelemen & Martin Rigelsky & Viera Ivankova, 2021. "Relationships between Renewable Energy and the Prevalence of Morbidity in the Countries of the European Union: A Panel Regression Approach," IJERPH, MDPI, vol. 18(12), pages 1-18, June.
    • Handle: RePEc:gam:jijerp:v:18:y:2021:i:12:p:6548-:d:577001
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    2. Jacek Brożyna & Wadim Strielkowski & Aleš Zpěvák, 2023. "Evaluating the Chances of Implementing the “Fit for 55” Green Transition Package in the V4 Countries," Energies, MDPI, vol. 16(6), pages 1-17, March.

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