Public funding of social protection: Impact on social indicators in Eurozone countries

  • Received April 17, 2021;
    Accepted May 18, 2021;
    Published May 28, 2021
  • Author(s)
  • DOI
    http://dx.doi.org/10.21511/imfi.18(2).2021.15
  • Article Info
    Volume 18 2021, Issue #2, pp. 181-192
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This work is licensed under a Creative Commons Attribution 4.0 International License

Social protection has long been a relevant subject of scientific debate. Its development is interrelated with the study of fiscal factors (collection of social contributions), establishment of major social protection vectors, and confirmation of hypotheses about the link between social protection policy and the resulting socio-economic indicators.
The purpose of the paper is to study the impact of public funding of social protectionon social indicatorsusing the example of Eurozone countries. To this end, a number of economic and mathematical methods of analysis were applied to process panel data of seventeen countries for the last fifteen years, including the calculation of the relative rate of variation, regression dependence statistics, and cluster analysis.
The study established the irrelevance between the scope of the fundingof spending on social protection and social contributions (coefficient of determination R2=0.255). As illustrated, social indicators are determined not only by the amount of funding of social spending, but also by the structure of the social protection system, in particular, the focus on assistance to families with children and disability compensation (coefficient of determination R2>0.3). The general level of public funding for social spending items results in the 69% income inequality index andis behind 58% of non-economic parameters affecting life quality. The information outlined in the papercan serve as a basis for the formation of social and budgetary policy, as well as the revision of the structure and scope of social protection funding toensure an efficient impact on the quality of life of the population.

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    • Figure 1. Country dendrogram for social spending and the Gini coefficient
    • Figure 2. Country dendrogram based on social spending indicators and the social progress index
    • Table 1. Average values of the scope of social spending for 2005–2019 and the Gini coefficient and social progress index for 2019
    • Table 2. Evaluation of the stability of the panel series of the Gini coefficient data for 2005–2019
    • Table 3. Coefficients of determination based on the social security contributions and social spending data
    • Table 4. Composition of clusters based on the indicators of the scope of social spending and the Gini coefficient and their average values
    • Table 5. Cluster composition based on social spending scope indicators and the social progress index and their average values
    • Table 6. Matrix of pair correlation indices ofthe Gini coefficient (у1) and social spending items
    • Table 7. Matrix of pair correlation indices of the social progress index (у2) and social spending items
    • Table 8. Regression statistics for the concurrent impact of the scope of funding for social spending items on social indicators
    • Conceptualization
      Igor Chugunov
    • Data curation
      Igor Chugunov
    • Investigation
      Igor Chugunov
    • Methodology
      Igor Chugunov
    • Software
      Igor Chugunov
    • Supervision
      Igor Chugunov
    • Writing – original draft
      Igor Chugunov
    • Formal Analysis
      Olha Nasibova
    • Funding acquisition
      Olha Nasibova
    • Project administration
      Olha Nasibova
    • Resources
      Olha Nasibova
    • Validation
      Olha Nasibova
    • Visualization
      Olha Nasibova
    • Writing – review & editing
      Olha Nasibova