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Influence falling income inequality for social stability: Case study of four European countries.

  • Published In: Analyses of Social Issues & Public Policy, 2024, v. 24, n. 3. P. 691 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Wan, Liqun; Wu, Yajun 3 of 3

Abstract

This study aims to assess the relationship between income inequality and social solidarity as a measure of societal stability, using European countries as a case study. Data from 20 European countries were included in the research. The primary dependent variable was defined as social solidarity, serving as an indicator of societal stability. The analysis of social solidarity was conducted concerning various social groups, including overall solidarity and solidarity towards vulnerable societal categories. Responses to questions were evaluated using the Likert scale. Income inequality within each country, measured by the Gini coefficient, was designated as the explanatory variable. Control variables were incorporated, including GDP per capita and the percentage of social expenditure relative to a country's GDP. The conducted analysis demonstrates a negative correlation between income inequality and the manifestation of social solidarity. The analysis of individual characteristics reveals that specific groups exhibit greater social solidarity compared to others. The conclusion drawn is that both lower and higher household income levels lead to a decrease in the overall manifestation of social solidarity in the face of increasing income inequality. The study's findings contribute theoretically to the discourse on income inequality and its impact on societal stability. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:Analyses of Social Issues & Public Policy. 2024/12, Vol. 24, Issue 3, p691
  • Document Type:Article
  • Subject Area:Economics
  • Publication Date:2024
  • ISSN:1529-7489
  • DOI:10.1111/asap.12425
  • Accession Number:181548872
  • Copyright Statement:Copyright of Analyses of Social Issues & Public Policy is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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