The Inequality of Material Living Conditions in EU Countries

Rakauskienė, Ona Gražina; Volodzkienė, Lina

doi:10.14254/2071-789x.2017/10-1/19

Cited by 13 publications

(11 citation statements)

References 1 publication

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“…Studies carried out in the past 10 years have revealed that high level of inequality prevents economic growth (Pernica, 2017). Nevertheless, as stated by (Rakauskienė & Volodzkienė, 2017), in order to study the actual level of socioeconomic inequality, we need to consider the distribution of wealth in different aspects. For this reason, they analysed the distribution of material living conditions and housing inequality in Lithuania and other EU countries, with a special focus on the extent and volatility of the problem.…”

Section: Literature Reviewmentioning

confidence: 99%

The impact of technological changes on income inequality: the EU states case study

Kharlamova

Stavytskyy

Zarotiadis

2018

Journal of International Studies

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In spite of economic growth, which led to the creation of millions of new jobs, income inequality has been growing sharply in most parts of the world. There is no doubt that inequality of income is the single greatest threat to social stability throughout the world. Development of technologies contributes to the increase of labour productivity, replacement of job positions by robots and automatic machines, which can further exacerbate social inequality. The aim of this paper is to determine how changes in technology affect the inequality of income in European countries. Based on the econometric apparatus, two periods are investigated: the first one, from 2006 to 2017 and the second one, from 2010 to 2017, that characterizes a new economic era after the global financial crisis. All countries were clustered, which made it possible to generalize their social and technological development. The novelty is that we considered the dichotomy and cointegration of two economic categories -income inequality and technological changes. Using a model that features biased heterogeneity, factor proportions, and labour market frictions, we obtained four quite sufficient results. (1) Central European countries and the UK have reached such a level of development and redistribution in the economy that a change in labour productivity is not significantly associated with any deepening of inequality in incomes. (2) Periphery countries, due to their significant dependence on larger economies and lack of

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Section: Literature Reviewmentioning

confidence: 99%

The impact of technological changes on income inequality: the EU states case study

Kharlamova

Stavytskyy

Zarotiadis

2018

Journal of International Studies

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“…Thus, scientists emphasize that the differentiation of incomes, especially when compared with existing proportions in neighbouring countries, becomes a significant migration driver, under the influence of which the demographic situation is becoming deteriorated and the perspectives of human capital reproduction are becoming more complicated in low-welfare countries, Ukraine being one of them [2]. At the same time, not only in developing countries, but also in developed ones, inequality is a fact recognised by scientists as a largely constraining social and economic progress and predetermines the imbalances of regional development [3][4][5]. In this case, one of the most famous works in the field of study of inequality and possibilities of its eradication, grounded by Doyle, M.W.…”

Section: Introductionmentioning

confidence: 99%

Impact of Income Distribution on Social and Economic Well-Being of the State

et al. 2020

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Income distribution can cause large-scale transformations in human resources structure, essential changes of economic outputs via its impact on life satisfaction and motivation of work. Thus, the overall objective of this research is to improve methodological tools of income distribution analysis based on identifying the links between different structural indicators of income inequality and the most essential features of social and economic well-being. We conducted comparative analysis of EU Member States and Ukraine. We used structural analysis based on two forms of income distribution—functional (share of “labour” in Gross domestic product - GDP) and household one (ratio of incomes measured by special decile coefficients) to identify income inequality and inconsistencies in distributive strategies. By grouping European countries according to economic well-being (described as GDP per capita) and inequality in income distribution (based on Gini coefficient), we determined apparent tendencies in distributive policies and revealed links between income distribution and connected social-economic features of well-being. We conclude that countries with the most stable and clear patterns in income distribution have distinct connections between the share of labour costs in GDP and successes in social and economic spheres, including human development level, property rights protection, GDP growth, possibilities for taxation and budgeting of social programmes.

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“…In the studies of Khan et al (2016) and Li & Huang (2009), it was proved that a co-integration connection between health and education has positive effects on the economic growth. The effect of the health status of the population can also be found in other economic and social aspects, such as countries' innovation performance (Herzer, 2020;Pacáková & Kopecká, 2019), knowledge transfer (Bar & Leukhina, 2010), technological progress (Gehringer & Prettner, 2019;Lechman, 2019), labour supply ( Jiang et al, 2019), and poverty (Kim, 2018;Rakauskienė & Volodzkienė, 2017).…”

Section: Theoretical Backgroundmentioning

confidence: 99%

How Do Gender Inequalities in Health Relate to the Competitiveness of Developed Countries? An Empirical Study

Gavurová¹,

Ivanková²,

Rigelský³

et al. 2020

JOC

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Public health plays an important role in the spectrum of economic indicators. Simultaneously, the competitiveness of countries is a key economic indicator, and this interconnection requires special attention, especially in the decision-making process of public policies. The main objective of the presented study was to evaluate the effects of selected health indicators on the competitiveness of developed countries. The following health variables were collected for the analysed period from 2010 to 2018: four variables of Life Expectancy (LE) and three variables of Perceived Health Status (PHS). Each variable was observed from the perspective of gender differentiation and gender inequalities. The Global Competitiveness Index (GCI) was also used in the analyses as an economic variable. The research sample included all countries of the Organisation for Economic Co-operation and Development (OECD). The analytical data processing consisted of descriptive analysis, difference analysis (Wilcoxon Test), regression analysis (Panel regression model) and correlation analysis (Spearman's ρ). Regarding the results, all health variables showed differences between men and women. The results of the regression analysis revealed a very strong and significant effect of LE and PHS on the competitiveness of individual economies. The correlation analysis confirmed all relations. Improving the health of men and women is likely to increase the competitiveness of developed countries. As a result, it provides space for further research and policy-making in each country.

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The Inequality of Material Living Conditions in EU Countries

Cited by 13 publications

References 1 publication

The impact of technological changes on income inequality: the EU states case study

The impact of technological changes on income inequality: the EU states case study

Impact of Income Distribution on Social and Economic Well-Being of the State

How Do Gender Inequalities in Health Relate to the Competitiveness of Developed Countries? An Empirical Study

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