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Trends of Convergence at Regional Level in European Union (EU-28)
Author(s) -
Daniela Antonescu
Publication year - 2020
Language(s) - English
Resource type - Conference proceedings
DOI - 10.18662/lumproc/ibmage2020/35
Subject(s) - convergence (economics) , european union , cohesion (chemistry) , per capita , divergence (linguistics) , context (archaeology) , inequality , economic geography , politics , process (computing) , premise , regional science , econometrics , economics , political science , geography , international trade , computer science , economic growth , mathematics , sociology , demography , law , chemistry , philosophy , organic chemistry , archaeology , mathematical analysis , population , linguistics , operating system
The objective regarding cohesion is achieved by means of a convergence process that assumes diminishing territorial inequalities between regions and territories. The cohesion process is not limited to the relatively poor regions, but aims also to more developed regions with the purpose of observing also the secondary effects for the entire EU (EC Report, 2013). Identifying the convergence or divergence trends is one of the intensely argued topics by both the academic and the political-decisional environment. The theoretical point of view approach regarding convergence was accompanied by models meant to mitigate the requirements of assessing over given periods the evolution of territorial inequalities (between countries or regions). Identifying a process of convergence or divergence at regional level is a widely debated issue both in the academic and political-decision making environment. Thus, in the context of favourable economic development, convergence assumes a process of closing the gap between the living standards between the poorer and richer areas beginning with the premise that the first have a swifter development as the latter. Considering this aspect, the present article analyses the trends of convergence/divergence at regional level in the context of the European Union with the help of GDP per capita and variation coefficients.

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