The EU designs its cohesion policy with the primary purpose of reducing disparities in regional development. The success of the policy is largely determined by the identification of factors that contribute to such disparities. One of the key determinants of economic success is human capital. This article examines the relationship between the quality of human capital and economic development of EU’s regions. Using spatial analysis methods, the spatial dependencies between the growth of human capital and GDP per capita are investigated.
According to the research results, the highest levels of human capital are typical of the most affluent regions in Western Europe, while its lowest levels are found in the poorest countries that became EU members only recently and in countries in southern Europe, including Greece. The spatial correlation measures confirm that spatial relationships have effect on the regional resources of human capital, showing that regions rich in human capital border on regions that are similar to them in that respect. The results of the spatial growth regression indicate that the amount of human capital in the region has a significant and positive effect on its GDP per capita.
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The aim of the paper is to apply the spatio-temporal Environmental Kuznets Curve (SpEKC) to test the relationship between economic growth and the amount of collected mixed municipal waste. The analysis was conducted at the level of sixty-six Polish sub-regions. The study contained selected environmental indicators. The dependent variable - the amount of municipal waste generated in kilograms per capita characterized the state of the environment. The GDP per capita in constant prices (as an explanatory variable) presented the level of economic development of the sub-regions. In the empirical part of the research there were used spatial panel data models based on EKCs. It determined the levels of economic development, at which the amount of produced wastes has fallen or increased, depending on the wealth of the region. The application of different types of spatial weight matrices was an important element of this modelling. Data obtained the years 2005-2012. Models were estimated in the RCran package.
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This study investigates the determinants of patent protection regimes with the use of the self-organizing map (SOM) method. Unlike any previous attempts in the existing literature, this paper takes into consideration the lack of analytical techniques in the past and tries to demonstrate a potential relationship between the patent protection and its determinants through the employment of a newer, more consistent method. The study consists of two main parts. Firstly, the patent protection strengths of 111 countries have been classified via a SOM-based model and it turns out that three types of clusters can be found around the world; low-, mid- and high-protection. The results also show that the densities of these clusters have dramatically changed in the post-1980 period. In the second part of the study, the determinants of the patent rights are examined for 49 developed and developing countries. After revisiting the older econometric models with recent data, this study also analyses the determinants with the SOM method. The findings suggest that there is a significant relationship between GDP per capita, human capital, R&D, market freedom, political rights and patent protection for about two-thirds of the sample; which implies that the patent policies of these countries are in accordance with the selected economic and social factors.
Regional competitiveness is considered to be an alternative basis for the determination of regional interventions. However, the composite competitiveness indicator is quite sensitive to the weights of sub-indicators, no matter what methodology is being used. To avoid this uncertainty in the determination of regional interventions, we proposed a new non-compensatory resonance approach that is focused on the hierarchical coincidence between weaknesses of NUTS 1 and NUTS 2 regions measuring the extensive and intensive components of competitiveness. Such a coincidence, being perceived as a resonance effect, is supposed to increase the effectiveness of interventions triggering synergetic effects and stirring up local regional potentials. The components of competitiveness are obtained through synthesising DEA methodology and Hellwig’s index, correspondingly focusing on the measurement of technical efficiency and resource level. In analysing Ukrainian regions, no correlation between resonance interventions and the composite competitiveness indicator or GDP per capita was found, pointing toward a completely different direction in resonance approach. In western Ukraine, the congestion of six NUTS 2 regions was defined as a homogeneous area of analogous resonance interventions focused on improving business efficiency.
The majority of Central and Eastern European post-socialist countries acceded to the European Union in 2004. The integration of these economies to the Union had begun earlier, which was strengthened by grants from the Structural Funds after the accession. One of their aims is to facilitate the catching up processes of less developed regions and their convergence to the average of older member states. In our study1, we examine the success of the catching up processes of the NUTS3 regions in the four Visegrad Group countries (V4), i.e., the Czech Republic, Hungary, Poland and Slovakia, between 2000 and 2014 to the average of the 15 initial member states of the European Union. Is there a process of catching up in each region, and if so, is it at a similar or a highly different rate? We analyze the development of GDP per capita at Purchasing Power Parity, and we examine disparities in the level of catching up using entropy-based Theil indexes. We provide a detailed analysis of two of the influencing factors of the catching up process of regions. Firstly, we look at whether the catching up process of the regions took place in a similar or very different way compared to the national average. Secondly, we examine how the size of the biggest city of the regions affected catching up, and whether the role of the biggest city of region can be shown.
Analysis of knowledge-based economy impact on economic development in the European Union countries
Directions of changes in the world economy occurring in recent years show the transition from industrial era economy to knowledge-based economy. Increasing investments in fixed assets is no longer a sufficient way of ensuring permanent economic growth. Research-development activity, innovation and human capital become decisive factors of development. As an essential determinant of the innovativeness level of individual economies are considered expenditures on research and development designed to conduct basic, applied research and development activities as well as effects of these research appearing in the form of innovations. The objective of the article is to analyze correlative connections between the two main variables describing knowledge-based economy, that is between the share of R&D expenditures in GDP and R&D expenditures per capita, and the remaining characteristics of knowledge - based economy. Another aim of the article is to assess the impact of these two variables on the basic macroeconomic indicators in the European Union countries, and, connected with them, to analyze the impact of knowledge-based economy on economic development of these countries.