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Financial Stability of Insurance Companies in Selected CEE Countries

at: https://data.worldbank.org/indicator/NY.GDP.PCAP.KD.ZG?locations=HU (15 December 2018). 35. World Bank (N/Ab), “World Bank national accounts data and OECD National Accounts data files”, available at: https://data.worldbank.org/indicator/NY.GDP.PCAP.KD.ZG?locations=PL (15 December 2018). 36. World Bank (N/Ac), “World Bank national accounts data and OECD National Accounts data files”, available at: https://data.worldbank.org/indicator/NY.GDP.PCAP.KD.ZG?locations=HR (15 December 2018). 37. Yanase, N., Asai, Y., Lai, G. C. (2008

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Convergence in GDP per capita across the EU regions— spatial effects

Abstract

The aim of this paper is to offer an empirical insight into the spatial effects of growth of regional income and disparities across EU regions (NUTS 2). Since regions are spatial units and there are interrelated standard linear regression is not sufficient to evidence the convergence process. Two models (Spatial Lag Model – SLM and Spatial Error model – SEM), derived from spatial econometrics, have been used to identify and explain spatial effects in convergence clubs—all EU countries (EU-28), countries that entered the EU in 2004 (EU-13) and countries that were in EU prior to 2004 (EU-15). Unconditional and conditional β-convergence has been examined in the period 2000-2015 thus covering two financial perspectives (including n + 2 rule3). Dummy variables have been also applied to catch the country-specific effects, such as national policies, legislation, technology progress, etc.

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Research Activities and their Relation to Economic Performance of Regions in the European Union

Abstract

Background: The intensity of innovation could often be crucial for further economic development of the regions. Science and technology are often seen as the key factor supporting innovation in the regions. Furthermore, we can assume that higher intensity of research activities could lead to better economic performance.

Objectives: Research aims to examine the link between the economic performance of the region and the intensity of science and technology activities, proxied by the share of employees in science and technology.

Methods/Approach: The analysis is based on panel data for NUTS2 regions of the European Union (EU) member states. We conducted correlation analysis, panel Granger causality tests and regression analysis.

Results: Our results suggest the existence of a significant positive correlation between GDP per capita and the share of employees in science and technology. Moreover, the regions with a higher intensity of science and technology activities are mostly characterized by relatively low unemployment rates.

Conclusions: Research activities are positive correlated with regional GDP and negatively correlated with unemployment. However, increasing the share of employment in science and technology beyond a certain turning point would not lead to any further positive effects on regional economic performance.

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Convergence analysis of household expenditures using the absolute β-convergence method

References Agarwal, J., Malhotra, N. K., Bolton, R. N. (2010), "A Cross-National and Cross-Cultural Approach to Global Market Segmentation: An Application Using Consumers' Perceived Service Quality", Journal of International Marketing, Vol. 18, No. 3, pp. 18-40. Boyle, G. E., McCarthy, T. G. (1999), "Simple Measures of Convergence in Per Capita GDP: A Note on Some Further International Evidence", Applied Economics Letters, Vol. 6, No. 6, pp. 343 - 347. Cateora, P. R., Gilly, M. C

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Differences between Croatia and EU Candidate Countries: the CAGE Distance Framework

firms.” Asia Pacific journal of management, Vol. 29, No. 4, pp. 1089-1104. 21. Sakarya, S., Eckman, M., Hyllegard, K. (2007), “Market selection for international expansion; assessing opportunities in emerging markets, International Marketing Review”, Vol. 24, No. 2, pp. 208-238. 22. Sousa, C.M.P., Bradley, F. (2006), “Cultural distance and psychic distance two peas in a pod?”, Journal of International Marketing, No. 14, pp. 49–70. 23. The World Bank (2015), “GDP per capita (current US$)”, available at http://data.worldbank.org/indicator/NY.GDP

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