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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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The role of entrepreneurship in explaining the real Gross Domestic Product per capita: Regression model selection

and GDP per capita. In Bendekovic, M., Klacmer Calopa, M. and Filipovic, D. (Eds.) “Economic and Social Development”, Book of Proceedings of the 6th International Scientific Conference on Economic and Social Development and 3rd Eastern European ESD Conference: Business Continuity, Vienna, 25-25 April 2014.Varazdin, Croatia: Varazdin Development and Entrepreneurship Agency. ISBN: 978-953-6125-10-4. pp. 507-516. 16. Harris, R. (1995). Using Cointegration Analysis in Econometrics Modelling. Prentice Hall/Harvester Wheatsheaf, Upper Saddle River

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Testing the validity of the Linder hypothesis for Croatia

2018]. 29. World Bank (2018a). GDP per capita (Current US$). Available at https://data.worldbank.org/indicator/NY.GDP.PCAP.CD [01 May 2018]. 30. World Bank (2018b). World Integrated Trade Solution. Available at https://wits.worldbank.org/CountryProfile/en/Country/HRV/StartYear/2000/EndYear/2016/TradeFlow/Import/Partner/ALL/Indicator/MPRT-TRD-VL [01 May 2018].

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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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Macroeconomic effects of the budget deficit in the Republic of Macedonia

(% of GDP) . Available at https://www.finance.gov.mk/en/node/2678 [10 May 2018]. 15. Nayab, H. (2015). The Relationship between Budget Deficit and Economic Growth of Pakistan. Journal of Economics and Sustainable Development , Vol. 6, No. 11, pp. 85-90. 16. Saleh, A. S. (2003). The Budget Deficit and Economic Performance: A Survey. Department of Economics, University of Wollongong , Working Paper 03-12, pp. 1-56. Available at http://ro.uow.edu.au/commwkpapers/78 [10 May 2018]. 17. National Bank of the Republic of Macedonia (2017). Basic

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Process of ranking countries by level of development

References 1. Cracolici, M. F., Cuffaro, M., Nijkamp, P. (2010). The Measurement of Economic, Social and Environmental Performance of Countries: A Novel Approach. Social Indicators Research, Vol. 95, No. 2, pp. 339-356. 2. Eurostat (2018a). Eurostatistics - Data for short term economic analysis - Issue No 6/2018. Available at http:// http://ec.europa.eu/eurostat/documents/3217494/8985191/KS-BJ-18-006-EN-N.pdf [24 March 2018]. 3. Eurostat (2018b). GDP per capita in PPS. Available at http

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Indicators of sustainable development performance: Case study of European Union countries

on the Benefit-of-the-Doubt model: The case of QS World University Rankings by Subject. Croatian Review of Economic, Business and Social Statistics, Vol. 2, No.1, pp. 1-14. 20. Markusen, J. (2013). Putting per-capita income back into trade theory. Journal of International Economics, Vol. 90, No. 2, pp. 255-265. 21. Milenkovic, N., Vukmirovic, J., Bulajic, M., Radojicic, Z. (2014). A multivariate approach in measuring socio-economic development of MENA countries. Economic Modelling, Vol. 38, pp. 604-608. 22. Popović B

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