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Models With Varying Parameters as A Tool to Classify Polish Voivodships in 2002-2008
One of the often used measures of economic development is gross domestic product per capita. In Poland the Main Statistical Office collects the data on this variable on several levels of aggregation. The paper shows the application of panel data models in order to classify Polish voivodships according to the level of economic development. As explained variable the regional GDP per capita was used and such variables as structure of employees, unemployment rate or retail sales per capita were the explaining variables. As a result the groups of voivodships with similar pattern of economic development were distinguished.
Jelena Zvezdanović Lobanova, Davorin Kračun and Alenka Kavkler
This paper deals with the economic effect of cross-border mergers and acquisitions on GDP per capita in European transition countries for the 2000- 2014 period. Our analysis shows that cross-border mergers and acquisitions have a negative effect on GDP per capita in the current period, whereas their lagged level positively impacts output performance. We found that transition countries characterized by a higher quality of institutional setting have achieved a positive impact on GDP per capita.
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 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.
and GDPpercapita. 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.
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Angus Maddison’s Contours of the World Economy , I - 2030 AD (2007) is perhaps the best world economic history work. Steve Hanke summarized it as the history of three “distinct epochs of economic growth: the Middle Ages 1000–1500, when the world percapitaGDP rose by 0.05% per year; the protocapitalistic epoch, 1500–1820, when it grew by 0.07% a year; and the capitalist epoch, 1820–2000, when the rate of growth was 17 times higher than it was in the preceding epoch” ( Hanke 2008 , x).
The neoclassical theory of economic growth
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B reuer J.B., M cnown R., W allace M., 2002, Series-specific Unit Root Tests with Panel Data , Oxford Bulletin of Economics and Statistics 64 (5), pp. 527-46, https://doi.org/10