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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.
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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This paper explores the role of micro, small and medium size enterprises in the growth of per capita gross domestic product at European Union level between 2005 and 2010. Using a panel of data from 25 Member States the results show a positive connection between the prevalence of SME in terms of created value added and GDP per capita growth. When investigating the aforementioned relationship at enterprise size class level the results differ considerably. While microenterprises prevalence in terms of created value added does not appear to cause more growth in per capita income at EU level, small and medium sized enterprises are some of the main drivers of the annual per capita GDP growth.
This paper examines the relationship between the structure and share of government expenditure into Gross Domestic Product (GDP) and the real GDP per capita. Our study uses a micro panel data for a sample made of ten countries from Central and East European, for the period 2002-2012. The empirical results of the linear regression show that the GDP/capita is positively correlated with public order and safety expenditures as well as with economic actions, while national defense and general public services are negatively correlated. The results obtained largely correspond with the ones reached by other researchers approaching the topic of the relationship between economic growth and composition of the government expenditures. The health and education expenses, though instrumental for the long-term development of any society, did not show any significant impact upon the evolution of the GDP/capita, probably as a result of the short-term available data.
This paper is explaining the relationship between NAFTA foundation and business cycles length. Has the participation in a multinational organization changed their frequency? Initially; we used GDP per capita growth annual data for each country countries (Canada, Mexico and USA) for 63 years (1950-2012). The data was cut for each country in two pieces one before the 1995 and one on the year of integration and after. Then we selected their spectral density plots in order to find periodicity eliminating the background noise from a periodogram. The results show that Canada doubled its cycle length progressively. Mexico and USA seem to have currently smaller but growing cycles than they used to have.
This paper is aimed at answering the question of whether absolute income (GDP per capita) beta-convergence exists in the case of regions in new EU Member States before the period of 2000–2008 and during the 2008–2011 crisis. The sample consists of 211 regions (NUTS 3-level) of Bulgaria, Czech Republic, Estonia, Hungary, Latvia, Lithuania, Poland, Romania, Slovenia and Slovakia.
The research is based on econometric models, namely on the spatial lagged model (SLM), the spatial error model (SEM) and the Durbin spatial model which contrary to the ordinary least squares the (OLS) model include possible spatial dependencies. The SLM and SEM models as well as the Durbin spatial model detect the absolute income beta-convergence on the level of about 1% during the years 2000–2008. Additionally, models do not confirm the existence of absolute income beta-convergence during the crisis of 2008–2011. SLM models (which offer the most reliable findings) find a spatial correlation (measured by the rho-parameter) at a level of 0.75 during 2000–2008 and 0.35 during 2008–2011. Thus, absolute income beta-convergence in the case of NUTS 3 regions in 10 new EU Member States existed only in the pre-crisis period and this period is characterized by much stronger spatial dependencies than the period of 2008–2011.
Maria Daniela Oțil, Andra Miculescu and Laura Mariana Cismaș
The issue of economic disparities within the European Union economies is not new, it is actually a topical issue. Unfortunately, the EU enlargement has determined an even stronger deepening of the regional disparities, because in the absence of adequate regional development policies, the financial instruments have proved to be ineffective. Recent studies show that the economic crisis has increased regional disparities in the European Union countries, influencing the most important regions, especially the economically less advanced ones, the significant regional differences being identified at the NUTS 3 level. Based on these issues, the present paper tries to answer the following questions: 1. How extended are the regional disparities in Romania and how did they evolve over the period 1998-2012? 2. How did the economic crisis influence disparities? Which territorial units were more affected?
In order to measure regional inequalities the Hoover index was used as well as the coefficient of variation, and the indicator for assessing the level of development as well as for highlighting regional disparities was GDP per capita. The analysis and interpretation of the results provide an overview of the situation at the regional level in Romania