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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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Evaluating the Nexus Between Financial Deepening and Economic Growth: Evidence from Ukraine

Abstract

In this paper systemic problems of Ukrainian banking sector are reviewed and the solutions are offered. The main objective of the study is to examine the relationship between a financial deepening and economic growth in Ukraine by estimating several multiple regression models over the 1993 to 2015 period. A real GDP growth per capita was used as an indicator for the economic growth. The domestic credit to private sector (% of GDP) was used as an index of financial depth. The study concludes that financial deepening causes a slight impact on the economic growth of Ukraine. A low level of impact is an indicator of a limitedness of lending to the real economy. This means that banking sector has not become the real driving force of the economic growth in Ukraine yet. The study suggests a statement that policy makers should design the policies which will encourage lending especially high tech production, small and mid-size business, micro financing to the real economy to promote economic growth and increase employment.

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The Impact Of Foreign Direct Investment On Turkish Economy 2010–2016

Summary

This study focuses on Foreign Direct Investment (FDI) inflows and how they are linked with the economic indicators in Turkey including the Real Effective Exchange Rate (REER), and Gross Domestic Product per capita of Purchasing Power Parity - GDP (PPP) in Turkey. The GDP (PPP) variable is used because it shows significant causality on REER, along with the exchange rate volatility of the U.S Dollar in the Turkish stock market. Also, as an important sector of the Turkish economy, tourism revenue is elucidated according to the Organization for Economic Co-operation and Development (OECD) data from 2016. The main objective of this study is to evaluate the impact of the FDI investment on economic condition in Turkey for the period between January 2010 and July 2016. The selected period is important because it represents the crucial time for Turkish economy following the 2008 global financial crisis along with the ongoing Civil War in neighboring Syria that had initiated in 2012, Turkish-Russian crises of 2015, and the military coup attempt in Turkey in 2016. It is argued that despite all the negative international and regional developments, FDI and Tourism play key roles in attracting income to the country. This is presented in the level of REER and GDP for PPP. The results also support the findings of many economists, who have previously asserted that the Turkish economic interaction is growing at a globalized level, and is able to compete with the other large attractive areas for foreign investors around the world. Finally, the results demonstrate that the tourism industry was the least affected sector in Turkey.

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Macroeconomic dynamics and the at-risk-of-poverty population in Slovakia

References Eurostat: Combating Poverty and Social Exclusion, 2010 Stiglitz, J., Sen, A., Fittoussi, J., P.: Report by the Commission on Measurement of the Economic Performance and Social Progress, Brussels-Paris, 2009 Kuznets, S.: National Income, 1929-1932". 73rd US Congress, 2d session, Senate document no. 124, 1934 Eurostat: Beyond GDP-Measuring Progress, True Wealth and the Well-being of Nations, International Conference, November 19-29, Brussels, 2007

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Determinants of Patent Protection Regimes: A Self-Organizing Map Approach

Abstract

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.

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New Resonance Approach to Competitiveness Interventions in Lagging Regions: The Case of Ukraine before the Armed Conflict

Abstract

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.

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The Catching up Processes of the Regions of the Visegrad Group Countries

Abstract

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.

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Analysis of the Validity of Environmental Kuznets Curve for the Baltic States

. Energy Economics 34:358-364. 20. He J.; Wang H. 2012. Economic struvture, development policy and environmental quality: An empirical analysis of environmental Kuznets curves with Chinese municipal data. Ecological Economics, Volume 76:49-59. 21. Holtz-Eakin, D.; Selden, T.M. Stoking the fires? CO2 emissions and economic growth. Journal of public economics, 1995, 57, p. 85-101. 22. Huang, W. M.; Lee, G. W. M.; Wu C. 2008. GHG emissions, GDP growth and the Kyoto Protocol: A revisit of Environmental Kuznets Curve

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Economic Inequalities and the Level of Decentralization in European Countries: Cluster Analysis

). Eurostat (2013), GDP at regional level, [online] http://epp.eurostat.ec.europa.eu/statistics_explained/index.php/GDP_at_regional_level . (Cited from 20 Apr 2014). Ezcurra R., Pascual P. (2007), Spatial Disparities in Productivity in Central and Eastern Europe , ‘Eastern European Economics’, no. 45. Falco E. (2014), Income inequality: nearly 40 per cent of total income goes to people belonging to highest (fifth) quintile , ‘Statistics in Focus’, no. 12, [online] http

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Disparities in Regional Economic Development in Romania

Abstract

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

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