Search

This study aims to find out the long-run relationship between human capital and the current account balances. The panel data analysis is carried out for the time period between 1990 and 2018. 88 developing and developed countries are included in the study. Panel cointegration analysis is applied to test the long-run relationships. The human capital is represented by two indexes. First one is The Institute for Health Metrics and Evaluation (IHME) human capital index. Second one is United Nations human development index. For both indexes, there are significant and positive long-run relationships between the human capital indexes and current account balances for high income countries. It is determined that there is a negative, significant and long-term relationship for "all countries except industrialized countries", "all countries except Africa and industrialized countries" and "all countries" groups. [ABSTRACT FROM AUTHOR]

In this study, panel data for 143 countries from 1993 to 2014 are used to examine the association between ICT penetration and human capital development. Human Capital Index is utilized as a proxy for human capital development while ICT penetration is proxied by the penetration of internet users, fixed broadband subscriptions, and mobile phones. Each ICT indicator is considered in a separate model to avoid any potential multicollinearity problems. Bivariate and multivariate fixed time effect panel data estimation results suggest that there is a positive and strong relationship between ICT penetration and human capital development. Multivariate models are also estimated for developing countries sub-sample to check the robustness of estimation results. It is be observed that estimation results support the previous findings. Estimation results also indicate that individuals using the Internet as a percentage of population has the largest impact on the human capital among ICT indicators used in the study. [ABSTRACT FROM AUTHOR]

According to the statistical classification of regions on Rev.1, Northeast Anatolia Region, East Anatolia Region and Southeastern Anatolia Region are Turkey's economically and socially underdeveloped regions. In Rev.2 distinction, Erzurum, Ağrı, Malatya, Van, Gaziantep, Sanlıurfa and Mardin proviences are sub-regions within this scope. During the planned economy period in Turkey these regions have been an issue for economic and social plan-projects continuously. In order to ensure economic growth, human capital needs to be examined especially. In this study, for seven sub-regions in Turkey the determinants of human capital such as education, health, culture and value-added per capita examined as a consequence of growth to consider the impact of competitiveness. Data used between the years 2007-2011 firstly converted to an index then panel data analysis performed. Effects of health, education, culture and value-added indexes on different regions competitiveness indexes are examined and inter-regional comparisons were carried out. According to panel data application based on regional competitiveness index; cultute and health indexes on TRB2 and TRC2 regions; education and health indexes on TRA1 and TRC1 regions; health and gross value added per capita indexes on TRB1region; culture and education indexes on TRC3 region have negative effects. According to the panel data application on TRA2 region; education, health, culture and gross value added per capita indexes have positive effects on regional competiteveness. From this point, education policies should be revised for he mentioned regions. The policies to be implemented for the development of education also need to be include culture and health policies. [ABSTRACT FROM AUTHOR]

According to the statistical classification of regions on Rev.1, Northeast Anatolia Region, East Anatolia Region and Southeastern Anatolia Region are Turkey's economically and socially underdeveloped regions. In Rev.2 distinction, Erzurum, Ağrı, Malatya, Van, Gaziantep, Sanlıurfa and Mardin proviences are sub-regions within this scope. During the planned economy period in Turkey these regions have been an issue for economic and social plan-projects continuously. In order to ensure economic growth, human capital needs to be examined especially. In this study, for seven sub-regions in Turkey the determinants of human capital such as education, health, culture and value-added per capita examined as a consequence of growth to consider the impact of competitiveness. Data used between the years 2007-2011 firstly converted to an index then panel data analysis performed. Effects of health, education, culture and value-added indexes on different regions competitiveness indexes are examined and inter-regional comparisons were carried out. According to panel data application based on regional competitiveness index; cultute and health indexes on TRB2 and TRC2 regions; education and health indexes on TRA1 and TRC1 regions; health and gross value added per capita indexes on TRB1region; culture and education indexes on TRC3 region have negative effects. According to the panel data application on TRA2 region; education, health, culture and gross value added per capita indexes have positive effects on regional competiteveness. From this point, education policies should be revised for he mentioned regions. The policies to be implemented for the development of education also need to be include culture and health policies. [ABSTRACT FROM AUTHOR]

The world economy that go through of agricultural, industrial and knowledge focused revolutions is being fictionalized upon the theories which put forward human and humanity gradually. The concept of human capital has become the one of the basic factors of economic growth. In the study, first of all, the concept of human capital has handled with perspectives of different authors. Then, the perspective of the schools of economic thought on human capital and their theoric debates on how the human capital can be measured has analyzed. In the application section, the indexes of human development, gross value added per capita, culture and regional competitiveness has developed as determinants of human capital. The data used in panel data analysis covers between 2007 and 2011 periods. Seven different models have setup in order to detect interactions between indexes of culture, education, health and regional competitiveness in panel data analysis. So directions of relations between this indexes have revealed. The study aims to fill the deficiency of researches about human capital on NUTS 2 level. [ABSTRACT FROM AUTHOR]

According to the statistical classification of regions on Rev.1, Northeast Anatolia Region, East Anatolia Region and Southeastern Anatolia Region are Turkey's economically and socially underdeveloped regions. In Rev.2 distinction, Erzurum, Ağrı, Malatya, Van, Gaziantep, Sanlıurfa and Mardin proviences are sub-regions within this scope. During the planned economy period in Turkey these regions have been an issue for economic and social plan-projects continuously. In order to ensure economic growth, human capital needs to be examined especially. In this study, for seven sub-regions in Turkey the determinants of human capital such as education, health, culture and value-added per capita examined as a consequence of growth to consider the impact of competitiveness. Data used between the years 2007-2011 firstly converted to an index then panel data analysis performed. Effects of health, education, culture and value-added indexes on different regions competitiveness indexes are examined and inter-regional comparisons were carried out. According to panel data application based on regional competitiveness index; cultute and health indexes on TRB2 and TRC2 regions; education and health indexes on TRA1 and TRC1 regions; health and gross value added per capita indexes on TRB1region; culture and education indexes on TRC3 region have negative effects. According to the panel data application on TRA2 region; education, health, culture and gross value added per capita indexes have positive effects on regional competiteveness. From this point, education policies should be revised for he mentioned regions. The policies to be implemented for the development of education also need to be include culture and health policies. [ABSTRACT FROM AUTHOR]

The importance of human capital in economic growth began to investigate since the second half of the 20th century and continues to this day. Especially today, when we live in the information, science and technology age the role of human capital in the economic growth is increasing. İn hundreds of studies including different periods and different groups of countries the econometric analysis demonstrated a strong relationship between human capital and economic growth. The purpose of this study is to investigate the relationship between human capital and economic growth in the 4 transition economies of Central Asia (Kazakhstan, Kyrgyzstan, Uzbekistan, Tajikistan) during the period 1991-2013 by utilizing the Kao panel cointegration, Panel FMOLS methods. The cointegration test results show that there is a cointegration relationship between human capital and economic growth in transition economies. [ABSTRACT FROM AUTHOR]

The World economy that makes living from agricultural production in ancient times has adopted industrial and knowledge-based production with technological developments. Human highlighted theories have become mandatory with information centered production. Because human capital began to be recognized as the engine of economic growth. In this study, regional development and human capital concepts have been analyzed. In this direction, a panel data analysis has been executed with education and health indicators for 2007 - 2011 period with indexing. It is detected that regional competitiveness, gross value added per capita, health and culture indexes have positive impacts on education index. And also, regional competitiveness and gross value added per capita indexes have the negative impact on health index while education and culture indexes have the positive impact. This study aims to investigate the variables that impact on the level of human capital indicators in NUTS 2 level regions and fill the efficiency of searches on human capital. [ABSTRACT FROM AUTHOR]