INTERRELATIONSHIPS BETWEEN HUMAN CAPITAL AND INTELLECTUAL CAPITAL: EVIDENCE FROM THE PANEL OF HIGH-INCOME AND LOW AND MIDDLE-INCOME GROUPS OF THE WORLD

Imran HUSSAIN

Department of Economics, Vidyasagar University, Midnapore, India,

imranhussaingrp@gmail.com

Ramesh CHANDRA DAS

Department of Economics, Vidyasagar University, Midnapore, India,

ramesh051073@gmail.com

(corresponding)

Aloka NAYAK

Department of Economics, Vidyasagar University, Midnapore, India

aloka.nayak21@gmail.com

Abstract

The competitiveness in production sector is increasing significantly due to the openness of the economies in the world. Importance of intellectual capital (IC) thus has been mounting continuously and human capital formation (HCF) is considered as the main source of it. IC, an advanced version of human capital, is formed by the efforts upon research and development (RD) activities. It is a natural question whether HCF helps in the formation of intellectual capital in the countries of different status. Under the backdrop, the study examines the long-term relationship between intellectual capital and HCF in case of some countries from the high-income group (HIG) and low and middle-income group (LMIG) during the period of 1998 to 2018. It employs panel unit root, panel cointegration and panel causality techniques for examining the long run associations and short run dynamics between human capital and intellectual capital for the two groups of the economies. The findings of the study show that long-term association exists between these two forms of capital for both the panels of high and low and middle-income nations. But the short-run causal interplay works in high-income group only where human capital formation is making a cause to the intellectual capital formation. A one-unit increase in the change of HCF at period t-1 results in a 0.05 unit rise in the change of current year intellectual capital in the high-income group. The governments of the countries are suggested to make more human capital formation via increasing expenditures on both education and health sector to assure more intellectual capital.

Keywords: Human capital, intellectual capital, growth, panel cointegration, panel causality, high and middle income countries

JEL classification: R10, R11, O30, C33

 pp. 107-122

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DIGITALIZATION OF ECONOMY AND LIVING STANDARDS OF POPULATION IN RUSSIAN REGIONS

Nadezda Vasilievna SEDOVA

Dr. Plekhanov Russian University of Economics, Russia

nadseva@mail.ru

Lidia Sergeevna ARKHIPOVA

Ph.D. Plekhanov Russian University of Economics, Russia

Arkhipova.LS@rea.ru

Darya Mikhailovna MELNIKOVA

Ph.D. Plekhanov Russian University of Economics, Russia

Melnikova.D@rea.ru

Irina Fedorovna ALESHINA

Ph.D. Plekhanov Russian University of Economics, Russia

Aleshina.IF@rea.ru

Abstract

The study of territorial inequality in the modern economic space corroborates the relevance of the strategic goals of enhancing the living standards of the population amid digitalization of the economy. Despite the regional disparities in the social and economic development of the Russian regions, favorable factors for the responsiveness to digitalization in various economic and social spheres formed. They include the high quality of human capital, a relatively sufficient level of Internet access among population, modern infrastructure in a significant number of the regions, increased organizational costs for the introduction and use of digital technologies, etc. Therefore, the purpose of the research is to assess the indicators of digitalization in the regions, their territorial disparities and model the indicators of living standards as well as the use of information and communication technologies by the population and in organizations. The research features a typology of regions according to the main indicators of digitalization with the identification of the top regions, where capital territorial entities of the Russian Federation and the northern regions with a high household income, an economy dominated either by processing and knowledge-intensive industries, or with a raw-material focus, stand out. It has been noted that over the past fifteen years, interregional differentiation by digitalization indicators has been decreasing, however, problems persist in the eastern remote and underdeveloped regions in the south of the country. The research is of practical value in terms of economic and mathematical modeling of digitalization and internetization process in relation to living standards of the population.

Keywords: digitalization, region (RF subject), indicators, human capital, internetization, modeling

JEL classification: R23, J610

 pp. 47-65

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HUMAN CAPITAL AND HIGHER EDUCATION AS DRIVERS OF ECONOMY IN ALBANIA

Etleva BAJRAMI

Prof. Assoc. Dr., Pedagogue in Finance Department, Faculty of Economy, University of Tirana

etlevabajrami@feut.edu.al

Brikena LEKA

Prof. Assoc. Dr., Pedagogue in Finance Department, Faculty of Economy, University of Tirana

brikenaleka@feut.edu.al

Abstract

Education is a strong pillar for the qualitative growth and improvement of human capital. Appropriate and necessary education of people will enable business employees to have the necessary knowledge for the activity. The growth of businesses will have its impact on the growth of the country’s economy. People are turning to higher education more and more as a way to enhance their personal wellbeing. Higher education is seen by people as the best way to enable the employment and higher salary in the future. For this reason the focus of this paper is education. The main objective is to understand the impact of higher education in economic growth. This paper analyzes the impact of education through several variables on economic growth in Albania, focusing more on the impact of higher education. The independent variables considered in this paper as representatives of education are mean years of schooling, enrollment in primary education, enrollment in secondary education, enrollment in higher education, while as a representative of growth is used dependent variable Gross Domestic Product (GDP) per capita. From the model we found the variables mean years of schooling and enrollment in higher education are significant and positively related with GDP per capita. The analysis is based on model building with secondary data using the method of least squares.

Keywords: human capital, higher education, school enrollment, GDP per capita

JEL classification: I23, O15, H52

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