scholarly journals HUMAN CAPITAL - THE MAIN COMPETITIVE ADVANTAGE UKRAINE: PROBLEMS THE WAY ITS IMPLEMENTATION

2017 ◽  
Vol 19 (1(63)) ◽  
pp. 59-64
Author(s):  
V.F. Goryachuk
Keyword(s):  
Human Capital ◽  
Competitive Advantage ◽  
Institutional Environment ◽  
Developed Countries ◽  
Gdp Per Capita ◽  
Level Of Education ◽  
High Productivity ◽  
Fair Competition ◽  
Technological Level ◽  
Per Capita

Human capital is the main competitive advantage of Ukraine, but there are a number of negative factors that limit the effectiveness of its use. First of all, this is a low level of staffing with fixed assets (5-6 times lower than in developed European countries). This results in a low technological level of production and, consequently, a 4-5 times lower level of labor productivity in comparison with developed countries, limiting the opportunities of Ukrainian citizens, especially of high qualifications, to realize their abilities and skills. As a result, the outflow of highly skilled professionals to other countries with a higher technological level of production and higher wages. Among 52 countries with the highest level of education, Ukraine has one of the lowest GDP per capita ($ 7,500). At the existing level of education in our country, GDP per capita should be about 30.0 thousand dollars. This inconsistency, to a large extent, can be attributed to inefficient government and high levels of corruption. All this negatively affects the efficiency of the use of human capital and productivity of work of citizens, which they can count on, taking into account their educational level. Important in the consideration of human capital is its moral component, which, unlike other components (education, knowledge, experience, health, etc.) determines the vector of its use: for good or for evil. The efficiency of the use of human capital depends on the state of the institutional environment. The existing institutional environment in Ukraine encourages redistribution rather than material wealth production, reduces the possibility of fair competition, limits the direction of high-productivity use of human capital. Ukraine has enormous intellectual potential. This is our main competitive advantage, it is an opportunity to take a worthy place among the leading countries of the world. Today, there is such a chance, but it will take some time and it can be lost if society continues to cultivate the readiness of people for dishonest acts for the sake of careers, power and money, instead of focusing on the realization of their creative abilities, energy and initiative to ensure the successful modernization of your country.

The Reproduction Vector of the Russian Economy: 1999-2007

2008 ◽  
pp. 94-109 ◽  
Author(s):  
D. Sorokin
Keyword(s):  
Economic Policy ◽  
Human Capital ◽  
Growth Rates ◽  
Developed Countries ◽  
Gdp Per Capita ◽  
Real Sector ◽  
Russian Economy ◽  
Per Capita ◽  
The Developed Countries

The problem of the Russian economy’s growth rates is considered in the article in the context of Russia’s backwardness regarding GDP per capita in comparison with the developed countries. The author stresses the urgency of modernization of the real sector of the economy and the recovery of the country’s human capital. For reaching these goals short- or mid-term programs are not sufficient. Economic policy needs a long-term (15-20 years) strategy, otherwise Russia will be condemned to economic inertia and multiplying structural disproportions.

scholarly journals Kapitał ludzki jako źródło konkurencyjności państw członkowskich Unii Europejskiej

2014 ◽  
pp. 47-56
Author(s):  
Magdalena Kowalewska
Keyword(s):  
European Union ◽  
Human Capital ◽  
Union Member ◽  
Gdp Per Capita ◽  
The European Union ◽  
Member States ◽  
Level Of Education ◽  
Synthetic Indicator ◽  
Per Capita ◽  
European Union Member States

The purpose of the article was to present the essence of competitiveness and human capital from the macroeconomic perspective, as well as to present human capital as a source of competitiveness of the European Union member states. In order to assess the human capital of the member states, the level of education of residents, as well as calculated synthetic indicator of human capital were analysed. In addition, relationship between the level of the indicator of human capital and competitiveness of the member states, measured by GDP per capita was examined.

International differences in labor productivity: Role of capital, technological level and resource rent

2016 ◽  
pp. 67-93 ◽  
Author(s):  
A. Zaytsev
Keyword(s):  
Labor Productivity ◽  
Developed Countries ◽  
Resource Rent ◽  
Per Capita Gdp ◽  
Technological Level ◽  
Per Capita ◽  
Oil Sector ◽  
Population Ratio ◽  
Gdp Gap ◽  
Productivity Gap

Using level accounting methodology this article examines sources of per capita GDP and labor productivity differences between Russia and developed and developing countries. It considers the role played by the following determinants in per capita GDP gap: per hour labor productivity, number of hours worked per worker and labor-population ratio. It is shown that labor productivity difference is the main reason of Russia’s lagging behind. Factors of Russia’s low labor productivity are then estimated. It is found that 33-39% of 2.5-5-times labor productivity gap (estimated for non-oil sector) between Russia and developed countries (US, Canada, Germany, Norway) is explained by lower capital-to-labor ratio and the latter 58-65% of the gap is due to lower technological level (multifactor productivity). Human capital level in Russia is almost the same as in developed countries, so it explains only 2-4% of labor productivity gap.

scholarly journals Examining GDP Growth and Its Volatility: An Episodic Approach

Entropy ◽  
2021 ◽  
Vol 23 (7) ◽  
pp. 890
Author(s):  
Jakub Bartak ◽  
Łukasz Jabłoński ◽  
Agnieszka Jastrzębska
Keyword(s):  
Economic Growth ◽  
Genetic Algorithm ◽  
Time Series ◽  
Human Capital ◽  
Growth Rates ◽  
Structural Breaks ◽  
Negative Relationship ◽  
Gdp Per Capita ◽  
Gdp Growth ◽  
Per Capita

In this paper, we study economic growth and its volatility from an episodic perspective. We first demonstrate the ability of the genetic algorithm to detect shifts in the volatility and levels of a given time series. Having shown that it works well, we then use it to detect structural breaks that segment the GDP per capita time series into episodes characterized by different means and volatility of growth rates. We further investigate whether a volatile economy is likely to grow more slowly and analyze the determinants of high/low growth with high/low volatility patterns. The main results indicate a negative relationship between volatility and growth. Moreover, the results suggest that international trade simultaneously promotes growth and increases volatility, human capital promotes growth and stability, and financial development reduces volatility and negatively correlates with growth.

HUMAN RESOURCES DEVELOPMENT OF REPUBLIC OF CROATIA AND PRIMORSKOGORANSKA COUNTY AND THEIR INFLUENCE ON ECONOMIC GROWTH∗

2009 ◽  
Vol 15 (1) ◽  
pp. 13-24
Author(s):  
Nada Karaman Aksentijevic ◽  
Zoran Jezic
Keyword(s):  
Economic Growth ◽  
Human Capital ◽  
Human Resources ◽  
Gdp Per Capita ◽  
Human Resources Development ◽  
Regression Analyses ◽  
Theoretical Part ◽  
Educational Structures ◽  
Indirect Indicator ◽  
Per Capita

In the theoretical part of research authors will establish connections and diversities between human capital and human resources categories. In the empirical part of research, via HDI, it will be evaluated the development of human resources in Republic Of Croatia and in Primorsko-goranska County and in will be evaluated relation between HDI and GDP per capita of Croatia and in Primorsko-goranska County. Authors will also analyze how much development of human resources has contributed to the economic growth of Republic Of Croatia. In order to demonstrate this it will be measured influence of investment, employment and educational structures (the indirect indicator of development of human resources) on the growth of GDP in the period of 1997-2005 with usage of regression analyses.

A PANEL ASSESSMENT OF REAL COVERGENCE IN CEMAC

2006 ◽  
Vol 4 (1) ◽  
Author(s):  
Daniel Gbetnkom
Keyword(s):  
Human Capital ◽  
Regional Integration ◽  
Gdp Per Capita ◽  
Convergence Hypothesis ◽  
Income Levels ◽  
Underdeveloped Countries ◽  
Policy Choices ◽  
Convergence Club ◽  
Per Capita ◽  
Rich Countries

Some authors support that regionalism among underdeveloped countries will tend to cause divergence of their income levels, and regional integration among rich countries will tend to cause convergence. This paper tests this convergence hypothesis in CEMAC between 1990-2002. Our findings lend support to the “convergence club” defined according to policy choices rather than initial levels of human capital. They show that unilateral and preferential suppression of tariff and non-tariff barriers favor the convergence of per capita incomes and reduce the dispersion of real per capita income levels of partners in the sub-region. These results make the idea of convergence club based on the initial levels of productive technology and GDP per capita relative.

scholarly journals Using fuzzy logic for evaluating the level of countries’ (regions’) economic development

2012 ◽  
Vol 59 (3) ◽  
pp. 293-310 ◽  
Author(s):  
Gordan Stojic
Keyword(s):  
Mathematical Model ◽  
Economic Development ◽  
Fuzzy Logic ◽  
Developed Countries ◽  
Gdp Per Capita ◽  
Industrial Growth ◽  
The Poor ◽  
The World ◽  
Level Of Economic Development ◽  
Per Capita

There are several divisions of countries and regions in the world. Besides geo-political divisions, there also are economic divisions. The most common economic division is the that on developed countries and the poor ones. These divisions are a consequence of the level of: GDP, GDP per capita, unemployment rate, industrial growth, and so on. The question is how to define a mathematical model based on which the following will be assessed: who is rich and who is poor, or who is economically developed and who is not? How the boundaries of transition from one category to another can be defined? This paper presents a model for evaluating the level of economic development of countries and regions using "fuzzy" logic. The model was tested on a sample of 19 EU member countries and aspirants for membership.

scholarly journals Revisiting the casing layer: Casing materials and management in Agaricus mushroom cultivation

2021 ◽  
Vol 45 ◽  
Author(s):  
Eustáquio Souza Dias ◽  
Diego Cunha Zied ◽  
Arturo Pardo-Gimenez
Keyword(s):  
Crop Management ◽  
Developed Countries ◽  
Mushroom Cultivation ◽  
Button Mushroom ◽  
High Productivity ◽  
Mushroom Production ◽  
Alternative Materials ◽  
Technological Level ◽  
Productivity Indices ◽  
Casing Layer

ABSTRACT The cultivation of button mushroom has reached a high technological level in developed countries and is associated with high productivity indices. This technological level involves not only compost production and crop management but also the casing layer. Peat has been established as one of the most appropriate casing materials for the cultivation of button mushroom due to its excellent properties. However, good-quality peat is not available in all countries, and peat is not renewable, which reinforces the need for alternative materials. Therefore, studies on the casing layer should include its response to the induction of fruiting since this stage is where the main changes that lead to the formation of primordia occur. This review addresses the different aspects of fruiting induction of Agaricus mushrooms and the influence of the characteristics of the casing layer on mushroom production.

scholarly journals Productivity and Institutions

2015 ◽  
Vol 11 (2) ◽  
pp. 375
Author(s):  
Gylfi Zoega
Keyword(s):  
19Th Century ◽  
Legal System ◽  
Industrial Revolution ◽  
Lower Cost ◽  
Standard Of Living ◽  
Gdp Per Capita ◽  
Past Century ◽  
High Productivity ◽  
The Past ◽  
Per Capita

Differences in productivity account for differences in output per capita between countries as well as changes in output and the standard of living for each country over long periods of time. During the first industrial revolution, one could already see the emergence of two groups of countries: the high- and the low-GDP per capita countries. The list of countries belonging to the highproductivity group has not changed much over the past century. Differences in institutions separate the two clubs. The high-productivity group is, amongst many other differences, characterized by less corruption, a better legal system, superior enforcement of contracts, a lower cost of starting a business and lower tariffs. Historical output series for Britain going back to the mid-19th century show that productivity has increased greatly and improved the standard of living.

P–731 Correlation between fertility rate, utilisation of ART and gross domestic product across Europe

2021 ◽  
Vol 36 (Supplement_1) ◽  
Author(s):  
A Lass ◽  
G Lass
Keyword(s):  
Correlation Coefficient ◽  
Developed Countries ◽  
Fertility Rate ◽  
Gdp Per Capita ◽  
Natural Fertility ◽  
European Economic Area ◽  
Eu Member States ◽  
Utilisation Rate ◽  
Registration Number ◽  
Per Capita

Abstract Study question Are there any correlations between a country’s wealth determined by GDP per capita and its total fertility rate (TFR) and utilisation of ART in Europe? Summary answer There is strong correlation across Europe between GDP and utilisation of ART. This correlation does not exist when only investigating the European Economic Area (EEA) What is known already The number of documented ART cycles has increased significantly from 203,893 cycles in 1997 (first European report) to 918,159 in 2016. During the same period, growth was observed in European GDP and, to a lesser extent, TFR following a significant and prolonged decline. Global data suggest that utilisation rate is higher in developed countries, speculated to be due to either generous reimbursement systems or higher affordability for patients paying out of pocket. This study analysed for the first time the relationships between national GDP, TFR and utilisation in Europe both as a whole, and specifically the more affluent EEA Study design, size, duration This study was an analysis of publicly available primary international reports: total cycles in the European IVF-monitoring Consortium (EIM) and TFR, GDP and population size from the World Bank indicators (https://data.worldbank.org/indicator). The period studied ranged from the first EIM report for 1997 (published in 1999) to the 20th report for 2016 (published in 2020). Participants/materials, setting, methods TFR was described as births per women (BPW) and country wealth was presented as GDP per capita in US Dollars. Utilisation rate was defined as the total national number of cycles (fresh IVF and ICSI, and frozen embryo transfer) divided per population, and presented as cycles per million (CPM). When utilisation was not reported, total cycles were projected by proportional calculation. Pearson Correlations were calculated using Sigmaplot for utilisation, GDP and TFR in 2016 Main results and the role of chance Forty countries were included in the EIM report for 2016, of which 18 reported in full. The median utilisation rate was 1280 CPM (range 162 - 3,156) and median TFR was 1.6 BPW (range 1.26 - 2.73); only one country, Kazakhstan, had a TFR above the natural fertility replacement level of 2.1 BPW. Mean GDP was $31604 per capita (range $10,610 - $110,650). There was no correlation between TFR and utilisation or between TFR and GDP, however there was a significant positive correlation between GDP and CPM (correlation coefficient = 0.428; P = 0.00661). Compared to Europe as a whole, analysis of only the EEA countries – EU member states plus Norway, Iceland, and Switzerland – revealed a similar median TFR (1.59), but a 27% increase in the utilisation rate to 1629 CPM (range: 317 – 3157) and 24% rise in GDP per capita to $39,300 (range: $19,885- $110,650). For the EEA, no significant correlations were observed, including between GDP and utilisation (correlation coefficient = 0.131; P = 0.507). Additionally, there was no significant correlation between TFR and GDP in the EU for the period of 1997 – 2016. Limitations, reasons for caution The data is a snapshot of a single year, but we observed similar outcomes in previous years. Projection calculation of utilisation in partially reporting countries may cause bias, however, with a reporting level of 92% (1347 of 1467 clinics), this bias is probably very limited. Wider implications of the findings: Findings of this study confirm that there are strong disparities in the availability of ART even in Europe. This difference does not exist in the more affluent countries in Europe suggesting that the reason for lower utilisation in lower-income countries being reduced affordability. Trial registration number NA

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