scholarly journals FISCAL DECENTRALIZATION AND ECONOMIC GROWTH IN SELECTED EUROPEAN COUNTRIES

2017 ◽  
Vol 18 (4) ◽  
pp. 745-757 ◽  
Author(s):  
Neringa SLAVINSKAITĖ
Keyword(s):  
Economic Growth ◽  
Economic Development ◽  
Fiscal Decentralization ◽  
Developed Countries ◽  
Panel Model ◽  
Development Level ◽  
Multiple Regression Method ◽  
Level Of Economic Development ◽  
High Level ◽  
The Empirical Analysis

The paper analyses the fiscal decentralization effects on economic growth in unitary countries of European Union for the period 2005–2014. The empirical analysis was based on the multiple regression method. The fixed effect panel model was used as framework for the analysis. In order to examine the different impact of fiscal decentralization, the same analysis was applied to subsets of countries categorized into two groups according to countries’ level of economic development. This further analysis found that there is positive relationship between fiscal decentralization and economic growth in low level of economically developing countries and no relationship in high level of economically developed countries. These results suggested that fiscal decentralization is not always instrument for promotion of economic growth, which means that country’s economic development level is an important factor when introducing reform of fiscal decentralization. The originality of this article – new fiscal decentralization index and evaluated fiscal decentralization level influence for countries economic growth.

Growth and Social Capital: Empirical Analysis of the Relationship

2019 ◽  
pp. 128-134
Author(s):  
Ksenia V. Bagmet
Keyword(s):  
Economic Growth ◽  
Social Capital ◽  
Economic Development ◽  
Social Development ◽  
Empirical Analysis ◽  
Panel Data Analysis ◽  
Well Being ◽  
Developed Countries ◽  
International Institute ◽  
Level Of Economic Development

The article provides an empirical test of the hypothesis of the influence of the level of economic development of the country on the level of development of its social capital based on panel data analysis. In this study, the Indices of Social Development elaborated by the International Institute of Social Studies under World Bank support are used as an indicators of social capital development as they best meet the requirements for complexity (include six integrated indicators of Civic Activism, Clubs and Associations, Intergroup Cohesion, Interpersonal Safety and Trust, Gender Equality, Inclusion of Minorities), comprehensiveness of measurement, sustainability. In order to provide an empirical analysis, we built a panel that includes data for 20 countries divided into four groups according to the level of economic development. The first G7 countries (France, Germany, Italy, United Kingdom); the second group is the economically developed countries, EU members and Turkey, the third group is the new EU member states (Estonia, Latvia, Lithuania, Romania); to the fourth group – post-Soviet republics (Armenia, Georgia, Russian Federation, Ukraine). The analysis shows that the parameters of economic development of countries cannot be completely excluded from the determinants of social capital. Indicators show that the slowdown in economic growth leads to greater cohesion among people in communities, social control over the efficiency of distribution and use of funds, and enforcement of property rights. The level of tolerance to racial diversity and the likelihood of negative externalities will depend on the change in the rate of economic growth. Also, increasing the well-being of people will have a positive impact on the level of citizens’ personal safety, reducing the level of crime, increasing trust. Key words: social capital, economic growth, determinant, indice of social development.

scholarly journals SMART GROWTH PROGRESS IN EUROPEAN UNION: A COHESION APPROACH

2019 ◽  
Vol 133 (2) ◽  
pp. 41-49
Author(s):  
Viktor Kozlovskij
Keyword(s):  
Economic Growth ◽  
Economic Development ◽  
Tertiary Education ◽  
Smart Growth ◽  
Developed Countries ◽  
Member States ◽  
Eu Countries ◽  
Development Level ◽  
Growth Indicators ◽  
The Eu

Economic development and socioeconomic cohesion have always been an object of scientific research. In particular, this issue had become a focus of attention after EU enlargement in 2004 and Great Recession in 2007–2009. The above changes have given way to a certain slowdown in economic growth in most EU countries along with triggering a range of divergence processes between EU countries and regions. As a response to situation, the EU offered a Europe 2020 strategy, in which smart growth was mentioned as one of critical instruments to deal with increasing menaces. The objective of the study is to evaluate the progress of the main smart growth indicators (investment in research and development (R&D), employment rate and share of population obtaining tertiary education) in the EU over the period 2001–2017 within the framework of the economic cohesion concept. The paper seeks to explore the EU from different perspectives. First, the EU new member states (EU-10) and the old ones (EU-14) were compared. Second, the EU countries were divided by economic development level (calculated by GDP per capita in PPP): highly developed (H-7), medium developed (M-7) and less developed (L-7) countries. Finally, aggregate cohesion indices of all three smart growth indicators were calculated for the entire EU (EU-28). The research findings have revealed some interesting trends. First, each smart growth indicator’s progress depends on countries’ economic development level. Aggregate values for more developed countries (EU-14, H-7 and G-3) are always higher than the EU average (EU-28) and aggregate values for less developed economies are basically lower. Second, cohesion progress of smart growth indicators was influenced by economic recession in 2007–2009. It is argued that cohesion is evident in times of economic growth, but its progress ceases or divergence might occur in case of economic hazards. However, despite the expanding cohesion between the new and the old member states, a gap between certain groups of countries is even growing. This is clearly evident when the EU member states are divided into groups subject to the level of their economic development.

scholarly journals Human Capital and the Level of Economic Development

2018 ◽  
Vol 14 (2) ◽  
pp. 31
Author(s):  
Rewat Thamma-Apiroam
Keyword(s):  
Economic Growth ◽  
Human Capital ◽  
Economic Development ◽  
Developed Countries ◽  
Causality Test ◽  
Capital Growth ◽  
Level Of Economic Development ◽  
The Government ◽  
The Relationship ◽  
Developing And Developed Countries

This study aims at testing the causal relationship between human capital via the government spending share on education and economic growth using cross-country evidence and investigating the relationship pattern between such human capital – growth and the level of economic development based on 30 country data. The study employs a standard approach through uniting root test and Granger causality test. The data is annually collected during the periods 1983 – 2012, totaling to 30 observations. The finding indicates that for both developing and developed countries, education human capital cannot explain much the economic growth and vice versa. In addition, from the relationship pattern between human capital – growth and the economic development level neutrality is the most commonly found pattern for both developing and developed countries. However, we see somewhat difference between them in terms of causation running from growth to human capital. That is, the number of developed countries is almost double as compared to the developing ones. This gives rise to a policy implication for developed countries in that it should put more emphasis on the government education spending share to GDP since it can help boost human capital in the long run.

scholarly journals Correlation between economic complexity and economic development in different types of Russian regions

2021 ◽  
Vol 51 (3) ◽  
pp. 144-161
Author(s):  
I.A. Shubin ◽  
Keyword(s):  
Economic Development ◽  
Oil And Gas ◽  
Inverse Correlation ◽  
Developed Countries ◽  
Russian Regions ◽  
Homogeneous Groups ◽  
Economic Complexity ◽  
Country Level ◽  
Level Of Economic Development ◽  
High Level

Economic complexity, according to the results of various studies at the country level, can be used as an indicator of economic development: more developed countries usually have a higher level of economic complexity. For Russian regions, the relationship between economic complexity, the level of innovative development and investment attractiveness is also revealed. This paper identifies the correlation between the complexity of export and the level of economic development for Russian regions and their separated more homogeneous groups. The results obtained by the author for regions of Russia contradict the rule identified for countries. For all Russian regions, there is a slight inverse correlation between the complexity of export and the value of per capita GRP. A slight positive correlation was found only for regions with a low export-to-GRP ratio and a high level of economic complexity. Such results are explained by the simple structure of Russian export, because of this the main recipients of export income are regions with a lower level of economic complexity — mainly oil and gas producing regions, as well as capitals that act as intermediaries.

scholarly journals Characterizing the level of economic development of countries

2019 ◽  
Vol 1 (1) ◽  
pp. 343-354
Author(s):  
Alexandra Nastu ◽  
Stelian Stancu ◽  
Andreea Dumitrache
Keyword(s):  
Economic Development ◽  
Composite Index ◽  
Principal Component ◽  
Developed Countries ◽  
Optimal Number ◽  
Point Of View ◽  
Economic Point ◽  
Development Level ◽  
Level Of Economic Development ◽  
Different Levels

Abstract The main purpose of this paper is to provide an objective analysis of the economic development level of countries. This is done by measuring it through a new index and by classifying the countries in an optimal number of clusters, each group characterizing different levels of economic development. The proposed methodology is based on three steps: creating a composite index (by applying the principal component analysis), establishing the optimal number of development groups (based on the number of principal components and on the hierarchical clustering) and clustering countries into them (with the help of k-means analysis). Therefore, this approach solves the difficulty of classifying the countries, complication that is mentioned in the specialized literature. Also, the paper creates a better understanding on the economic development level of countries, as, usually, the papers examine the economic growth level of countries. The analysis is conducted at the level of 60 countries for year 2015, using 12 indicators from categories that influence economic development (income, inequality, health, education and living conditions). The empirical results revealed that the countries can be grouped in two groups: economical developed countries (approximatively 2/3) and economic developing countries (approximatively 1/3). The countries that are most developed from an economic point of view are: Singapore, Luxemburg and Finland.

Analysis of Major Problems Faced by Small Firms in North India

2015 ◽  
Vol 15 ◽  
pp. 150-160
Author(s):  
Davinder Singh ◽  
Jaimal Singh Khamba ◽  
Tarun Nanda
Keyword(s):  
Economic Growth ◽  
Developing Countries ◽  
Economic Development ◽  
Small Firms ◽  
Small And Medium Enterprises ◽  
Developed Countries ◽  
North India ◽  
Small Enterprises ◽  
Employment Generation ◽  
Medium Enterprises

Micro, Small and Medium Enterprises (MSMEs) have been noted to play a significant role in promoting economic growth in less developed countries, developing and also in developed countries. Worldwide, the micro and small enterprises have been accepted as the engine of economic growth of any nation. Small and Medium Enterprises are the backbone of the economies, because it trigger employment, output, export, poverty alleviation, economic empowerment, economic development etc. in developed as well as in developing countries. It is more important to developing countries as the poverty and unemployment are burning problems. MSMEs have been playing a momentous role in overall economic development of a country like India where millions of people are unemployed or underemployed. Therefore, the growth of small sectors is essential for the growth in the GDP, employment generation, total manufacturing production and export. India, being one of the fastest growing economies of the world, needs to pay an honest attention for the utmost growth of MSMEs for its increased contribution in above areas.

Political and Economic Effects on Greenhouse Gas Emissions – a Quantitative Study

2014 ◽  
Vol 10 (2) ◽  
pp. 313-341
Author(s):  
Ole Martin Lægreid
Keyword(s):  
Economic Development ◽  
Linear Relationship ◽  
Greenhouse Gas Emissions ◽  
Greenhouse Gas ◽  
Separation Of Powers ◽  
Economic Effects ◽  
Gas Emissions ◽  
Middle Income ◽  
Level Of Economic Development ◽  
High Level

AbstractThis study examines whether there is a curve linear relationship between economic development and greenhouse gas emissions, where poor and rich countries have low emissions while middle-income countries have high emissions. This is a controversial argument that suggests that persistent economic growth is the best means for achieving considerable emission reductions. The study contributes with new knowledge about the causes of variations in greenhouse gas emissions, by analyzing data for greenhouse gas emissions and testing economic explanations in relation to a broad array of political explanations. As the study demonstrates, there is a curve linear relationship between the level of economic development and greenhouse gas emissions, but the turning point – where a higher level of economic development starts to produce lower rather than higher emission levels – is far higher than previously thought. Among the study’s sample of countries, only the Scandinavian countries and Switzerland have experienced a sufficiently high level of economic development in order for increased wealth to result in lower emissions. Among the political impacts on greenhouse gas emissions, the study indicates that countries with consensual political systems produce lower emission levels than countries where the separation of powers is more centralized. A more robust “green” civil society leads to lower emissions in countries where the democratic system is functioning well, and ambitious targets regarding reduction of emissions in the Kyoto Protocol also seems to lower emissions.

Efficiency Driven Effect of Education in China: The Perspective of Global Competitiveness and Graduate Education

2021 ◽  
Vol 1 (1) ◽  
pp. 36-43
Author(s):  
Jia Liu ◽  
Lun Li
Keyword(s):  
Higher Education ◽  
Economic Growth ◽  
Economic Development ◽  
Practical Significance ◽  
Education Policies ◽  
Global Competitiveness ◽  
Higher Education Policies ◽  
Level Of Economic Development ◽  
Education In China

Capital, natural resources, technology and education are often considered to be the most important factors in improving the level of economic development. China is in the "efficiency-driven" stage of economic development. There are objective laws in the development of education level and economic growth, but they interact with each other. Economic growth provides the foundation and necessary conditions for the development of education. At the same time, the role of education in promoting economic growth is also very obvious. Based on the perspective of postgraduate training, this paper studies the role of education in economic efficiency-driven, through the study of theory, data collection and empirical analysis, combined with the development characteristics of China's higher education, and compares China's and US higher education policies to guide China's higher education. The development of education, and then promote the transformation of China into the "innovation-driven" stage, has certain theoretical and practical significance.

scholarly journals Adaptation of Globalization and Their Effect to the Tanzania Economic Growth

2018 ◽  
Vol 13 (8) ◽  
pp. 217
Author(s):  
Japhet Jacksoni Katanga ◽  
Seleman Pharles
Keyword(s):  
Economic Growth ◽  
Economic Development ◽  
International Cooperation ◽  
Developing Economies ◽  
Economic Inequality ◽  
Developed Countries ◽  
Advance Technology ◽  
African Countries ◽  
The Social

Globalization can be defined as the process based on international cooperation strategies, the aims of globalization is to expanded the operation of a certain business or service to become into a worldwide level, Globalization facilitate the modern advance technology which help community to undergo the social, political and economic development. Globalization economic has reinforced the margination for African developing economies and make to be dependent for the few primary commodities or service whereby the price and demand are extreme determine by externally. On this outcome it lead some of the African countries to be turn into poverty or economic inequality due let their own resources being determine by developed countries. On these paper you will get a chance to oversee the effect of adaption globalization to Tanzania economic growth.

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.

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