Motivation: The concept of sustainable development relates in particular to the analysis of the causes of excessive environmental degradation. It defines a strategy for limiting this process in three main areas: ecological, economic and socio-cultural human activity. The survey will cover selected EU countries, including Poland, in accordance with Eurostat's sustainable development arrangements. The analysis concerns sustainable development in transport, modality of transport division, logistic efficiency and the volume of freight transport relative to GDP.Aim: The purpose of the article is to present an analysis and development of sustainable transport development in selected European Union countries by using appropriate indicators in relation to the transport of goods.Results: Relevant indicators regarding the transport of goods and identifying trends affecting the environment and society of transport in the EU have been analysed.
This paper aims to examine the innovation performance of 28 European Union countries. Hypothesis of the paper states there is a significant difference of innovation performance between the old and the new EU members. Furthermore, the role of SMEs regarding innovation capacity may not be the same across EU. Using K-means clustering results indicated Germany, Ireland, France, Luxemburg and Austria as the most innovative countries and Bulgaria, Estonia, Latvia, Hungary, Poland and Slovakia as the least innovative countries. Czech Republic, Croatia, Cyprus, Denmark, Finland, Greece, Italy, Lithuania, Malta, Netherlands, Portugal, Slovenia, Sweden, United Kingdom and Spain were found to have a medium level of innovation performance. Furthermore, United Kingdom surpassed the average innovation level of the cluster for the small sized enterprises. Croatia was below the average level of the cluster regardless of the size of the enterprise. Romania was the outlier with the least innovation. In order to facilitate more innovation these findings may be valuable in creating more country specific recommendations for entrepreneurial policy.
Purpose: The purpose of this work is to assess the degree of similarity in the structure of the unemployed according to various categories (gender, age, education, the duration of unemployment) in the EU countries. Approach/Methodology/Design: As a research tool, the vector elimination method was used, which facilitates a division of a set of objects into subgroups with similar structures. Statistical data on the structure of the unemployed due to selected features in 28 European Union countries come from the Eurostat database and relate to 2018. Findings: The spatial distribution of groups of EU countries in 2018 confirms the authors' observations formulated at the beginning of the work that the structures of the unemployed by selected categories are similar in most countries, but it is also possible to distinguish countries in which these structures are significantly different. Practical Implications: The knowledge about the regularities of the structures of the unemployed in individual EU countries is necessary when developing strategies to combat unemployment, especially among people in a particular situation on the labor market. Originality/Value: There are no comprehensive analyzes in the literature to determine the similarity of the structure of the unemployed in EU countries, taking into account various demographic features that are typically taken into account in this type of research (e.g., gender, age, or level of education). The presented studies fill a gap in this area, they can also complement existing studies focusing mainly on the level of unemployment. ; peer-reviewed
In the Summer of 1998, the Executive Board discussed a set of three papers prepared by the staff that focused on the likey impact of EMU on selected non-EU countries. In recognition of the contribution these papers could make to the literature and discussion of EMU, the Board requested that this collection of papers be published. This Occasional Paper presents the three papers in one volume Chapter 1 provides an analysis of the likely impact of EMU on three regions: Central and Eastern Europe, the Mediterranean Basin, and the African CFA zone. Chapter 2 focuses on the trade and financial effects of EMU on selected transition and Mediterranean countries. And Chapter 3 considers the possible implications of EMU for the Middle East and North Africa region
Developing a coherent and comprehensive brand of a country is of vital importance for a destination in the contemporary global world. There seems to be a recognizable gap in the literature regarding the application of visual signs practiced in country branding. The subject of the study: The research identifies the logos of the European Union countries used in place branding. The purpose of the study is the exploration of the logo content from the senders' perspective, i.e., the structures and organizations responsible for the country branding. There are many reasons why logos are used in place branding practice. The authors decided to focus on the logo as a form of controlled and projected message communicated via media and ICT. Cognitive gap: The research conducted so far has focused on the reception of logos by the recipients. The presented research attempts to examine the visual message contained in logos from the senders' perspective. Research methods and data collection techniques: The content analysis method was used to study the visual identity of the countries. The authors collected logos and scrutinised them using Beyrow and Vogt as well as Mollerup's taxonomy. The results of the study illustrate how governmental institutions, which are responsible for country branding, portray countries using visual identity on the Internet, social media, and their own media.
This paper has aimed to investigate the education – economic development nexus in the selected European Union (EU) countries during the period of 1997 – 2016. Descriptive statistics analysis and econometric techniques have been applied for this purpose. Research results have revealed statistically significant interrelationships between education and economic growth in majority of the selected countries. However, only Belgium, France, Ireland and United Kingdom have demonstrated causal relationships between the variables under consideration. In these countries the unidirectional causality running from education to economic development has shown that increase in the share of population having tertiary education promotes economic performance. In the remaining countries neither increasing share of tertiary education effects on economic development nor growing real GDP promotes tertiary education of the population. The insights of the research could be useful in achieving the goals for Europe 2020, where tertiary education is highlighted as one of the five measurable targets.
This paper has aimed to investigate the education – economic development nexus in the selected European Union (EU) countries during the period of 1997 – 2016. Descriptive statistics analysis and econometric techniques have been applied for this purpose. Research results have revealed statistically significant interrelationships between education and economic growth in majority of the selected countries. However, only Belgium, France, Ireland and United Kingdom have demonstrated causal relationships between the variables under consideration. In these countries the unidirectional causality running from education to economic development has shown that increase in the share of population having tertiary education promotes economic performance. In the remaining countries neither increasing share of tertiary education effects on economic development nor growing real GDP promotes tertiary education of the population. The insights of the research could be useful in achieving the goals for Europe 2020, where tertiary education is highlighted as one of the five measurable targets.
This paper has aimed to investigate the education – economic development nexus in the selected European Union (EU) countries during the period of 1997 – 2016. Descriptive statistics analysis and econometric techniques have been applied for this purpose. Research results have revealed statistically significant interrelationships between education and economic growth in majority of the selected countries. However, only Belgium, France, Ireland and United Kingdom have demonstrated causal relationships between the variables under consideration. In these countries the unidirectional causality running from education to economic development has shown that increase in the share of population having tertiary education promotes economic performance. In the remaining countries neither increasing share of tertiary education effects on economic development nor growing real GDP promotes tertiary education of the population. The insights of the research could be useful in achieving the goals for Europe 2020, where tertiary education is highlighted as one of the five measurable targets.
This paper has aimed to investigate the education – economic development nexus in the selected European Union (EU) countries during the period of 1997 – 2016. Descriptive statistics analysis and econometric techniques have been applied for this purpose. Research results have revealed statistically significant interrelationships between education and economic growth in majority of the selected countries. However, only Belgium, France, Ireland and United Kingdom have demonstrated causal relationships between the variables under consideration. In these countries the unidirectional causality running from education to economic development has shown that increase in the share of population having tertiary education promotes economic performance. In the remaining countries neither increasing share of tertiary education effects on economic development nor growing real GDP promotes tertiary education of the population. The insights of the research could be useful in achieving the goals for Europe 2020, where tertiary education is highlighted as one of the five measurable targets.
In: Wiadomości statystyczne / Glówny Urza̜d Statystyczny, Polskie Towarzystwo Statystyczne: czasopismo Głównego Urze̜du Statystycznego i Polskiego Towarzystwa = The Polish statistician, Band 66, Heft 8, S. 24-45
Innovation is one of the main determinants of economic development. Innovative activity is very complex, thus difficult to measure. The complexity of the phenomenon poses a great challenge for researchers to understand its determinants. The article focuses on the problem of innovation-related geographical disparities among European Union countries. Moreover, it analyses the principal components of innovation determined on the basis of the European Innovation Scoreboard (EIS) dimensions. The aim of the paper is to identify the principal components of the innovation index which differentiate countries by analysing the structure of the correlation between its components. All calculations were based on indicators included in the EIS 2020 Database, containing data from the years 2012–2019. A comparative analysis of the studied countries' innovation performance was carried out, based on the principal component analysis (PCA) method, with the purpose of finding the uncorrelated principal components of innovation which differentiate the studied countries. The results were achieved by reducing a 10-dimensional data set to a 2-dimensional one, for a simpler interpretation. The first principal component (PC1) consisted of the human resources, attractive research systems, and finance and support dimensions (understood as academia and finance). The second principal component (PC2), involving the employment impacts and linkages dimensions, was interpreted as business-related. PC1 and PC2 jointly explained 68% of the observed variance, and similar results were obtained for the 27 detailed indicators outlined in the EIS. We can therefore assume that we have an accurate representation of the information contained in the EIS data, which allows for an alternative assessment and ranking of innovation performance. The proposed simplified index, described in a 2-dimensional space, based on PC1 and PC2, makes it possible to group countries in a new way, according to their level of innovation, which offers a wide range of application, e.g. PC1 captures geographic disparities in innovation corresponding to the division between the old and new EU member states.
Islamic banking is a relative young industry, with a high rate of growth, which in the last years became a highly discussed subject, due to the challenges and opportunities that it brings. Due to the fact, that in the last decade, the Islamic banking made its presence in the European Union market, too, in this paper we try to describe the main features of the Islamic banking transactions and to identify the challenges and opportunities that its brings.
This article investigates the competitiveness of agri-food exports of the European Union (EU-27) countries on global markets, using the revealed comparative advantage (B) index over the years 2000-11. Panel unit root tests, mobility index and the Kaplan-Meier survival rates of the B index are used. The majority of agri-food products in the EU-27 countries show a comparative disadvantage on global markets. The B indices of the EU-27 countries tend to convergence. Most of the old EU-15 Member States experienced a greater number of agri-food products having a longer duration of revealed comparative advantages than have most of the new EU-12 Member States. Among the most successful Member States in agri-food export competitiveness on global markets are the Netherlands, France and Spain. Adapted from the source document.
AbstractStudies have shown that citizens' risk-perceptions and risk-assessment are affected by large scale terrorist acts. Reported evidence shows that individuals are often willing to trade-off civil liberties for enhanced security particularly as a post-terrorist attack reaction as well as adopting more conservative views. Within this strand of the literature, this paper examines whether terrorism and in particular mass-casualty terrorist attacks affect citizens' political self-placement on the left-right scale of the political spectrum. To this effect the Eurobarometer surveys for 12 European Union countries are utilized and ordered logit models are employed for the period 1985–2010 with over 230,000 observations used in the estimations. On balance, the findings reported herein seem to be pointing to a shift in respondents' self-positioning towards the right of the political spectrum.
Social expenditure plays an important role in European Union (EU) countries. It improves the lives of citizens whose welfare is endangered due to poverty or illness. However, social expenditure represents a considerable share of the budgets of EU member states. Despite evident similarities in their levels of development, EU countries show apparent differences in social expenditure levels. Therefore, this work aims to determine the similarities and differences between EU countries in this regard. The analysis uses clustering methods, such as hierarchical cluster analysis and the k-means, to divide countries into homogeneous groups. The research demonstrates significant differences between EU countries in the years 2008-2018, which resulted in a low number of objects (countries) in the identified groups. In the case of 6 out of 28 countries, it was not possible to assign them to any group. The research proves that EU countries should take more care when organising their social policy, taking into consideration cultural and social factors.
In: Wiadomości statystyczne / Glówny Urza̜d Statystyczny, Polskie Towarzystwo Statystyczne: czasopismo Głównego Urze̜du Statystycznego i Polskiego Towarzystwa = The Polish statistician, Band 65, Heft 5, S. 27-44
Digitalization involves an increase in the use of information and communication technologies (ICT) in all areas of the economy and all domains of the functioning of a society. Technologies of this kind affect the level of competitiveness of economies. The aim of the article is to compare the levels of competitiveness of European Union countries in the field of information and communication technologies, on the basis of indices developed by international institutions.The European Commission, World Economic Forum and Eurostat databases were used for comparative analysis of economies. Synthetic indices, such as the 9th pillar of the Global Competitiveness Index (GCI Pillar 9), the European Digital Economy and Society Index (DESI) and the Networked Readiness Index (NRI) were used to compare the levels of digitalization of the economies. The actual individual consumption (AIC) value was adopted as an indicator of the wealth of EU economies. Changes in single indices were analysed as follows: in the NRI in 2014–2016, in the GCI Pillar 9 in 2015–2017 and in the DESI in 2016–2018, while the multi-character classification of countries according to the three variables (the NRI, DESI and GCI Pillar 9) was performed for the year 2016. Ward's hierarchical method and non-hierarchical analysis of k-means clusters were used to this effect. The multiple regression model revealed relationships between the welfare level measured by the AIC and the level of digitalization. The NRI turned out to be the best predictor. The results of the analysis indicate that there are still differences between the 'old' and the 'new' EU countries in terms of the development of the ICT sector.