The main purpose of this paper is to study the influence of various indicators related to the knowledge economy on country competitiveness in the European Union (EU). Based on the Pearson coefficient and panel-data regression models, we analyzed the Global Competitiveness Index (GCI) in relation to research and development (R&D) expenditure (as a % of gross domestic product (GDP)), percentage of population with tertiary education, lifelong learning, GDP per capita, and debt to equity. The findings highlighted the crucial role of both innovation and education as determinants of EU competitiveness and economic convergence. The development of EU policies regarding the lifelong learning possibilities of the European workforce and the focus on research and development activities can significantly contribute to the competiveness of EU member states.

The new technologies, the digitalisation of processes and automation of work will change the manner of doing business, working and living. The effects of digitalisation on the economy, society and quality of life imply significant challenges of the labour market. All the participants will be concerned: authorities, companies and ordinary people. The objective of this research is to analyse the perceptions of the EU citizens about digitalisation and to highlight the differences among specific socio-demographic groups. The analysis is grounded on a composite methodology, comprising several statistical and econometric methods that provide scientific support to achieved conclusions: statistical analysis (with the primary goal to shed light on the EU citizens' perceptions about their digital technology skills), TwoStep Cluster Analysis (TSCA) (with the purpose to identify the 'digital vulnerable groups' and then the 'digital vulnerable countries' in terms of the exposure to digital divide) and logistic regression (with the main aim to quantify the impact of the relevant factors on citizens' perceptions about digitalisation). We identified a group of respondents evaluating themselves as having meagre digital skills, very afraid that robots could steal their jobs and with low usage of the internet. They are elderly, with a low level of education, manual workers or not working, with a relatively low level of income and little Internet use. The originality of our approach is given by the fact that we focused on investigating if digital divide leads to the creation of vulnerable groups (citizens and/or countries) and if there are specific patterns in terms of the perception on being skilled in the use of digital technologies in daily life or at work and of the understanding that robots replace human on the labour market. We aim to find relevant factors for the labour market to assume targeted measures that should be taken for a better match of supply and demand on the labour market and for creating a smart labour market. It is highly needed to increase the people's confidence in their skills level and to make the most of digitalisation of the societies. The results show consistent patterns in term of socio-demographic characteristics and perception towards digitalisation. The latter will have a

Abstract:In the aftermath of Angola's civil war, strong economic relations developed between the country and the People's Republic of China. Our study addresses China's investment risks in Angola, considering an infrastructure-for-petroleum partnership between these two countries. The main working hypothesis is that the recovery of Chinese investments made in Angola is has translated into thousands of barrels of petroleum being imported daily from Angola. We analyzed the main economic, social, and political indicators that describe the situation in Angola that could impact the recovery of Chinese loans in the form of oil exports. Data processing implied involved regression-based imputation, MinMax data normalization, the use of the Analytical Hierarchy Process (AHP), and econometric analysis, next to the construction of a composite risk indicator. The results of the econometric analysis highlighted that an increase in the composite risk indicator of 1% leads to a decrease in the quantity of petroleum exported by almost 6377 barrels per day. Because, at least in the short run, the economic diversification in Angola is weak, and the most important asset is its oil, the partnership with China will continue to exist. This cooperation model represents a source of economic growth and infrastructure development for Angola and a source of energy that fuels China-one of the most powerful economies in the world.

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