Suchergebnisse

This paper aims to provide an analysis of the interaction between human, economic and social development in Romania, in the period 2010-2019. To facilitate the examination of the human development, I have used the human development index and its components, while the economic development has been examined using gross domestic product per capita and its determinants. On the other hand, in the case of social development, I have used the poverty rate and other relevant indicators. The conclusion of the paper is that Romania has been on an upward trend in terms of development in the post-crisis period, but further progress are needed to be able to mitigate the development gaps towards the European Union.

This paper provides an analysis of the human development drivers in the European Union. The variables used cover the 2010-2017 period, during which the Member States have faced different economic and social challenges generated by the global economic crisis. In the analysis, I used Panel Estimated Generalized Least Squares, weighted with the Period SUR option. The paper confirms a direct relationship between three independent variables (life expectancy, corruption perception index and gross fixed capital formation) and the dependent variable - the human development index. In this context, the study demonstrated that a decrease in the dimension of corruption leads to an increase in the human development, since the growth of corruption perception index is associated with a fall in the corruption dimension. On the other hand, an inverse relationship was identified between the other two exogenous variables (the share of people leaving education and training early, respectively employment in agriculture) and the human development index.

This paper analyse the way how the sustainable developments components are interacting between them and reflects on a possible trade-off between social, human, economic, technological and environmental progress. In this context, I have computed the Pearson correlation coefficient between the mentioned forms of development for 2010-2018 period, but in some cases, my analysis was limited to a lower period due to the data availability. At all, I have concluded that social, human, economic, technological and environmental development are positively linked, but the link between technological and social development depends on the degree of automation which may spread certain social imbalances across the European Union on short-run. However, the link between social and technological development remain positive when it is assessed through the digitalisation channel or the growth of the IT&C sector.

This paper examines the economic development drivers and the ones of the social development in order to check if there is a potential trade-off between these development forms at the level of European Union, with a focus on human development and technological progress. In this context, I have used panel yearly data covering the period 2010-2018 for EU Member States. Both models were estimated using Panel Estimated Generalized Least Squares and some weighting options as Period SUR and Cros-section weights. However, the specificities of the data led to a different application of the methods in the case of the mentioned models. In this regard, I have run a Fixed Effects Model in studying the determinants of economic development and a None Effects Model when analysing the drivers of social development. The main results of the paper showed a positive relationship between human development and social and economic development. In adition, the study estimated a positive impact of ITC sector on economic development and a negative one on the poverty rate. However, the negative impact of ITC on social development is quite low and it may also include a positive impact on poverty (lower than the one manifested through the opportunities channel) exercised by automation, but this needs to be further explored. Both models provided feasible results which strengthens the confidence in the examined relationships.

This paper aims to provide an analysis of the determinants of poverty rate in ten Member States of the European Union from the Central and Eastern Europe, and of the way how its influenced poverty in the 2009-2016 period. In order to estimate the impact, I used panel technique and Estimated Generalized Least Squares method with no effects, weighted by Period SUR option to provide more consistent estimators. To verify if the model is correctly specified and to confirm the maximum verisimilitude of the estimators, I tested the Gauss-Markov. The conclusion of the paper is that the unemployment rate, rural population, as well as the early leavers rate of people aged between 18-24, have a positive impact on the rate of people at risk of poverty rate after social transfers. On the other hand, the government spending on social protection has a negative impact on the used dependent variable.

In this paper, we estimated the impact of COVID-19 shock on the industrial production and on the confidence in industry at European Union level, using Panel EGLS method - weighted by Cross-section SUR option. The negative impact we found on both indicators is quite high and may severely affect the economy, in the absence of political support and in the case of prolonging COVID-19 crisis or starting another lockdown waves. The largest drops of industrial production were found in Italy, Slovakia, Romania and Hungary, while Latvia, Malta, Finland and the Netherlands were less vulnerable to the COVID- 19 shock. Through this paper, we also identified a high similarity between the dynamics of industrial production and the industrial confidence index. The outlooks are still exposed to uncertainty, but these have been improved in the latest months.

This paper examines the impact of financial risks on economic growth in the first 15 Member States of the European Union, considering 1995-2014 period and aims to lay down a new explanatory model of economic growth, based mainly on the behavioral reactivity of the financial disruptions mentioned above. The model was estimated through the panel estimated generalized least squares method and included additional control variables in order to strengthen the research conducted. Our goal consists in the examination of the financial risks in the European Union and in the estimation of their impact on economic growth.

This paper assesses the impact of telework on economic growth in the European Union using Feasible Generalized Least Squares method, applied to a Panel of 27 Member States, in the period 2010-2019. The econometric model also analyses the impact of the rate of employed population not working from home on the economic growth, to facilitate the comparative analysis of telework and traditional work. The results indicate a greater impact of telework on economic growth, than that exerted by the rate of employed population not working from home, the effect being manifested through the channel of labour productivity. However, the paper examines the short-term relationship between these variables and does not exclude the reduction of the impact of telework on economic growth to a lower level than the specific effect of traditional work, on medium or longterm.