Search

The main purpose of this study is to investigate the application of predictive analytics techniques in the energy field and to identify strategies to stimulate renewable energy production. The analysis begins by examining four key indicators: renewable energy, gas price, gas consumption and renewable energy consumption through a detailed descriptive analysis. Visual graphs are built to get an overview of the evolution of the energy sector in the period 2011-2020 with the help of Tableau software. The analysis is supported by the use of the Random Forest algorithm as a prediction model, considering critical indicators such as gas price, gas consumption and renewable energy consumption. The prediction results provide insight into anticipating changes in renewable energy production in the European countries studied. At the same time, the study highlights the current situation of renewable energy in Europe and identifies the necessary measures for its sustainable development through the analysis of specialized literature. It also examines the way in which big data management, facilitated by technologies such as smart meters and drone sensors, can help improve the energy sector. This research offers valuable results, providing insights into the evolution of renewable and fossil energy, as well as a detailed comparison of renewable energy, gas prices, gas consumption and trends in renewable energy consumption. By integrating predictive analytics techniques, data management and renewable energyspecific indicators, this study makes an innovative contribution to energy systems analysis. Its focus on European countries contributes to the understanding of the growth potential of renewable energy generation in this region.

The lack of data for many indicators and the existence of significant gaps in the availability and comparability of data is a problem of global interest, felt by authorities and agencies specialized in data collection, analysis and use. Their objective is to provide data and indicators of good quality, which will help to correctly inform the political decision-makers and to solve the inequalities in the field of health. Thus, this paper aims to provide clear and coherent solutions to a number of problems identified in data management in general and in the medical sector in particular. The added value of this paper consists in a case study, which presents an x-ray of the current situation of data quality through the analysis of metadata. The research methodology used in the paper includes a swot analysis on the quality of health data, using metadata from three sources corresponding to distinct levels of aggregation: National (Romania), European and Global.

This paper makes a review of the most popular graphical user interfaces (GUIs) in order to help new and unexperienced users learn and use R. Although R is free and benefits from state-of-the-art implementations of statistical algorithms and methods, it is not the first choice among statistical software users. This can be attributable to a lack of user-friendly interfaces similar to the ones available for other statistical packages. However, there are several GUIs that enable R users to use it quickly and effectively without having to use interactive programming and learn R code. For standard statistical analysis, RCommander proves to be the best solution that not only offers standard functionalities that are similar to commercial statistical software, but allows users to visualize, use, and customize the codes that perform standard data and statistical procedures, thus helping them to effectively learn R. For more advanced users, there are two main specialized GUIs RStudio, which facilitates the use of R through the use of scripts and generation of interactive applications and reports, and Rattle, specialized for data mining procedures and algorithms.

The reliability and comparability of international migration statistics belong to the most important statistical issues due to the importance of correct dimensioning of the migration flows and stocks for effective and timely design of effective policy measures. This paper presents an assessment of the migration statistics provided by Eurostat, reveals the most prominent discrepancies between stock and flow data, prepares a summary of vital issues affecting both quality and completeness of the migration data, and identifies certain solutions in order to improve data comparability, reliability and completeness. There is no one-size-fits-all solution, but an eclectic mix which extends the use of administrative and private data, matches data coming from distinct sources, harmonizes the way in which data is compiled and reported by different countries, matches observed flows with (demographic) stock-based estimates, provides consistent estimates of the bilateral migration flows between countries, and improves the measurement of temporary and illegal/undeclared migration.

Romanian economy’s transition process began suddenly and was accompanied by disintegration of former political and economic system. In terms of GDP per capita, Romania has been one of the poorest countries in Central and Eastern Europe. Also, the Romanian economy was one of the most agrarian economies in Europe. Completely isolated from the informational point of view, Romania had a fully centralized economic system. Beginning of transition was completely chaotic, especially because of the complexity of integrating the fundamentals of democracy and market economy. Internal problems, instability, political corruption or lack of appropriate reforms have led to a difficult restructuring and privatization process.In this paper we present and analyze the tendencies and vulnerabilities on Romanian labor market between 19991 and 2009 versus EU member states. There were identified three shocks with major social impact on Romanian economy: the revolution in December 1989; the EU accession in January 2007 and the world economic crisis began in 2007. These three structural shocks have deeply influenced and still do the evolution of Romanian labor market.

This paper analyses the correlation between social security budget and the main macroeconomic indicators (like GDP, monthly average gross earnings, unemployment) in Romania during the period 2000 – 2009. Romania faces a more severe economic recession than originally anticipated. Although the implementation of anti-crisis program was able to lead to normalization of financial conditions, the contraction of economic activity is higher than initial projections. Because of the great policy debate in Romania about the impact of the reduction of pensions and salaries and increases of taxations on the reduction of budget deficit, we have explained in our paper the basic sides of the balanced budget debate. There are three basic sides to the balanced budget debate. The traditionalists argue for a reduction of the budget deficit since it harms the economy. Another group holds the Ricardian view of government debt in believing that there is no real harm done to the economy by the national debt. A third group claims one way or another that the budget deficit is not an adequate measure of fiscal policy. We will argue which of these views is most reasonable, based on a study case. The study is based on official data published by the National Institute of Statistics, with the specification that they are transformed into real values in order to assure the data comparability. The methodology used is the correlation analysis, the factorial analysis and the regression analysis, in order to evaluate the impact of some macroeconomic policies on the budget deficit. Three hypotheses on macroeconomic policies are discussed in the paper and their influences on the budget deficit. The main problem in Romania was that the macroeconomic policies didn’t give enough attention to budget deficit in order to keep it under control. This is the main cause of the actual unfavourable economical situation in Romania, with a huge budget deficit, with a decrease in economic activity, with increases of inflation and unemployment. Among the variables used in the study we mention: total incomes, total expenditure, budgetary deficit, unemployment rate, monthly average net earnings, average number of pensioners and social allowance recipients, monthly average pension of pensioners and social allowance recipients, economically active population, monthly average inflation rate. By analysing the correlation between all the studied variables we observe that there is a strong correlation between monthly average pension and monthly average net earnings. Increases in the level of earnings will determine the increase of budget deficit. At first view the macroeconomic policy adopted by the actual government in Romania (the cut with 25 % of salaries in the budgetary system, VAT increase) will have as a result the decrease of budget deficit. Since the monthly average net earnings is correlated with unemployment and inflation rate, the reduction of the general level of earnings will determine the increase of unemployment and inflation. Therefore this policy should be applied with caution, taking in parallel measures to compensate its adverse effects. The impact of some of the macroeconomic policies on budget deficit is studied using two regression functions. After an econometric analysis we shall conclude about the influence of the dependent variables of these functions on the Romanian budgetary deficit.

The labour market is constantly changing due to the development of technology. Technology is expanding as the need for data processing, analysis, and use increases. Technology not only becomes more skilled than man, but also urges him to live faster. Technology makes economic processes easier and faster. The human resource will assume the role of orchestrator of technology, but in order to do so, it must be available to learn permanently. The case study will focus on describing the main benefits of continuous learning for the workforce. For employees, the accumulation of new knowledge gives them the opportunity to improve their skills. For the unemployed, continuous learning gives them the opportunity to get hired. Therefore, we will identify whether employees are more interested in continuous learning. Additionally, we will identify whether the occupation that employees have influences the rate of participation in continuous learning. As the labour market is placed in the context of industrialisation 4.0, it is necessary to talk about continuous learning in the direction of digitalisation. In the digital economy, it is important that the workforce has at least a basic knowledge of technology in order to keep their job. Technological unemployment occurs precisely because the human resource is exceeded by the new demands of the workplace. Thus, we will identify the level of digitisation at the European level but also the way in which the population has acquired digital skills. We will also highlight the fact that the share of people with ICT skills and knowledge is higher in the case of employees than in the case of the unemployed. The purpose of the paper is to present comparatively the benefits that continuous learning has for both a person who already has a job and a person without a job, but also the impact that the industrial revolution 4.0 has on continuous learning.

In the case study we aim to analyse the long-term distribution of vacancies on the Romanian labour market. This approach allows us to identify one of the long-term consequences of the digitalization of the economy, namely polarization. Polarization can be viewed from several perspectives, but here we are only referring to the polarization of the job supply. The phenomenon implies a significant reduction in interest in mid-level jobs. Thus, to identify the probability that this phenomenon will already manifest itself in Romania, we carried out an analysis with the help of Markov chains. In this way we will identify the occupations that could be the most numerous in the long run in Romania. Even if Romania does not indicate an obvious polarization of the labour market, in the long run, clues in this regard can be identified. There is a system of vocational training at national level, but it does not cover the prospects of the labour market.

Given the advent of Industry 4.0 and the importance of labour-based automation in ensuring competitiveness at the firm, regional cluster, or country level, the paper aims to explore, for the first time, the features of several estimates of occupational/labour automation and to assess the potential risks associated with it. A comparative analysis of the most well-established estimates of labour automation, the Occupational Information Network (O*NET) degree of automation estimates and Frey and Osborne’s future probabilities of automation was carried out to see whether, and to what extent, these estimates are compatible. Results show significant distributional differences between them, which are quantified into automation-triggered disruption risks at the occupational level, as current levels of labour automation are, in some cases, well below their future estimates. Work context features were used to derive a typology of occupations, which can explain up to one-third of the current, and up to half of the future levels of labour automation. Finally, we identified which occupations and occupational groups are likely to be affected by the highest risk of automation-induced displacement and estimated the magnitude of different disruption classes. Conclusions are compatible with other economywide assessments of the impact of labour automation on the workforce, thus being valuable inputs for corporate strategy, decision-makers and human resource planners as they address a growing need for quantitative insights useful for adapting the labour force structure, workers’ skills, and the task content of occupations to the competitiveness requirements related to the process of digitization in the Industry 4.0 context.

Whether we like it or not, technology has become part of our lives and, at the same time, it has undoubtedly helped people become more informed and connected. Reducing healthcare costs and improving patient outcomes are benefits of implementing modern technologies in the medical sector. Digital health can significantly improve the productivity of an organization or nation, including at the individual level, and if digital healthcare solutions are made at an affordable cost, digital health could be a response to emerging market challenges to grow sustainable and improve health systems to provide patient-centred care, meaning accessibility and quality. This paper assesses trends in demographic evolution and their influence on digital health innovation as well as emerging trends as a result of healthy aging. [ABSTRACT FROM AUTHOR]

When we mention social inclusion, most of us think of political participation, social rights, civil liberties, equal access to race, ethnicity and gender, access to social services and the labour market, basically to a broader concept than social development. Social inclusion is a concept that can actually be defined, which means it can probably be measured. On this basis, a continuous effort is being made to measure the social inclusion elements, so the results can be used to build new indicators that help measure the multiple dimensions of social inclusion: The Social Inclusion Index, the Human Opportunity Index. This paper presents the development, based on multivariate data analysis techniques and methods, of an aggregated indicator of social inclusion for the member countries of the European Union which, besides the traditional variables (GDP), also measures the factors related to civil and political rights, women’s rights or perception of the LGBT community. First published online 06 October 2021

The established variable selection methods for building composite indicators have strong limitations with respect to the results obtained. Some of them focus on getting an index structure with a high alpha reliability and/or a high percentage of the total data variance explained. These methods are likely to omit variables with strong explanatory power, and lead to an unsatisfactory classification of countries. Decision trees can also be used in selecting variables that are the most relevant for building composite indicators. An example of variable selection for building a composite indicator, which compares results using Cronbach's coefficient alpha, factor analysis, and decision trees, shows that the latter method yields comparable, or better results. Using cluster analysis on the selected variables, we show that the decision tree variable shortlist has better discrimination power than those obtained with the other methods, even in the presence of outliers and missing values.

Social exclusion may manifest through spatial concentration of deprived population in communities located in certain areas. The globalization has reshaped the social and spatial geography of cities which led to major implications for research on social exclusion. Thus, in any practical formulation of social inclusion policies, it is necessary to consider the idea that social exclusion is inherently spatial. By addressing the territorial dimension of social exclusion, some important theoretical issues about the interaction of the two concepts ("social" and "space") are analyzed. Based on theoretical-conceptual contributions developed recently, this paper analyzes this dimension of social exclusion. [ABSTRACT FROM AUTHOR]

The objective of the article is to investigate the phenomenon of economic development in old member states (EU15) in two period: 2000-2007, regarded as the boom period, and 2008-2010 which is considered to be the post-boom period. Particular emphasis will be set on the GDP per capita in Purchasing Power Standards, on the real GDP relationship between GDP growth and public debt. [ABSTRACT FROM AUTHOR]

Many European and non-European countries face different forms of discrimination on the labor market: it's about gender discrimination, religion discrimination, race, nationality, physical disability, age or political options discriminations. Equal opportunities and combating discrimination in any form is one of the basic principles of the European Strategy for Sustainable Development. This article aims to present the point of view of future economic graduates on the main types of discrimination in the labor market in Romania, the degree of discrimination and the intensity of the phenomenon. This goal is achieved by conducting a survey among the third-year students of an economic university (The Academy of Economic Studies in Bucharest). The survey is developed within SPIN project, co-funded by European Social Fund. [ABSTRACT FROM AUTHOR]

The demographic dynamics analysed in the context of the relationship between economic development and social inclusion presents an image of the sustainable development of a community as well as the manner how the financial resources have been used. With an allocation of 74.3 million euro in the programming period 2007-2013, the Brasov Growth Pole has pursued the contribution to the achievement of sustainable development since 2005 by the participation in the Agenda 21. The implementation of projects with European financing in areas such as transport, social and educational infrastructure or tourism have generated changes/demographic movements, which this paper proposes to present. The evolution of the stable population, its dynamics at the level of each locality that is part of the Brasov growth pole as well as the dynamics of the number of employees or the development of the unemployment rate are presented by the cluster analysis. The effects of the European financing obtained from Regional Operational Programme 2007-2013 are thus reflected in the sustainable development of the Brasov growth pole from the point of view of the dynamics of the population

The purpose of the article is to illustrate the importance of the output gap in analysing macroeconomic stability in general and business cycle dynamics in particular. Ten EU countries are considered, with five old members and five new members. For all ten countries the data for the period 1999-2014 is used, but for four countries, namely France, the United Kingdom, Italy and Spain additional data is available that goes back to 1965, such that the whole period 1965-2014 is covered, which allows for a particular analysis. An empirical analysis is performed with regard to the behaviour of the output gap for different countries over time. The results obtained allow for relevant comparisons and highlight the usefulness of this indicator as a tool in the study of business cycles.

In today’s rapidly evolving financial markets, risk management offers different techniques in order to implement an efficient system against market risk. Probability of default (PD) is an essential part of business intelligence and customer relation management systems in the financial institutions. Recent studies indicates that underestimating this important component, and also the loss given default (LGD), might threaten the stability and smooth running of the financial markets. From the perspective of risk management, the result of predictive accuracy of the estimated probability of default is more valuable than the standard binary classification: credible or non credible clients. The Basle II Accord recognizes the methods of reducing credit risk and also PD and LGD as important components of advanced Internal Rating Based (IRB) approach.

The problems concerning the labor resources are actual guidelines in scientific research field and in practical applicability; this domain has major implications on every economical-social structure. Labor force has an important place, together with the capital and the patrimony, in the production activity. Reducing the employment and the growth of the unemployment were declared within the Treaty of Amsterdam (1997) "urgent problems". The paper presents the main statistical methods used in analysis of the employees’ fluctuation, as well as the main informatics solutions used in applying these statistical methods and the obtained results.

In view of knowing the essence of phenomena it is necessary to perform statistical data processing operations. This allows for shifting from individual data to derived, synthetic indicators that highlight the essence of various phenomena. The high volume and diversity of processing operations presuppose developing plans of computerised data processing. To identify distinct and homogenous groups and classes it is necessary to realise well-pondered groupings and classifications that presuppose to comply with the requirements presented in the article.