Predictors of Economic Outcomes among Romanian Youth: The Influence of Education-An Empirical Approach Based on Elastic Net Regression.

Young people have to be provided with opportunities to access prosperous, resilient and fulfilling lives. Investing in education and skills is considered one of the most important ways to support young people's well-being and to enable them to enjoy good career prospects. Using the framework of human capital theory, we explored the role of education among the factors explaining wage variation among Romanian youth. We built our analysis on micro-data for Romania from the EU Statistics on Income and Living Conditions 2020. In order to identify the most important factors influencing the wage distribution, we employed the elastic net regression approach. Moreover, we considered the phenomenon of expansion of education and ran the analysis by alternately using a traditional measure for education and a relative measure reflecting the theory of education as positional good. We ran the analysis for different cohorts of the population, focusing the discussion on the results for young people. Our findings confirm the importance of education for wage distribution together with other factors of influence, such as gender, degree of urbanization, region, sector of employment and working experience. Our conclusions are relevant for designing more effective educational and social policies to deal with various disadvantages faced by youth in Romania.

Exploring the Moderation and Mediation Effects in Addressing the Main Determinants of Income Inequalities in Supporting Quality of Life: Insights from CEE Countries.

Income inequality has become an increasingly pressing economic and social problem in Europe, especially in emerging countries with more significant inequalities than the EU average. The high-level inequality persistence can decrease well-being by accentuating the shortcomings at the household level, increasing poverty and social exclusion, generating political instability, leading to a decline in social cohesion, and, finally, a weakening of the Union as a whole. In this context, the paper aims to identify the main determinants of income inequality across the CEE countries and their significant implications in supporting the quality of life and well-being, highlighting the mediation and moderation effects. The analysis focuses on emerging European countries, using panel-based data analysis for ten EU countries covering 2008-2019. The empirical findings highlighted the importance of the minimum wage, high-tech exports, the degree of economic openness, the quality of institutions, and education spending in reducing income inequality. On the other hand, the proportion of the population with a higher education level and the interaction between official and unofficial economies led to income inequality. Therefore, to increase the quality of life, it is mandatory to decrease inequalities. Thus, fewer people will be at risk of living a less qualitative life. The empirical results also proved that the informal economy and the share of people employed in industry exhibited mediating roles. In contrast, the economic growth, the urbanization degree, and the share of people employed in services exhibited moderating roles. Additionally, we also tested the impact of the income inequality determinants of the quality of life, the empirical results supporting the influence of minimum wage, employment with tertiary education, government effectiveness, the degree of economic openness, and education expenditures.

A Bibliometric Analysis of Research Publications of the Bucharest University of Economic Studies in Time of Pandemics: Implications for Teachers' Professional Publishing Activity.

The epidemic has forced the academic world, regardless of nation of origin, to unify to find a response to the economic and social difficulties we confront as quickly as possible. This paper investigates how academic performance in terms of scientific publications, especially during the pandemic period, may constitute the premises for boosting professional well-being. The analysis focuses on the researchers and professors of the Bucharest Academy of Economic Studies, analysing in a comparative way the academic performance during the pandemic as a fundamental side of their professional career. To do that, two samples of scientific publications collected between January 2020 and December 2021 were investigated. The first sample comprised 1411 documents indexed in the WoS database, while the second one was formed by 876 documents indexed in the Scopus database. All samples were published during the pandemic and have the university's affiliation. The empirical findings indicated that the pandemic has created a boost in the number and quality of medical publications for the professors at the Bucharest University of Economic Studies. They created new multidisciplinary teams (economics and medicine), strengthening and widening national and international collaborations.

Determinants of Student Loyalty in Higher Education: A Structural Equation Approach for the Bucharest University of Economic Studies, Romania.

In today's world, the higher education system represents a means of developing the national and global economy by providing individual and collective benefits. Student loyalty is a critical measure in the success of higher education institutions that aim at retaining students until graduation and then attracting them back. As they fuel the knowledge economy, universities create a more educated labor market, providing employment and higher salaries. Having this major significance, it is vital to study the key determinants that persuade stakeholders to form long-term relationships with universities, revealing high loyalty. Aiming to stay competitive and survive the drastic, ongoing changes, successful universities thrive on building loyalty among all stakeholder groups, especially students. Despite the importance of the higher education institutions (HEIs), little research has been conducted on student loyalty. Therefore, the main objectives of this study are to empirically examine the key factors influencing student loyalty by testing two models, namely perceived quality, brand associations, satisfaction, trust, and commitment, and to test the relationships among them. To analyze the data, a confirmatory factor analysis was applied where it explored the associations between items and constructs and, then, utilized a structural equation model (SEM) to investigate the relationships existing between constructs with the application of the STATA program. A structured questionnaire comprising of 66 questions was developed, using a five Likert scale. A total of 682 students from the Bucharest University of Economic Studies filled in the questionnaire. In both cases, the findings reveal that commitment has the most significant direct impact on loyalty. The other factors have an indirect effect, satisfaction having the most significant total effect, followed by trust and commitment. Therefore, universities must focus on improving service quality to develop positive brand associations, student satisfaction, trust, and commitment in developing student loyalty.

What Encourages Longer Educational Careers in Tertiary Education? A Three-Level Approach for the Case of Romanian Universities.

Students' commitment and engagement in the educational process are shaped by a dense combination of factors, with effects on educational attainment and on the length of their educational careers. Decisions of prolonging education by enrolling in master's degrees are beneficial for both individuals and societies, as such programs provide higher levels of specialized skills Longer educational careers are favored by a mix of factors acting at the level of individual, university, or wider environment. We focus our study on exploring factors conducive for students' intentions to pursue master's degrees considering longer educational careers as desirable outcomes. Thus, this article investigates how the individual and environmental factors interplay and shape the predisposition of students to prolong their educational career by enrolling in master's degrees. For this, we applied three-level logistic regression models for a sample of 502 students enrolled in their final year of bachelor studies grouped by universities and universities grouped by counties. The empirical results revealed that the final grade, the father level of education, the type of working contract, and job seniority are individual-level determinants influencing the decision of enrolment in a master's program. At the university level, the type of university and the university performance score positively impact the students' decision to enroll in a master's program. At the county level, the empirical evidence pointed out the significance of determinants such as the proportion of students enrolled in bachelor studies; participation rate in education and training; employment level in high-technology sectors (HTC), total-knowledge intensive sectors (KIS), and knowledge-intensive high-technology sectors (KIS_HTC); proportion of persons with tertiary education employed in science and technology; proportion of scientists and engineers; local development; R&D expenditure, personnel, and researchers in the business sector; average gross earnings; density of active firms; birth rate of companies; proportion of innovative enterprises or those introducing product innovations on the decision to enroll in a master's program.

Exploring Consumer Emotions in Pre-Pandemic and Pandemic Times. A Sentiment Analysis of Perceptions in the Fine-Dining Restaurant Industry in Bucharest, Romania.

This research paper aims to analyse how consumer emotions have evolved during the pandemic period in comparison with the pre-pandemic period in relation to restaurant demand in the Romanian fine-dining industry and uses valuable information based on social-media sentiment analysis and content analysis. Focusing on theories of consumer behaviour, the study aims to emphasize how, under the influence of an epidemic crisis caused by an infectious disease, individual behaviour adapts to the "new normal", embracing a series of changes in the preferences, attitudes, and cognitive choice-making processes. The article takes into account a comparative analysis of the consumer emotions between the pre-COVID-19 pandemic period (2010-2019) and the pandemic period (2020-present), based on the online reviews provided by customers for five fine-dining restaurants from Bucharest, the capital city of Romania: The Artist, Relais & Chateaux Le Bistrot Francais, Casa di David, Kaiamo, and L'Atelier. The research was based on two mining analyses-content analysis and sentiment analysis-and explored the emotional intent of words, with the data being collected from TripAdvisor through web-scrapping. The empirical results defined the fine-dining experience during the pandemic as being associated with the quality of the dishes and also with the quality of the service. The overall consumer sentiment in the direction of the restaurants analyzed is positive. The sentiment research found that throughout the epidemic, the consumers' attitudes about restaurants deteriorated. In this sense, consumers seem to be less satisfied with the restaurants' services than before the pandemic. This is another thing that the restaurants had difficulties in when adapting their operations for the pandemic.

Forecasting the Romanian Unemployment Rate in Time of Health Crisis-A Univariate vs. Multivariate Time Series Approach.

Economic crises cause significant shortages in disposable income and a sharp decline in the living conditions, affecting healthcare sector, hitting the profitability and sustainability of companies leading to raises in unemployment. At micro level, these sharp decreases in earnings associated with unemployment and furthermore with the lack of social protection will impact the quality of life and finally the health of individuals. In time of crisis, it becomes vital to support not only the critical sectors of the economy, the assets, technology, and infrastructure, but to protect jobs and workers. This health crisis has hit hard the jobs dynamics through unemployment and underemployment, the quality of work (through wages, or access to social protection), and through the effects on specific groups, with a higher degree of vulnerability to unfavorable labor market outcomes. In this context, providing forecasts as recent as possible for the unemployment rate, a core indicator of the Romanian labor market that could include the effects of the market shocks it becomes fundamental. Thus, the paper aims to offer valuable forecasts for the Romanian unemployment rate using univariate vs. multivariate time series models for the period 2021-2022, highlighting the main patterns of evolution. Based on the univariate time series models, the paper predict the future values of unemployment rate based on its own past using self-forecasting and implementing ARFIMA and SETAR models using monthly data for the period January 2000-April 2021. From the perspective of multivariate time series models, the paper uses VAR/VECM models, analyzing the temporal interdependencies between variables using quarterly data for the period 2000Q1-2020Q4. The empirical results pointed out that both SETAR and VECM provide very similar results in terms of accuracy replicating very well the pre-pandemic period, 2018Q2-2020Q1, reaching the value of 4.1% at the beginning of 2020, with a decreasing trend reaching the value of 3.9%, respectively, 3.6% at the end of 2022.

Comparative Analysis of Different Univariate Forecasting Methods in Modelling and Predicting the Romanian Unemployment Rate for the Period 2021-2022.

Unemployment has risen as the economy has shrunk. The coronavirus crisis has affected many sectors in Romania, some companies diminishing or even ceasing their activity. Making forecasts of the unemployment rate has a fundamental impact and importance on future social policy strategies. The aim of the paper is to comparatively analyze the forecast performances of different univariate time series methods with the purpose of providing future predictions of unemployment rate. In order to do that, several forecasting models (seasonal model autoregressive integrated moving average (SARIMA), self-exciting threshold autoregressive (SETAR), Holt-Winters, ETS (error, trend, seasonal), and NNAR (neural network autoregression)) have been applied, and their forecast performances have been evaluated on both the in-sample data covering the period January 2000-December 2017 used for the model identification and estimation and the out-of-sample data covering the last three years, 2018-2020. The forecast of unemployment rate relies on the next two years, 2021-2022. Based on the in-sample forecast assessment of different methods, the forecast measures root mean squared error (RMSE), mean absolute error (MAE), and mean absolute percent error (MAPE) suggested that the multiplicative Holt-Winters model outperforms the other models. For the out-of-sample forecasting performance of models, RMSE and MAE values revealed that the NNAR model has better forecasting performance, while according to MAPE, the SARIMA model registers higher forecast accuracy. The empirical results of the Diebold-Mariano test at one forecast horizon for out-of-sample methods revealed differences in the forecasting performance between SARIMA and NNAR, of which the best model of modeling and forecasting unemployment rate was considered to be the NNAR model.

Shedding Light on the Main Characteristics and Perspectives of Romanian Medicinal Oxygen Market.

Medicinal oxygen plays an important role in healthcare, being essential for the existence and maintenance of the health of millions of people, who depend on medicinal oxygen every day, both in hospitals and at home. Medicinal oxygen is the primary treatment administrated to the majority of patients suffering from respiratory problems and low levels of oxygen in the blood, and in the context of the actual health crisis caused by the new COVID-19, the challenge is represented by increasing the supply of medicinal oxygen while reducing cost so that it is accessible where it is needed most, free at the point of use. It will take increased investment and commitment to put oxygen at the center of strategies for universal health coverage. In this context, it becomes essential to investigate the main characteristics of the Romanian market of medicinal oxygen, highlighting top key players, market development, key driving factors, types of products, market perspectives as well as shedding light on the segmentation of this particular market based on considerations regarding regions, hospital competence class and hospital specialization. Also, the research aims to explore the regional disparities in the decision of using O93%medicinal oxygen, revealing the main factors related to the usage of this type of product among Romanian public hospitals. The research relies on the first quantitative survey regarding medicinal oxygen usage among 121 public hospital units from a total of 461 public hospitals in 2018, which meet the specific requirements: includes the entire population according to the list published on the website of the Ministry of Health, is the most recent data and does not show repetition. The sampling was of probabilistic stage-type stratification, with the following sampling layers: hospital county distribution, hospital competence class officially assigned by the Ministry of Health and also area of residence (urban/rural). In order to analyze the main characteristics of the Romanian oxygen market, the following methods have been used: analysis of variance (ANOVA) together with Kruskal-Wallis, Pearson correlation coefficient as well as Goodman and Kruskal gamma, Kendall's tau-b and Cramer's V, as well as multilevel logistic regression analysis using hierarchical data (hospitals grouped in regions). The Romanian market of medicinal oxygen is rather an oligopoly market characterized by the existence of a small number of producers and two types of products currently used for the same medical purpose and having a substitutable character: medicinal oxygen O99.5%, and medicinal oxygen O93%. An overwhelming proportion of public hospitals agree that both types of medicinal oxygen serve the same therapeutic purpose. The Romanian market of medicinal oxygen highlighted a significant segmentation on considerations based on regions, hospital competence class and hospital specialization. Regarding the main perspectives, the Romanian market of medical oxygen keeps the growth trend registered globally, with development perspectives for competitors. Exploring the regional disparities in the decision of using O93 medicinal oxygen, the empirical results acknowledged the important role of unitary price, hospital capacity and the relevance of this product seen as a medicine. Medicinal oxygen is vital in sustaining life, proving its utility mainly in the context of the actual health crisis. In this context, the Romanian local market exhibits prospects for further development, being characterized by an important segmentation depending on regions, hospital competence class and hospital specialization.

Assessing the vulnerability of water resources in the context of climate changes in a small forested watershed using SWAT: A review.

The present study evaluates the applicability performance of the Soil and Water Assessment Tool (SWAT) in small forested watersheds (less than 1000 km2). This open-source software is widely used in investigations focused on water availability and quality. Overall, SWAT model performance ranges between satisfactory to good. Normally, underestimates daily peak discharges. The limitations of the model are related to the accuracy of climate data used and to the time period used for validation. Watershed area, forest cover and streamflow spatial distribution have an important influence on modeling processes. Overall, from the analyzed studies, we observed for discharge a decreasing tendency, more pronounced towards the end of the 21st century (up to -54%). For surface runoff, was noticed the same decreasing tendency up to 41%. Regarding sediment yield, the results vary within very wide limits. These findings vary according to watershed location, scenarios adopted, and the eligible period of time.

Torrential flood risk assessment and environmentally friendly solutions for small catchments located in the Romania Natura 2000 sites Ciucas, Postavaru and Piatra Mare.

The management of torrential flood risk areas located in natural protected sites requires special approaches. Also, those processes can cause casualties and damage socioeconomic structures (roads, railways, houses, etc.) The processes intercept protected landscapes, sometimes endangering protected species and habitats. The restoration of the streambed's stability in protected areas and the protection of the economic objectives affected by the torrential floods, imply special measures of planning. The planning measures are based on the use of ecological materials and technologies with minimal impact on the environment. The article presents a methodology for identifying small river basins with high torrential risk and the endangered economic objectives, as well as applying this methodology into three Natura 2000 sites from central Romania (ROSCI0207 Postavaru, ROSCI0195 Piatra Mare and ROSCI 0038 Ciucas). Identification of the basins was made considering their geomorphological and hydrological characteristics and the vulnerability of the intercepted socio-economic objectives. Into identified watershed, measurements of the streambed topography and the geometric characteristics of the endangered structures were made. Based on hydraulic simulations, maps were generated for floods with a 100-year return period. Using these flood maps, the maximum water level was determined to highlight the flood risk areas for each socioeconomics structural objective. In areas identified as floodplain, special structural and nonstructural solutions are proposed for guiding water into convenient paths to avoid the endangered structures.