Suchergebnisse

Svrha ovog rada je istražiti neke od glavnih uzroka visoke stope nezaposlenosti u zemljama Europske unije polazeći od dva ključna izvora u ekonomskoj literaturi: nedostatak ukupne potražnje i sve veće nepodudarnosti na tržištu rada. Analiza je provedena na temelju panel podataka i fokusira se na dva cilja: izmjeriti kratkoročni i dugoročni utjecaj rasta BDP na nezaposlenost za razne kategorije sudionika na tržištu rada (mladi, stari i radnici s nižom stručnom spremom) i ocijeniti odnos nepodudarnosti između vještina (obrazovnih i profesionalnih) i nezaposlenosti. Jedan od glavnih zaključaka jest da su promjene u stopama nezaposlenosti mladih i nisko obrazovanih osoba uvelike pod utjecajem dinamičnog ekonomskog rasta kako dugoročno, tako i kratkoročno, dok stope nezaposlenosti među starijima ukazuju na veću mogućnost prilagodbe. Nadalje, izgleda da profesionalna nepodudarnost ima značajan dugoročni utjecaj na promjenu u stopi nezaposlenosti svih kategorija nezaposlenih, dok je kratkoročni utjecaj mješovit i varira od zemlje do zemlje. Jedno objašnjenje je činjenica da se ekonomska struktura za vrijeme krize može mnogo brže mijenjati nego što se tržište rada i obrazovni sustav mogu prilagoditi. ; The purpose of this paper is to investigate some of the main drivers of high unemployment rates in the European Union countries starting from two sources highlighted in the economic literature: the shortfall of the aggregate demand and the increasing labour market mismatches. Our analysis is based on a panel database and focuses on two objectives: to measure the long and short-term impact of GDP growth on unemployment over recent years for different categories of labour market participants (young, older and low educated workers) and to evaluate the relationship between mismatches related to skills (educational and occupational) and unemployment. One of the main conclusions is that unemployment rates of young and low educated workers are more responsive to economic growth variations both in the long and short run, while unemployment rates of older workers show a greater capacity of adjustment. In addition, occupational mismatches seem to have a significant long-term impact on the changes in unemployment of all categories of unemployed, whereas the short run effect is rather mixed, varying across countries. One explanation is the fact that during crisis, economy's structure tends to change more rapidly than labour market and educational system can adapt.

Our article aims to present an in-depth analysis of the correlation between health status and poverty in European countries. Our research is grounded on two types of data: a survey of the perceptions of the European citizens related to their own physical and mental health conducted in 2017 in European Union countries and the United Kingdom on a sample of 28,000 respondents and macroeconomic data retrieved from Eurostat Database, showing the incidence of poverty and working poor in Europe during the 2017-2019 time span. Multiple logistic regression has revealed that self-rated health status is influenced by the sociodemographic characteristics of the respondents, whereas TwoStep Cluster analysis and Mann-Whitney U test proved that health is an important driver of the differences between countries in terms of poverty and working poor. The originality of our research stems from both the integrated approach, the analysis being made at individual, group, and country levels, and by the results that bring new evidence about population health status as a determinant of quality of life and national competitiveness.

The aim of the study is to deep dive into the potential of green entrepreneurship and its drivers in a time of multiple challenges when green growth seeks to reconcile economic and sustainable development goals. The need for responsible business models has become evident in recent years, and companies that offer green products or services are creative, eco-friendly growth incubators and important economic actors that can change the future of society. We used a logistic regression model for 7326 companies from 36 European countries to identify what influences the decision to go green, including supply and demand factors, measures for resource efficiency and targeted policies. We found that the company's age, its financial performance, the country's level of development, as well as the incentive measures have a significant potential of stimulating green entrepreneurship. Our results highlight the overwhelming importance of financing. Firms in less developed countries face difficulties in developing green products and services, so support programs are needed to build green entrepreneurship in some regions. Many entrepreneurs in less developed countries are highly educated, creative, and innovative, so they can successfully run sustainable business models if the transfer of good practices is accompanied by an infusion of capital.

This article addresses the problem of the main factors driving sectoral unemployment in the Mediterranean countries most affected by this phenomenon. The choice of the four countries (Greece, Italy, Spain and Portugal) relies on the fact that they are dealing with the highest unemployment rates in the European Union and a certain typology of the economic structure. The originality of our research is offered by its direction, less tackled until now, namely the focus on the particularities of the economic sectors, trying to capture differences between them. The importance and the impact of the results are supported by the methods used to produce them, indicators and econometric models that are on trend and bring extra information to available studies. Descriptive statistics and mismatch indexes are used to outline the economic and labour market structure, while the econometric models built on panel data capture the impact of factors such as GVA growth, specialization and labour market mismatches on the unemployment rate at six economic sectors level. Our paper makes three contributions to the literature. First, we have demonstrated that agriculture is the sector of activity less sensitive to output fluctuations in terms of unemployment and can become a buffer for the jobless in times of recessions. Second, we have proved that industry, as a whole, is highly responsive to economic developments and bad specialization could worsen unemployment situation in this sector. Third, we showed that educational mismatches have a significant impact on unemployment in those sectors of activity that employ low educated workforce.

This article addresses the problem of the main factors driving sectoral unemployment in the Mediterranean countries most affected by this phenomenon. The choice of the four countries (Greece, Italy, Spain and Portugal) relies on the fact that they are dealing with the highest unemployment rates in the European Union and a certain typology of the economic structure. The originality of our research is offered by its direction, less tackled until now, namely the focus on the particularities of the economic sectors, trying to capture differences between them. The importance and the impact of the results are supported by the methods used to produce them, indicators and econometric models that are on trend and bring extra information to available studies. Descriptive statistics and mismatch indexes are used to outline the economic and labour market structure, while the econometric models built on panel data capture the impact of factors such as GVA growth, specialization and labour market mismatches on the unemployment rate at six economic sectors level. Our paper makes three contributions to the literature. First, we have demonstrated that agriculture is the sector of activity less sensitive to output fluctuations in terms of unemployment and can become a buffer for the jobless in times of recessions. Second, we have proved that industry, as a whole, is highly responsive to economic developments and bad specialization could worsen unemployment situation in this sector. Third, we showed that educational mismatches have a significant impact on unemployment in those sectors of activity that employ low educated workforce.

[Abstract] 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 meaningful impact on the economy and the society in the European Union in the next period. That is why a positive attitude towards digitalisation is essential for transforming this relatively new challenge into an excellent opportunity for the future. ; PNCDI III Program – Project "Understanding and modelling time-space patterns of psychology-related inequalities and polarization", PN-III-P4-IDPCCF-2016-0084 ; Rumanía. Unitatea Executiva Pentru Finantarea Invatamantului Superior a Cercetarii Dezvoltarii si Inovarii (UEFISCDI); PN-III-P4-ID-PCCF-2016-0084

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 meaningful impact on the economy and the society in the European Union in the next period. That is why a positive attitude towards digitalisation is essential for transforming this relatively new challenge into an excellent opportunity for the future.