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The paper analyses the determinants of green development in the Central and Eastern European (CEE) countries pointing out the influence of the sophistication of productive structure and exported goods (economic complexity). The study uses OECD data regarding green development, World Bank Indicators, World Penn Table Data, and MIT Harvard data covering the period of 1996 to 2020, in a heterogeneous panel approach. Fully Modified Ordinary Least Squares (FMOLS) and Dynamic Ordinary Least Squares (DOLS) models are estimated in order to express the influence on green development of the economic complexity index, KOF globalization index, renewable energy consumption, human capital index, and a constructed institutional quality index (computed by using the Principal Component Analysis based on data from World Governance Indicators). All considered variables have a validated statistical influence on green growth in both models. The Dumitrescu-Hurlin causality test revealed a bidirectional causal relationship between institutional quality and green growth and unidirectional ones from economic complexity, human capital and renewable energy to green development and from green development to globalization. Policy implications are also provided.

Central and Eastern European (CEE) countries are struggling with internal and external macroeconomic and social factors in their catching-up strategies to be closer, as economic wealth, to the Western developed European countries. In these ex-communist countries, institutional factors could be seen as critical for success in narrowing the income gap. The paper proposes an analysis of the impact of economic and financial development and globalization on the income gap in 11 Central and Eastern European (CEE) countries (Bulgaria, Croatia, Czechia, Estonia, Latvia, Lithuania, Poland, Romania, Slovak Republic and Slovenia) for the period of 1996 to 2019, taking into consideration institutional factors. The study analyses the variables: transition coefficient as a proxy for income gap, GDP per capita, KOF Financial Globalisation Index, Financial Development Index and World Bank Institutional Indicators in a panel approach methodology and estimation of FMOLS and DOLS equations. The paper’s findings show that all considered factors have a significant contribution to the income gap in the examined period of time. Economic and financial development, as well as institutional quality, is positively associated with the closing income gap, while globalization has a negative influence. It is also revealed the direction of the causality relationship between the considered variables: from economic and financial development, globalization and institutional quality to the income gap. These findings suggest some policy recommendations in support of the continuation of the European integration process.

The paper examines the Environmental Kuznets Curve (EKC) model in the panel of the most complex economies in the world by considering the ecological footprint as an indicator of environmental degradation and economic complexity - as a variable of interest and expression of structural changes in the economy. The study includes the first 48 complex economies in the world, with positive averages of the Economic Complexity Index (ECI) for 1995-2017. The model of cointegrating polynomial regression (CPR) includes also variables with impact on ecological footprints such as globalization, energy intensity and urbanization. The EKC model is validated in the panel of the 48 complex economies, suggesting that these countries have already reached a development stage enabling them to curb the increasing pollution expressed by ecological footprint. Globalization has a mitigating effect while urbanization and energy intensity have an extension effect on ecological footprint. Policy implications are also included.

The aim of the paper is to provide empirical evidence in support of the relationship between renewable energy consumption and economic growth in eleven Central and Eastern European (CEE) countries over the period 1995-2015 within a multivariate panel data analysis. Based on World Bank data, the panel cointegration analysis reveals that renewable energy consumption and economic growth are positively associated in the long run in CEE countries. The heterogeneous panel causality test indicates a bi-directional causality relationship in support of the feedback hypothesis between economic growth and renewable energy consumption in Central and Eastern European countries.

The study aims to explore the real wage convergence across the 42 Romanian counties from 1991 to 2016 by using the convergence algorithm developed by Phillips and Sul (2007). The process of divergence is identified in the period of 1991-2016 as well as a number of 4 convergence subgroups (clusters). Transitional curves indicate that over the long-run the real wage tends to converge. Policy implications of the paper’s findings are also provided.

The paper aims to prove the link between human capital and gross added value in bioeconomy sectors in the EU countries. Data from EUROSTAT data base regarding employment and gross added value in 6 bioeconomy sectors were used in a cross-country regression analysis. The econometric analysis of cross-country data shows a positive correlation between human capital in bioeconomy sectors and their gross output in 2015 in 26 European countries. It is found also that the correlation is stronger in the highly developed economies as in the central-eastern countries, as well as in the European economy.

The paper documents the impact of global competitiveness on economic growth in the EU Member States. In a panel data approach, for a time span of 10 years (2008- 2017), a validated influence of Global Competitiveness Index on annual rate of GDP in the EU countries was found. The impact is higher in the group of Eastern and Central European countries (ECE) than in the Western European (well developed) countries, as well as at European economy level.

The paper explores the association between economic competitiveness and inclusive development in 101 economies based on data provided by the 2018 World Economic Forum reports. Coefficients of ranks correlation and cluster analysis are used in this view. The values of Competitiveness Index and of Inclusive Development Index delivered by the 2018 World Economic Forum reports are considered. Economic competitiveness and inclusive development are positively associated in our sample of 101 economies and the correlation is stronger in the emerging countries as in the group of advanced economies. Among the advanced economies the mean scores of GCI and IDI are higher than in the group of emerging countries showing a better coordination of economic and institutional factors driving competitivity as well as inclusiveness. Countries belonging to a geographical region/continent/economic group are not grouped in the same cluster, emphasizing disparities among countries at regional/continental/economic group level. In the group of emerging economies, the disparities regarding competitivity and inclusiveness are lower than those among the advanced economies, the clusters are closer to one another and they are more homogeneous. Greater competitivity and economic performance can generate socioeconomic inequity that should be corrected through appropriate economic and social policy measures aimed to lead to wider distrbution of income and social inclusiveness.

The aim of the paper is to explore the association between environmental performance and income level in the world economy in 2016. Data from Yale University and World Bank are used in a cross-country regression analysis comprising 166 countries. The gross Domestic Product per capita (based in purchased power parity, constant 2011 international dollars) in these countries is positively associated with the environmental performance index (EPI) calculated by Yale and Columbia University in 2016. Furthermore, the causality of this relationship is from GDP per capita to Environmental Performance and both Environmental Health (EH) and Ecosystem Vitality (EV) are positively associated with GDP per capita. Environmental Health (EH) is stronger related to GDP per capita, meaning that investments in public health, sanitation and infrastructure are increasing as countries develop.

The aim of the paper is to compare the employers' and employees' insights on human capital quality defining and human capital development at organisational level, based on a survey carried out in the county of Satu Mare, Romania. Our findings show that as human capital buyers, employers understand by human capital quality professional background and skills, professional behaviour and efficiency and productivity for the organisation. As human capital sellers, for employees human capital quality means health and the ability to learn and to be suitable to the job requirements. Regarding the opportunities to develop the organisational human capital, the views of employers and employees are very different when the level of discussion is international (macro-level). Employees consider that the international environment has a greater impact on human capital development in their organisation as the employers.

The purpose of the paper is to give an overview of the changes in the structure of industries in Romania, specifically on the questions (1) whether the industrial structures become more similar or more different in the Romanian regions and (2) whether the Romanian industries become more concentrated or more dispersed. EUROSTAT regional data on Gross Value Added and employed population for the period of 2000-2013 are used in order to calculate several statistical indices of specialization and concentration (Krugman, Entropy, Hirschman-Herfindahl, Lilien Index and Gini coefficient). By comparing the values of these different measurements, the main finding is that Romanian regions become less specialized, while industries become slightly more concentrated. The speed of structural changes in all Romanian regions registered a noticeable slowdown of the speed of sectoral changes after the economic crisis. Our conclusions provide useful information for the economic policy makers in investment funds allocation or employment measures designing.