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Research background: Digitalization in the context of the COVID-19 pandemic has accelerated significantly across Europe, including in regions that are at the stage of catch-up development. However, as innovative technologies are intensively integrated into everyday life, the digital gap between the EU countries is increasing. The widening digital gap is becoming a serious threat to achieving the EU's sustainable development goals and building a sustainable European society. Purpose of the article: The purpose of the article was to empirically substantiate the inclusiveness and convergence of the digital strategy in the EU countries. Methods: Using the method of fuzzy sets, the level of asymmetry in access to transactional (e-commerce), information (cloud computing), operational (artificial intelligence) technologies in the EU countries was assessed. The negative impact of the digital gap within the countries (the gap between small, medium, large companies) and the global digital gap (the gap between EU countries) on the competitiveness of countries was established, for which correlation analysis and the Granger causality test were used. Findings & value added: The findings of this study contribute to the literature of digital transformation and digital gap of European countries. The impact of the digital gap in transactional, information, operational technologies on the competitiveness of countries is differentiated depending on the level of digitalization of the country. Cluster groups of countries are determined by the convergence of digitalization and ways to ensure long-term competitiveness. The directions for reducing the digital gap in the EU countries are substantiated by changing the priorities of spending on innovation and increasing productivity, diversifying the digital technologies used. The empirical results obtained can serve as a basis for improving the effectiveness of the digitalization policy in the EU countries in accordance with individual convergence goals. The main added value of the paper is related to the presented research procedure, which can be used in analyses of digital technologies development also for other countries. The results provide valuable insights into evaluating the digital technologies in European countries. [ABSTRACT FROM AUTHOR]

Research background: The role of human capital in modern economy development is as important as that of material growth factors. According to the three-sector model theory, economic growth is associated with the process of labour force leaving the primary sector. The research issue addressed in this paper was the human capital level estimation in European NUTS 2 regions and the relationship between the human capital level and sectoral structure of the economy. Purpose of the article: The article aimed to verify the hypotheses of absolute and conditional human capital convergence in European NUTS 2 regions. The analysis covered the 2005-2020 period for European NUTS 2 regions and two subgroups: the CEE regions and the Western European regions. Methods: A composite indicator approach was adopted to measure human capital levels in NUTS 2 regions. In order to verify the absolute and conditional b-convergence hypotheses, dynamic panel data models were estimated. The Blundell and Bond system-GMM estimator with parameter standard errors robust to heteroscedasticity was used. Findings & value added: The study positively verified the hypotheses of absolute and conditional convergence in each group of regions. Percentages of employees in sectors proved to be the steady-state determinants. The time needed to reduce differences occurring in human capital levels by half (a half-life) was about 11 times greater for the CEE regions than for the Western European ones. The value added of the article lies in proving the relationship between the sectoral structure of employees and the pace of human capital convergence in European NUTS 2 regions. [ABSTRACT FROM AUTHOR]

Research background: It is not straightforward to identify the role of institutions for the economic growth. The possible unknown or uncertain areas refer to nonlinearities, time stability, transmission channels, and institutional complementarities. The research problem tackled in this paper is the analysis of the time stability of the relationship between institutions and economic growth and real economic convergence. Purpose of the article: The article aims to verify whether the impact of the institutional environment on GDP dynamics was stable over time or diffed in various subperiods. The analysis covers the EU28 countries and the 1995-2019 period. Methods: We use regression equations with time dummies and interactions to assess the stability of the impact of institutions on economic growth. The analysis is based on the partially overlapping observations. The models are estimated with the use of Blundell and Bond's GMM system estimator. The results are then averaged with the Bayesian Model Averaging (BMA) approach. Structural breaks are identified on the basis of the Hidden Markov Models (HMM). Findings & value added: The value added of the study is threefold. First, we use the HMM approach to find structural breaks. Second, the BMA method is applied to assess the robustness of the outcomes. Third, we show the potential of HMM in foresighting. The results of regression estimates indicate that good institution reflected in the greater scope of economic freedom and better governance lead to the higher economic growth of the EU countries. However, the impact of institutions on economic growth was not stable over time. [ABSTRACT FROM AUTHOR]

Research background: We assume that the dynamics of spatial wage inequality can be caused by both shifts in the sectoral structures of regional economies and changes in inter-sectoral and intra-sectoral (inter-regional) wage inequality. Purpose of the article: The paper is aimed at analysis of the sectoral factors influenced the spatial wage inequality in Russia in 2005-2014. Methods: The employment-weighted Gini coefficient was applied for assessment of spatial wage inequality; the modified Lerman-Yitzhaki technique allowed to decompose it by main economic activities and their determinants; the mixed methods of factor analysis was used to evaluate the contribution of sectoral determinants to regional wage convergence in Russia. Findings & Value added: We found a weak and inconsistent convergence of Russian regions in average wage over the period under review and explained it by the opposing forces in the main economic activities. The spatial convergence was basically created by mining, manufacturing, agriculture, construction, and transport and communications activities, while wholesale and retail trade, financial intermediation and real estate operations counteracted it. The convergence was mainly facilitated by a reduction in inter-sectoral differences in wages as well as by rapprochement of the employment structures in some economic activities of Russian regions. In the meanwhile, the migration of labor force from lower wage to higher wage activities negatively affected the smoothing regional differences. Ultimately, intra-sectoral wage inequality and wages correlation in various activities rather preserved inequality. The results are applicable in the management of spatial inequality both at the regional and national levels. [ABSTRACT FROM AUTHOR]

The study examines the concept of stochastic convergence in the EU28 countries over the 1994-2013 period. The convergence of individual countries' GDP per capita towards the EU28 average per capita income level and the pairwise convergence between the GDP of individual countries are both analyzed. Additionally, we introduce our own concept of conditional stochastic convergence which is based on adjusted GDP per capita series in order to account for the impact of other growth factors on GDP. The analysis is based on time series techniques. To assess stationarity, ADF tests are used. The study shows that the process of stochastic convergence in the EU countries is not as widespread as the cross-sectional studies on β or σ convergence indicate. Even if we extend the analysis to examine conditional stochastic convergence, the number of converging economies or pairs of countries rises, but not as much as it could be expected from the cross-sectional studies. [ABSTRACT FROM AUTHOR]

Research background: We assume that the dynamics of spatial wage inequality can be caused by both shifts in the sectoral structures of regional economies and changes in inter-sectoral and intra-sectoral (inter-regional) wage inequality. Purpose of the article: The paper is aimed at analysis of the sectoral factors influenced the spatial wage inequality in Russia in 2005-2014. Methods: The employment-weighted Gini coefficient was applied for assessment of spatial wage inequality; the modified Lerman-Yitzhaki technique allowed to decompose it by main economic activities and their determinants; the mixed methods of factor analysis was used to evaluate the contribution of sectoral determinants to regional wage convergence in Russia. Findings & Value added: We found a weak and inconsistent convergence of Russian regions in average wage over the period under review and explained it by the opposing forces in the main economic activities. The spatial convergence was basically created by mining, manufacturing, agriculture, construction, and transport and communications activities, while wholesale and retail trade, financial intermediation and real estate operations counteracted it. The convergence was mainly facilitated by a reduction in inter-sectoral differences in wages as well as by rapprochement of the employment structures in some economic activities of Russian regions. In the meanwhile, the migration of labor force from lower wage to higher wage activities negatively affected the smoothing regional differences. Ultimately, intra-sectoral wage inequality and wages correlation in various activities rather preserved inequality. The results are applicable in the management of spatial inequality both at the regional and national levels.

Research background: Information infrastructure is a very important pillar within a knowledge-based economy. The widespread use of information and communication technologies facilitates effective communication, dissemination and processing of information and knowledge. It also creates new opportunities for the effective use of knowledge and information in building competitive advantage. Information infrastructure is also a significant determinant in the development of territorial units, and therefore it affects the regional dimension of building the knowledge-based economy in Poland. Purpose of the article: The purpose of the study was to evaluate regional differentiation of the level of information infrastructure in Poland, and changes which occurred in this respect between 2010 and 2015. An attempt was made to provide an answer to the following question: Are regional differences in the level of information infrastructure in Poland increasing or decreasing, i.e. is a regional divergence or a regional convergence process taking place in this respect?. Methods: Taxonomic methods were used, including linear ordering based on a synthetic variable and a method of grouping linearly-ordered objects. Findings & Value added: The regional differentiation of the level of information infrastructure in Poland has slightly decreased, which means, that a slow convergence process has taken place in this respect. This fact is confirmed by the value of the variation coefficient, which fell from a level of 17.6% in 2010 to a level of 14.4% in 2015. Convergence processes were observed in twelve provinces. In the case of seven of them, they had the nature of a catching-up effect, and in the case of the remaining five -- a lagging-behind effect. Divergence processes were observed in four provinces. The Dolnośląskie and Mazowieckie Provinces distanced themselves from other areas of the country. In the Małopolskie and Opolskie Provinces a marginalisation effect was observed. [ABSTRACT FROM AUTHOR]