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Research background: The relationship between labour share and income inequality is a complex and multifaceted problem. Despite ongoing discussions among economists, there is still no consensus on the direction of the relationship between labour share and income inequality. Purpose of the article: The article aims to assess the impact of labour share on income inequality, which is measured in three ways: the Gini index of gross income, the Gini index of market incomes, and the Gini index of household disposable income. Methods: Dynamic panel data models were applied to estimate the relationship between Gini coefficients and socio-economic indicators. The study investigated 25 European Union countries over the 2011-2021 period. Findings & value added: Despite the long convergence process of the EU economies, there is still great diversity in the labour share, social inequalities, and the interplay between these factors. The added value of this research is the indication of labour share impact on three Gini measures covering a diverse income spectrum (from labour and capital). Based on the research findings, hypothesis 1, claiming that the more developed the national economy, the lower the share of employment income, favouring capital gains, is confirmed. Hypothesis 2 (as the share of income from work increases, the Gini coefficient of gross incomes decreases) must be rejected. There is no significant relationship between labour share and the studied Gini measures in 'old' EU countries. In 'new' EU members, there is a reverse relationship than assumed in hypothesis 2. The growth of the Gini coefficient was influenced by the rise in labour share, which can be attributed to the diversity in economic structures. [ABSTRACT FROM AUTHOR]

The labour market in Poland has undergone significant transformations over the past two decades. The observed changes have been influenced by various factors related to, among other things, the possibility of free movement of the population resulting from membership of EU structures, demographic changes, technological changes, and the automation and robotisation of production processes. Demographic change is becoming a significant challenge, highlighting the shortage of workers with different qualifications and competencies in the labour market in various sectors of the national economy. This paper aims to indicate to what extent Ukrainian citizens can fill the gaps in Poland's emerging labour market. To that end, a survey was conducted in the Qualtrics programme in May-June 2022 among Ukrainian citizens who arrived in Poland before 24th February 2022, i.e., before the outbreak of the war and who were registered in the Gremi Personal database. This particular company provides support connected to employment for Ukrainians. Due to the non-probabilistic sampling technique, the results cannot be generalised with regard to the entire population. To analyse the results, descriptive statistics were used to examine the population structure and determine the significance of the characteristics studied and the correlation between them. The research shows that labour shortages in Poland's labour market can be compensated to some extent by employing migrants from, for example, Ukraine. The commencement of the proper research was preceded by the preparation of a pilot study and the collection and analysis of statistical data related to the situation on the Polish labour market, taking into account the level and structure of employment and an indication of shortages in the labour market when the research was prepared, and the fact that complete statistical data ended in 2020, hence the decision to include this research period in the analyses. [ABSTRACT FROM AUTHOR]

10.3390/en15010340 26 Zinecker M., Doubravsky K., Balcerzak A.P., Pietrzak M.B., Dohnal M. The COVID-19 disease and policy response to mitigate the economic impact in the EU: An exploratory study based on qualitative trend analysis. Of particular importance seems to be the analysis of changes in the prices of electricity and primary fuels and the relationship between these markets and the renewable energy market. Bus. Econ. 2020; 19: 114-135 7 Dmytrów K., Bieszk-Stolorz B. Comparison of changes in the labour markets of post-communist countries with other EU member states. Q. J. Econ. Econ. [Extracted from the article]

The paper aims to improve the methodology of the Digital Economic and Society Index (DESI), the European Commission's newest index to assess the development of the digital economy. In particular, we investigate whether methodological changes to the structure of DESI improve its ability to capture the digital transformation of EU economies. Using the sensitivity-based analysis, we check whether the selection of weights of individual elements included in the DESI is optimal or should be improved. We also verify the importance of DESI in explaining changes in GDP per capita in EU economies. In the literature, we find that digital transformation has enabled the creation of new business models and maximized efficiency in traditional firms. Using DESI, we empirically test whether the gap between rich and poor countries in European Union can be closed or eliminated through rapid and intensive digital transformation. Our results show that the DESI -- when modified by eliminating the pillars on internet services and digital public services -- has the same explanatory power. Connectivity is the dimension with the largest impact on digital transformation in EU countries. We also find that DESI is a significant regressor to explain changes in GDP per capita in EU countries. [ABSTRACT FROM AUTHOR]

The Global Competitiveness Index (GCI) developed by the World Economic Forum (WEF) is used as a standard for measuring a country's competitiveness. However, in literature, the GCI has been accused of numerous methodological flaws. Consequently, in 2018, the WEF introduced significant methodological changes. This study aims to examine whether the methodological modifications in the GCI's structure increase its ability to capture the real competitiveness of economies. In addition, the study considers whether the selection of weights of individual elements included in the GCI is optimal or could be improved. By employing a sensitivity-based analysis, we find that the change in methodology resulted in fewer pillars of marginal importance. In the case of the GCI 2017, there were four pillars, whereas in that of the GCI 4.0, there were only two pillars: product market and labor market. Furthermore, we reveal that the WEF weights do not reflect the measured importance of the variables. In the optimization process, numerous variables (primarily opinion-based indicators) were insignificant in explaining the GCI variance and could be eliminated from the set of diagnostic variables without affecting the index's value. For instance, in the case of the GCI 4.0, 35 out of 103 variables could be eliminated. The new rankings obtained by weight optimization and reduction of the diagnostic variables demonstrated a strong positive correlation with the original rankings. This research contributes to the literature from both a theoretical perspective (indicating the most vital indicators in the GCI) and a practical standpoint (reducing the costs and time of obtaining redundant data). [ABSTRACT FROM AUTHOR]

Research background: The problem of digital deprivation is already known, but the COVID-19 pandemic has highlighted its negative consequences. A global change in the way of life, work and socialisation resulting from the epidemic has indicated that a basic level of digital integration is becoming necessary. During the lockdown, people were forced to use ICTs to adapt to a rapidly changing reality. Current experience with coronavirus pandemic shows that the transition to these extraordinary circumstances is not smooth. The inability to rapid conversion to the online world (due to a lack of skills or technical capabilities) significantly reduces professional mobility, hinders access to public services, and in the case of children, exposes them to the risk of remaining outside the remote education system. Purpose of the article: This research paper is addressing new issues of the impact of the COVID-19 pandemic on deepening and increasing the severity of e-exclusion. The goal of the paper is to indicate territorial areas in Poland which are particularly vulnerable to digital deprivation due to infrastructural deficiencies. Methods: Raster data regarding landform, combined with vector data regarding population density and type of buildings as well as the location of BTS stations are used in so-called modelling overland paths (GIS method) to indicate areas vulnerable to the infrastructural digital divide. Findings & Value added: The research showed that 4% of Poles remain out-side the Internet coverage, and additional ten percent of them are out of the reach of the Internet, allowing efficient remote work or learning. The research indicated that digital 'accessibility gap' is underestimated. E-exclusion has become a pressing issue and requires urgent system solutions, in case of future lockdowns. [ABSTRACT FROM AUTHOR]

Research background: Composite indicators are commonly used as an approximation tool to measure economic development, the standard of living, competitiveness, fairness, effectiveness, and many others being willingly implemented into many different research disciplines. However, it seems that in most cases, the variable weighting procedure is avoided or erroneous since, in most cases, the so-called 'weights by belief' are applied. As research show, it can be frequently observed that weights do not equal importance in composite indicators. As a result, biased rankings or grouping of objects are obtained. Purpose of the article: The primary purpose of this article is to optimise and improve the Human Development Index, which is the most commonly used composite indicator to rank countries in terms of their socio-economic development. The optimisation will be done by re-scaling the current weights, so they will express the real impact of every single component taken into consideration during HDI's calculation process. Methods: In order to achieve the purpose mentioned above, the sensitivity analysis tools (mainly the first-order sensitivity index) were used to determine the appropriate weights in the Human Development Index. In the HDI's resilience evaluation process, the Monte Carlo simulations and full-Bayesian Gaussian processes were applied. Based on the adjusted weights, a new ranking of countries was established and compiled with the initial ranking using, among others, Kendall tau correlation coefficient. Findings & Value added: Based on the data published by UNDP for 2017, it has been shown that the Human Development Index is built incorrectly by putting equal weights for all of its components. The weights proposed by the sensitivity analysis better reflect the actual contribution of individual factors to HDI variability. Re-scaled Human Development Index constructed based on proposed weights allow for better differentiation of countries due to their socio-economic development. [ABSTRACT FROM AUTHOR]

The energy transition is now treated in most countries as a necessary condition for their long-term development. The process of energy transformation assumes the simultaneous implementation of the Sustainable Development Goals, which are a major challenge for modern economies and introduce significant restrictions in their functioning. Our study aims to group EU member states according to their ability to achieve energy transition over time. The novelty of our approach is the assessment of energy transformation in the European Union through two aspects. The first one, "smart and efficient energy systems", assess the current, widely understood energy consumption in economy, and the second one, "macroeconomic heterogeneity", refers to the economic potential of a country. In our analysis, we included indicators from the 7th, 8th, 10th, 11th, and 12th Sustainable Development Goals. Using taxonomic methods, we created clusters of countries according to the emissivity of their economies and the socio-economic potential for the energy transition. The analysis results revealed that countries vary more due to their emissivity than economic potential. [ABSTRACT FROM AUTHOR]

Our paper aims to investigate the impact of COVID-19 on private sector companies in terms of sales, production, finance and employment. We check whether the country and industry in which companies operate, government financial support and loan access matter to the behaviour and performances of companies during the pandemic. We use a microdata set from a worldwide survey of more than 15,729 companies conducted between April and September 2020 by the World Bank. Logistic regression is used to assess which factors increase the likelihood of businesses suffering due to the COVID-19 pandemic. Our results show that COVID-19 negatively impacts the performance of companies in almost all countries analysed, but a stronger effect is observed among firms from developing countries. The pandemic is more harmful to firms providing services than those representing the manufacturing sector. Due to the pandemic, firms suffer mainly in sales and liquidity decrease rather than employment reduction. The increase in the number of temporary workers is an important factor that significantly reduces the probability of sales, exports or supply decline. The analysis results indicate policy tools supporting enterprises during the pandemic, such as increasing the flexibility of the labour market or directing aid to developing countries. [ABSTRACT FROM AUTHOR]

This article aims to improve one of the newest energy transition measures—the World Economic Forum WEF Energy Transition Index (ETI) and find its driving forces. This paper proposes a new approach to correct the ETI structure, i.e., sensitivity analysis, which allows assessing the accuracy of variable weights. Moreover, the novelty of the paper is the use the spatial error models to estimate determinants of the energy transition on different continents. The results show that ETI is unbalanced and includes many variables of marginal importance for the shape of the final ranking. The variables with the highest weights in ETI did not turn out to be its most important determinants, which means that they differentiate the analysed countries well; nonetheless, they do not have sufficient properties of approximating the values of the ETI components. The most important components of ETI (with the highest information load) belong to the CO2 emissions per capita, the innovative business environment, household electricity prices, or renewable capacity buildout. Moreover, we identified the clustering of both ETI and its two main pillars in Europe, which is not observed in America and Asia. The identified positive spatial effects showing that European countries need much deeper cooperation to reach a successful energy transition. [ABSTRACT FROM AUTHOR]