State Aid Impact on Central and Eastern Europe Economies

State aid is a fairly common phenomenon in the European Union, and, in the context of the COVID-19 pandemic, the number of companies receiving state aid has even increased. However, scientific research confirms that, depending on the macroeconomic, political and social situation as well as on industry specifics, state aid can have a dual effect -positive or negative. To date, there is no clear answer to the question of what impact and under which conditions state aid has on national economies in the long run. This article contributes to filling a gap in the literature because to date researchers have focused on the cases of large, heavily populated European Union countries, but the research into the impact of state aid on the Central and Eastern EU economies, where the level of state aid as percentage of GDP is higher than the EU average, is still scarce. In addition, the mixed results obtained in previous studies caused confusion over the effects of state aid and its relevance for economic development. In our research, we applied correlation analysis, Granger causality test, ARDL, PTR models and evaluation of multipliers for the analysis of the panel data set representing 11 Central and Eastern EU countries over a 20-year period (from 2000 to 2019). We found that state aid does not promote economic development in most Central and Eastern EU countries under certain conditions in the long term. This paper contributes to a deeper understanding of the state aid-economic development relationship at the national level in the Central and Eastern Europe and has implications for policy makers.

Smart economic development patterns in Europe: interaction with competitiveness

Purpose: This paper aims to investigate the smart economic development (SED) patterns in Europe in relation to competitiveness. Motivational focus corresponds to global events: the fourth industrial revolution, transition to a low-carbon economy, economic shocks (such as the 2008 financial crisis, Brexit or the coronavirus pandemic), which requires rethinking development policies, targeting competitiveness increase and reducing imbalances in economic development. Design/methodology/approach: The analysis includes self-organising neural networks cluster analysis and correlations, comparative analysis of SED indicators structure and cumulative index estimation with World Economic Forum (WEF) global competitiveness index. The panel data set of 19 years from 2000 to 2018 for 30 European countries. Findings: Overall, cross-country examination suggests that European countries of higher competitiveness illustrate higher estimates in SED. The key determinants are juridical fairness, social responsibility, competence building, intelligence and welfare employment to develop smart patterns for reaching higher competitiveness. Research limitations/implications: The limitations relate to the particular sample of European countries and gathering statistical data and a methodology of the SED index calculation. In addition, the paper contains a macroeconomic environment focus on competitiveness estimation. Further research may be improved with micro and mezzo environment incorporation at a cross-country analysis level. Practical implications: By linking well-known terms of competitiveness and economic development with a concept of smartness, new approaches to policymaking emerged. The methodology presented in this paper has implications for territorial cohesion policies, competitiveness and branching strategies. The combination of SED sub-indexes and WEF GCI might aid a more accurate ex ante measurement. Social implications: The findings are essential for fostering a smart approach in economic development for long-term competitiveness. Originality/value: This paper provides original empirical evidence about the relationship between SED and competitiveness and adds new knowledge that smartness becomes a way for building countries' competitiveness by identified two profiles of SED patterns by development stages, namely, integrated to economic development and institutional-based which is divided to focus and balanced. © 2021, Emerald Publishing Limited.

Automated System and Machine Learning Application in Economic Activity Monitoring and Nowcasting

The amount of data is growing at an extraordinary rate each year. Nowadays, data is used in various fields. One of these areas is economics, which is significantly linked to data analysis. Policymakers, financial institutions, investors, businesses, and households make economic decisions in real-time. These decisions need to be taken even faster in various economic shocks, such as the financial crisis, COVID-19, or war. For this reason, it is important to have data in as frequent a range as possible, as only such data will reliably assess the economic situation. Therefore, automated systems are required to collect, transform, analyse, visualise, perform other operations, and interpret the results. This paper presents the concept of economic activity, classical and alternative indicators describing the economic activity, and describes the automated economic activity monitoring system. Due to the different economic structures and the different availability of data in different countries, these systems are not universal and can only be adapted to specific countries. The developed automated system uses working intelligence methods to predict the future values of indicators, perform clustering, classification of observations, or other tasks. The application’s developed user interface allows users to use different data sources, analyses, visualisations, or results of machine learning methods without any programming knowledge. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

The impact of economic freedom on economic and environmental performance: evidence from european countries

The EU Green Deal and its impact on economic transformation provoked a slightly forgotten free market vs. market regulation discussion, but in the light of a new context—economic and environmental performance development. The economic shock caused by COVID-19, which transformed economies and societies, intensified this discussion. This article analyses the impact of economic freedom on economic performance and environmental performance in European countries. The article contributes to a gap in the literature, because, to date, research has examined the effects of economic freedom, or some of its components, on economic or environmental measures in groups of nations with a lacking sustainable development context. In addition, the mixed results obtained led to confusion in perceptions and knowledge about the influence and usefulness of economic freedom for economic and environmental performance. We also found mixed results regarding the influence of economic freedom on economic and environmental performance, but the introduction of a new concept—the optimal level of economic freedom—organized the different results into a coherent logical sequence. The paper provides original empirical evidence and specifies the targets of structural reforms. The results are thus useful for policymakers to develop more appropriate and efficient economic freedom. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.