This article is aimed at identification of the shadow economy’s causal factors and indicators in 19 Eurozone member states over the period from 2005 to 2016. Application of the MIMIC model has allowed to identify the following causal factors of the shadow economy in the Eurozone: employment rate, gender wage gap and income inequalities (expressed as the GINI index). All of these causal factors of the shadow economy in the Eurozone are attributable to the group of labour market determinants, which proposes that a reasonably arranged labour market mechanism can substantially diminish the probability of the shadow economy emergence. On the other hand, it has been found that the level of the shadow economy determines a positive/negative degree of the public trust in the EU authorities. The novelty of the research lies in the disclosure of the main causal factors of the shadow economy in the geographical area that covers different countries with a single currency. The findings of this research may contribute to the development of the shadow economy reduction strategies in 19 Eurozone member states.
The trans-boundary area between the Europe Union and other countries is highly susceptible to changes in water quality and variations in the potential pollution load that could influence its eco-systems significantly. The Neris (Viliya) River is one of the biggest surface water bodies in Lithuania and Belarus with an ecologically important area protected by international legislation. The study was aimed at evaluating the impacts of integrated pollution on water quality of the Neris River taking into account different storm-water flows and ecological scenarios. For this purpose, qualitative and quantitative statistical evaluation was set up and calculation was done; different integrated pollution loads of the catchment area were estimated. The evaluation considered a decrease in river discharge due to changes in the regional storm-water flow and technological development that should lead to the growing covered surface and a reduction in the untreated storm-water flows. The obtained results indicated that, in the case of storm-water treatment, the total nitrate and phosphate concentrations will decrease, while in the cases of changes in combined suspended solid, the concentration of nutrients will decrease. Thus, a trans-boundary storm-water treatment plant of the Viliya River is required as it should eliminate pollution accumulation and restore its acceptable environmental status. A coordinated international project for the entire catchment of the Neris (Viliya) River based on the specifications and requirements of the EU Water Framework Directive (EU 2000) should be developed and implemented. Subsequently, ecological river-use policies should be established at the international level, which should offer considerable perspectives for the sustainable development of the area.
One consequence of intensive outdoor disinfection using chlorinated compounds is environmental pollution. It has been found that disinfectants are the most effective tool to avoid the spread of infections and viruses. Studies have shown that the use of chlorine-based disinfectants (sodium hypochlorite) leaves residual chlorine and other disinfection byproducts in the environment. They also have harmful effects on, inter alia, water quality, ecosystems, as well as exacerbating the corrosion of surfaces. To meet regulatory standards, monitoring of the presence of residual chlorine in the environment is vitally important. The aim of this study is to analyse the occurrence of residual chlorine in stormwater after outdoor disinfection using sodium hypochlorite and to investigate its interaction with different microelements as well their possible impacts. Stormwater samples collected at permanently disinfected locations were analysed via X-ray absorption spectroscopy. The concentrations of Cl and the following elements Na, Si, K, Ca, Cr, Fe, Ni, Cu, Zn were detected and their relationship with chlorine was determined using the Python programming language. The research presents Cl concentration values (%) that vary from 0.02 to 0.04. The results of the modelling revealed strong correlations between Cl and Fe (value 0.65) and Ca (value −0.61) and the occurrence of CaCl2 and FeCl3. The strong relationship between Cl and Fe explains the significant increase in surface corrosion after disinfection with chlorine-based substances.
Studies looking at the links between corruption and quality of life have begun to take place recently, as until now the quality of life has not traditionally been associated with political decisions. Corruption may be defined as the abuse of entrusted power for private gain, which in one way or another affects the quality of life and satisfaction of others. The aim is to bridge the gap between the nexus of corruption and the quality of life in the EU. EU countries were divided into groups of countries according to the year of accession and cover the years 2004-2017 period. The EU has been selected as a geographical region with the aim of uneven economic development of the countries and the lack of research in the region. The aim of the article is to determine the interdependencies between corruption and quality of life indicators in EU countries. Multivariate regression models revealed that the prevalence of corruption among individual groups of six countries had the highest impact on mortality rates, unambiguously showing how well countries are managing their health care systems, population density, birth rate and population aging, GDP per capita, economic situation, life expectancy, serving as an indicator of quality of life and the number of people with primary education. The results of empirical research allow to form insights that in order to reduce corruption it is necessary to focus on the following spheres reflecting the quality of life: education, health care system and general economic situation of the country. The article used the following methods: comparative and systematic literature analysis, multiple regression analysis.
The article is very topical and of high scientific value as it covers the problems of regional exclusion emphasized in the EU strategic documents. Regions suffer from social and economic exclusion, which, in turn, induces high unemployment and crime rates, and leads to the flourishing of smuggling. The aim of this article is to estimate the level of the shadow economy in the regions of Lithuania over the period 2012 to 2016. The topic is very relevant to such transition economies as Lithuania with huge separation between regions and large cities. Deep social problems in regions, lack of job places and absence of investment along with high emigration rate and intensive population's movement to the largest cities lead to the growth of crime rate and high scope of the shadow economy. Calculations performed under the MIMIC model have shown that the share of indirect taxes, average income, the cases of cigarette smuggling, population of women per 1000 men, the number of criminal offences, children in social risk families and the number of tourists are the main causes for the emergence and growth/decline of the shadow economy level. The novelty of the article lies in the calculations that reveal a significantly higher level of the shadow economy in the regions than at the country level. Therefore, it is recommended to make calculations at the regional level in order to select measures to more effectively fight with the "shadow". Identified reasons allow formulating the following recommendations for responsible authorities: increase efficiency in tax system, since current excise tax policy has a positive impact on the level of poverty, especially at regional level, deepening of social problems, which as a result contribute to the growth of shadow economy; encourage women occupancy and emancipation and attract funding from national and international projects, to promote equal rights in researched regions; increase the level of attractiveness and security level in cities, promote FDI to cities, and effectively use money from the EU Structural Funds.
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