Suchergebnisse

Environmental health is among the priority areas of public health, and the current professional communities are intensively engaged with it. The main objective of the study is to quantify regional disparities of preventable mortality in Slovakia and to study the extent of the influence of selected environmental factors on changes in the development of its values. A cross-sectional linear regression model is used to quantify effects of environmental factors on the preventable mortality. Also, cluster analysis is used to identify regions with similar levels of air pollution. Environmental factors were selected based on the study of the World Health Organization. From the point of view of the influence of environmental factors on preventable mortality in the case of men, statistically significant connection to sewerage, SO2 production, and production of particulate matter was demonstrated. In the case of women, equally important factors showed connection to sewerage and SO2. The results of this study point to significant regional disparities in preventable mortality and a different degree of impact of environmental factors. Preventable mortality is above the Slovak average in most of the least-developed districts. Even in this group, there are significant differences. ; ATTRACTIVE DANUBE "Improving Capacities for Enhancing Territorial Attractiveness of the Danube Region" [DTP40]; European Union Funds (ERDF, IPA)

Abstract
In recent years, gender inequality has been considered the main characteristic of insufficient gross domestic product (GDP) growth. This paper discusses the evolution of GDP per capita in 21 countries of the European Union between 2015 and 2019. Using panel regression, we investigated the change in GDP per capita through five variables. The analysis results showed that female employment rate is the most statistically significant and positive variable on GDP. Gender Equality Index also appeared to be an essential variable. The second part of our analysis consisted of an explanatory spatial data analysis of all variables to examine the spatial dimension of the variables. To explain spatial econometrics, we used selected methods, namely, choropleth maps, Local Indicators of Spatial Association (LISA) cluster analysis, Moran's scatter plots, and Moran's I statistics. Based on the visualization of choropleth maps, GDP per capita did not change during the observed period, even though the values of the explanatory variables changed. For GDP per capita, the same applies in the case of LISA cluster analysis. At the end of the monitored period, the countries were included in the same cluster as at the beginning. When plotting Moran's scatter plot, it was found that GDP per capita did not tend to have positive or negative spatial autocorrelation or no spatial autocorrelation. Moran's I statistic showed that GDP per capita values were not randomly dispersed; they were grouped according to a specific formula into clusters.

AbstractᅟWe study the transmission channels for rises in the minimum wage using a unique firm-level dataset from eight Central and Eastern European countries. Representative samples of firms in each country were asked to evaluate the relevance of a wide range of adjustment channels following specific instances of rises in the minimum wage during the recent post-crisis period. The paper adds to the rest of literature by presenting the reactions of firms as a combination of strategies and evaluates the relative importance of those strategies. Our findings suggest that the most popular adjustment channels are cuts in non-labour costs, rises in product prices, and improvements in productivity. Cuts in employment are less popular and occur mostly through reduced hiring rather than direct layoffs. Our study also provides evidence of potential spillover effects that rises in the minimum wage can have on firms without minimum wage workers.JEL ClassificationsD22, E23, J31