The main aim of this research is to analyze the relationship between income inequality and inflation in 13 European countries for the period 2000 to 2009 using panel data methodology. The GINI coefficient has been used to measure the income inequality while the inflation rate, the growth rate, the employment level and the openness of the economies have been used as independent variables. The results support the hypothesis that inflation has a positive significant effect on income inequality.

This paper examines the use of GARCH-type models for modeling volatility of stock markets returns for four European emerging countries and Turkey. We use daily data from Bulgaria (SOFIX), Czech Republic (PX), Poland (WIG), Hungary (BUX) and Turkey (XU100) which are considered as emerging markets in finance. We find that GARCH, GJR-GARCH and EGARCH effects are apparent for returns of PX and BUX, WIG and XU whereas for SOFIX there is no significant GARCH effect. For both markets, we conclude that volatility shocks are quite persistent and the impact of old news on volatility is significant. Future research should examine the performance of multivariate time series models while using daily returns of international emerging markets.

The aim of this paper is to examine different GARCH models with three different distributions in order to compare their forecasting power in terms of volatility existing in the returns of the Czech Stock Market and more specific in the PX index, for the period 08.01.2001-20.07.2012. We have employed GARCH, GJR-GARCH and EGARCH models against normal, student-t and generalized error distributions. Then, we have forecasted stock market volatility for the Czech Republic by its returns using the same models, GARCH, GJR-GARCH and EGARCH comparing their forecasting performance. The results show that return volatility can be characterized by significant persistence and asymmetric effects. We have estimated the corresponding variances for all models for the full sample period using static forecasts. After comparing the forecasting performance of all nine models it was found that the EGARCH model has the best forecasting performance compared to others.

Purpose: The goal of this paper is to explore the trend of FDIs in the Czech Republic and its changes in recent years using the gravity model. Apart from traditional variables used in FDI models we also introduce IFRS in national accounting rules. Design/Methodology/Approach: We use open-source data from the World Bank and FDI data from the Czech national bank, to analyse a panel data of bilateral FDI for 19 EU countries over the period 2008-2017 by PPML specification. Findings:We have observed significant effect of positive impact on broader introduction of IFRS in 2010 in terms of country imports and exports. We observed lower significance of IFRS dummy in the gravity model, where dependent variable is the sum of FDI inflow and FDI outflow it is not significant in the models which dependent variables are FDI inward and FDI outward for FDIs. Practical Implications: In general, FDIs increased productivity in the Czech Republic, especially in 1990s. We assess the effect and possible contribution of traditional variables like size, GDP, border and distance to Czech FDIs. Originality/Value: We find that the positive effect of IFRS exists at 10 percent significance for FDIs. Nevertheless we claim that this effect is mixed with other institutional issues, namely institutional isomorphism. Further tests will be needed after the forthcoming change of the Czech accounting act, which is approaching after 2020.

The impact of the COVID-19 pandemic has been detrimental toall countries, despite the continuous efforts of governments on all continents to attempt to mitigate its damaging effects. All economic and social indicators have worsened. This study explores the impact of COVID-19 on international trade among the Visegrad Four (V4) countries. We employ data from Eurostat and FRED to explore this influence, using the monthly import and export data for the 2010 M1–2021 M4period. We estimate the trade model for each member country of the V4, exploring their trade relations with other V4 members. We employ a shift dummy and impulse dummy to show the effect of country lockdowns initiating possible structural change. After exploration, we found that the COVID-19 impact was evident in all countries, but not with the same strength. Looking outside the V4 group, we can also see that there are strong trade relations with Germany, which is the strongest European economy. For further exploration, we suggest investigating these outside links to complete the picture.