Rising political and economic uncertainty over the world affects all participants on different markets, including stock markets. Recent research has shown that these effects are significant and should not be ignored. This paper estimates the spillover effects of shocks in the economic policy uncertainty (EPU) index and stock market returns and risks for selected Central and Eastern European markets (Bulgaria, Czech Republic, Estonia, Hungary, Lithuania, Poland, Croatia, Slovakia and Slovenia). Based on rolling estimations of the vector autoregression (VAR) model and the Spillover Indices, detailed insights are obtained on the sources of shock spillovers between the variables in the system. Recommendations are given based on the results both for policymakers and international investors. The contribution of the paper consists of the dynamic estimation approach, alongside allowing for the feedback relationship between the variables of interest, as well as examining the mentioned spillovers for the first time for majority of the observed countries.

Debate on tourism-led growth and growth-led tourism is still ongoing today, with much research done for developed countries and those which are popular tourist destinations over the world. Surprisingly, the research is scarce for the Central and Eastern European (CEE) and South and Eastern European (SEE) countries. The contribution of this research is examining the dynamic relationship between spillovers of tourism growth and economic growth for CEE and SEE countries for the first time in the literature. The methodology used in the study (spillover indices) allows for estimating the dynamic relationship throughout rolling indices. Based upon monthly data (with different time spans depending upon availability of data, from January 2000 to January 2003 until December 2017, i.e., October 2018), the following countries were in focus: Bulgaria, Croatia, Czech Republic, Hungary, Poland, Slovenia and Slovakia. Results from dynamic rolling spillover indices indicate mixed results for all of the countries throughout the sample. Dynamic results enable policymakers from individual countries to focus on specifics of their economies to develop even better policies in order to achieve best possible results regarding the tourism growth and related economic growth.

Measuring the efficiency of research and development (R&D) expenditure and innovation policy has gained attention in recent years. This research examines the efficiency of 29 selected European countries for the period ranging from 2007 to 2017 in achieving and obtaining R&D goals. The methodology applied is the data envelopment analysis approach with the inclusion of the missing data approach. The contributions of this research include the following: dynamic analysis is conducted to track changes of (in)efficiencies over time; the decomposition of the efficiency is done by separating the main variables of interest into the private, higher education, and government sectors; and the robustness of the results is evaluated, which is often ignored in the literature. The results of the analysis are discussed with possible directions for inefficient countries. The rankings provided in the empirical part of the study confirm previous findings on disparities between the European countries with respect to innovation and the R&D sector.

Due to the development of financial markets, products, financial and mathematical models, portfolio selection today represents a comprehensive set of activities. Investors take into consideration many different factors, such as the market factors, return distribution characteristics and financial statements information. This research applies a Grey Relational Analysis (GRA) approach to evaluate the performance on a sample of stocks by taking those different factors into consideration. The results based upon a sample of 55 stocks for the trading year 2017 on the Croatian capital market show that using GRA approach in portfolio selection provides useful guidance for investors when making investment decisions, and better portfolio results in terms of risk and return are reachable compared to an equally weighted portfolio benchmark.