The recent outbreak of the coronavirus pandemic has made a significant impact on the global financial markets. The aim of this paper is to assess the short-term reaction of the Visegrad countries’ financial markets to the COVID-19 pandemic. The Visegrad Group is a political alliance of four Central European countries, namely Czechia, Hungary, Poland, and Slovakia. The financial assessment is based on the EUR/CZK, EUR/HUF, and EUR/PLN exchange rates and the major blue-chip stock market indices, that is Prague PX, Budapest BUX, Warsaw WIG20, and Bratislava SAX. It is evident that the ongoing pandemic has changed the expectations of the financial market participants about the future value of exchange rates in the Visegrad countries. This study indicates that, as a consequence of COVID-19, higher probability has been attached to the large depreciation of the Czech koruna (CZK), the Hungarian forint (HUF), and the Polish zloty (PLN) than to their large appreciation. Moreover, based on the TGARCH model, the positive and significant correlation between the number of reported COVID-19 cases and the exchange rates has been confirmed, implying that the ongoing pandemic has resulted in the depreciation of the Visegrad currencies. Additionally, the result of the TGARCH model reveals that there is a significant and negative link between the Visegrad stock market indices and the COVID-19 spread.

The question of the sources of agricultural competitiveness is widely discussed on the farm and sectoral levels in the European Union. This paper assesses the competitiveness of the plant production using the combination of trade measures and strategic management measures in the selected European countries related to the Czech Republic. Thus, the paper evaluates and identifies the sources of competitiveness of plant production. In the case of Belgium and the Netherlands, labour and capital factors have a significant influence on production; in the case of the new member states, these factors are less important, and, conversely, market competitiveness factors are more crucial. The continuous convergence process between Belgium and the Netherlands is illustrated. The divergence between the Netherlands and the rest of the countries is also visible. There is a stable connection between the Czech Republic and Austria, France, and Slovakia. It can be mentioned that there is no statistically significant difference in the comparative advantage between 2005 and 2019, except in the case of France. Analysing sources of competitiveness among the countries of interest is a possible tool for the future direction of trade policies.

The study aims to explore the sources of competitiveness of dairy producers before and after the abolition of milk quotas in selected EU member states. The investigation is based on the stochastic frontier modelling of an input distance function in the specification of the four-error-component model. The model is estimated with a multistep procedure employing the generalized method of moments estimator, addressing the potential endogeneity of netputs, and panel data gained from the FADN database. The results revealed that total factor productivity experienced an increasing trend in the majority of the analysed countries. Since the main driver of productivity growth was found to be the scale effect, our findings support the hypothesis that abolishing milk quotas has a positive effect.

The paper, based on RCA, LFI and GL indices, and logistic regression analysis, allowed us to track the dynamics of the comparative advantage/disadvantage of the Czech Republic in individual commodity aggregates in relation to individual EU partners, and to comprehend the role of the main production factors. The only production factor with a statistically significant effect is capital. Trade with countries richly endowed with agricultural land and capital, in most cases, appeared not favorable for the Czech Republic in terms of having a comparative advantage over them, if measured with LFI index. The values of the GL index disclosed that trade with these countries is mostly of an inter-industry character. The analysis revealed the following top-3 mostly competitive Czech aggregates: S3-08 (animal feed stuff), S3-06 (sugar and sugar preparations), along with S3-04 (cereals and cereal preparations). Some aggregates appeared to not have any comparative advantage: S3-01 (meat, meat preparations), S3-05 (vegetables and fruits), and S3-41 (animal oils and fats). Speaking of developmental trends, from 2000 to 2019 the Czech Republic has managed to improve its position in agri-food trade within the EU-27 by 43.81% if measured with LFI, and by 51.63% if measured with RCA. These positive changes also appeared to be statistically significant.

Objective: This study aims to analyse the relationship between entrepreneurship and economic development. Quantified through the gross domestic product (GDP) per capita, across selected developed and developing countries. The research seeks to clarify how variations in entrepreneurial activity, as measured by the Global Entrepreneurship Index (GEI), relate to GDP per capita, thereby contributing to the broader understanding of the economic impacts of entrepreneurship. Research Design & Methods: This study adopted a quantitative approach, employing a cross-sectional ordinary least squares (OLS) model to explore the relationship between entrepreneurship and GDP per capita. Spanning the 2015-2019 period, our analysis incorporated data from 98 countries. Recognising the potential endogeneity concerns associated with specific independent variables, we implemented the instrumental variables (IV) approach, employing the two-stage least squares (2SLS) method to mitigate this potential bias. Findings: Our findings suggest that differences in GDP per capita between countries are significantly associated with variations in entrepreneurship. This highlights the importance of entrepreneurship as a driving force for GDP per capita. According to the 2SLS model, we found a positive relationship between the global entrepreneurship index (GEI) and GDP per capita. On average, a one-percent increase in GEI is associated with a 3.04% increase in GDP per capita. Implications & Recommendations: This study underscores the significant potential of entrepreneurship to drive economic development across diverse nations, regardless of their development stage. The findings demonstrate a positive and statistically significant association between higher levels of GEI and increased economic development. Therefore, policymakers have the potential to create an environment conducive to both entrepreneurship and sustainable economic development by implementing supportive policies and investing in key areas. Contribution & Value Added: This study provides valuable insights into the relationship between entrepreneurship and economic development. It highlights the importance of creating an enabling environment supporting entrepreneurship through infrastructure, education, market development, and innovation investment. Further research is needed to explore the nuances of this relationship and develop effective policies to promote sustainable and competitive economic development.