Purpose: The main aim of this article is to search for long-term correlations between the level of economic growth and the level of export and import with cointegration analysis. To this end, the authors used the statistical data of the V4 countries which, since the 1990s, have been implementing market economy elements to different degrees. Approach/Methodology/Design: Econometric methods were used, including stationariness testing using ADF and KPSS tests and Engle-Granger cointegration test. Findings: The results obtained confirm that only in the case of Poland and Hungary there were two-way long-term interdependencies. For Poland, it was a pair of variables (GNP and export value), for Hungary (GNP and import value). No long-term correlation between economic growth and the value of foreign trade could be confirmed for Slovakia and the Czech Republic. Practical Implications: The study of interdependence using statistical methods is an important element in testing economic theories in the field of economic growth research in the countries of the former communist bloc. It is also an important stage in the search for economic growth generators. Originality/Value: Given the importance of trade, it is necessary to study the interaction of variables, check whether exports and imports had an impact on the level of economic growth and whether economic growth determined the increase in foreign trade turnover. The results obtained are the basis for the construction of a vector-autoregressive models (VAR).

Purpose:The article aimed to determine the general relationships between economic growth and development and selected innovativeness indicators in two countries belonging to the leaders of innovativeness in comparison with two countries of Central and Eastern Europe representing moderate innovators. Design/Methodology/Approach: Cluster analysis (agglomeration method), elements of descriptive statistics, correlation calculus, and the ADF test were used to study the stationarity of the variables initially. Findings: The results have shown that the analyzed innovativeness indicators have fluctuated to varying degrees, although in many cases, Poland and Hungary demonstrated high rates of growth, which could suggest a catching-up effect. Although the correlation coefficients between the levels of economic growth and development and the analyzed innovativeness variables were in many cases significant (usually positive), stationarity tests showed that the variables are in the vast majority non-stationary, which is a reason for further research when trying to build an econometric model. Practical Implications: A general analysis of the data indicated that the following stages of the study would require an expansion to include a cointegration account and determine the interrelationship of variables in both the short and long term, using autoregressive models. Originality/Value: Preliminary analysis of economic growth factors using descriptive statistics and correlation coefficients for selected countries (Sweden, the Netherlands, Poland, Hungary) based on available source data from OECD.