Our paper examines the potential effect of different types of entrepreneurship (in particular, early-stage entrepreneurship, opportunity-driven entrepreneurship, and necessity-driven entrepreneurship) on economic growth at a national level and aims to identify whether the contribution of entrepreneurship to economic growth differs according to the stage of economic development of a country. Our empirical analysis is based on the panel data, which covers 17 years (2002–2018) and 22 European countries, classified into two groups. The results suggest that all three types of entrepreneurship have a greater impact on economic growth for the entire sample of European countries, and some types of entrepreneurship are more important than others. We find that opportunity-driven entrepreneurship and early-stage entrepreneurship would be key factors in stimulating economic growth across the sample of European countries. Our estimations also show that opportunity-driven entrepreneurship would have a greater impact in transition countries, while necessity-driven entrepreneurship would have a stronger influence in the innovation-driven countries. The results of our research could be of interest to policymakers, as it can help in identifying and implementing the most appropriate measures to eliminate the obstacles in the macroeconomic environment that entrepreneurs face, and measures to support innovative entrepreneurial activities.

Entrepreneurship plays a major role in national economies, being considered one of the main engines of economic growth, and an important contributor to creating new jobs and innovations. Identifying the main determinants of entrepreneurial activity is important for helping the decision makers in adopting adequate measures to support the creation and development of new businesses. The turbulent economic environment in recent years dominated by economic and financial crises, resulting in a reduction in economic growth but also in an increase in unemployment, has led decision makers to turn their attention again to the determinant factors of entrepreneurship. Starting from those stated above, through this paper we aim to investigate the impact of some macroeconomic, individual and business environment-related factors on the dynamics of entrepreneurial activity in 18 European Union (EU) countries for a period of 14 years (2002–2015). We use three regression models and we apply panel data fixed effect model approach. The results of our study highlight that inflation rate, foreign direct investments, access to finance and total tax rate are the main macroeconomic determinants of entrepreneurship. Also, we find that all individual business-related factors considered in the analysis have a significant impact on total entrepreneurship rate.

Purpose – the study has a dual purpose. First, to assess the impact of the most important determinants of financial performance, which have been measured through four generations of indicators. In addition, the study provides the first quantification of interdependencies between different financial performance measures: profit margin (PM), profit growth rate (PGR), return on assets (ROA), return on equity (ROE), and economic value added (EVA). Research methodology – the primary data was collected from the AMADEUS database. Empirical research was conducted on a relatively homogeneous sample from the automotive industry, using the panel data method for the period 2010–2019. Two models were tested. The first model highlights the relationships between performance measures and selected determinants. The second model highlights the relationship between the different performance measures and the determinants used in the first model. Findings – the determinants analysed have different influences on the selected performance measures. For example, in the first model, the results statistically significant indicated the following. The current ratio has a positive influence on ROA, but a negative one on ROE and EVA. Gearing has a negative influence on PM and ROA, but a positive one on EVA. The growth rate of sales has a positive influence on PM, but a negative one on ROA and EVA. The size of the company has a positive influence on three performance measures (PM, ROA, and EVA). Regarding the relationships between the different performance measures (second model), the research indicates that EVA is negatively influenced by PGR and ROA. In this model, the determinants analysed maintain their meaning and intensity of influences. Research limitations – the article has several limitations. The representativeness of the results is valuable only at the level of the researched industry. In addition, it should be noted that the analyses are focused only on financial performance, assessed by accounting measures. The authors are considering conducting comparative analyses at the level of fields/branches of activity to capture not only the impact of determinants on financial performance but also to assess organizational resilience. Practical implications – The research provides clues to managers and financial decision-makers to increase the financial performance of the companies they lead. Originality/value – the originality of the study lies in the presented methodological approach. Unlike previous research, which usually evaluated performance on only one indicator, this paper aims to assess the impact of the most important determinants on five performance measures. In addition, the analysis of the interdependencies between the different performance measures is another novelty of this research.

This paper analyses the main economic factors that are influencing the competitiveness of Central and Eastern European (C.E.E.) countries. The research was carried out on a sample of ten countries (Bulgaria, Czech Republic, Estonia, Hungary, Lithuania, Latvia, Poland, Romania, Slovenia and Slovakia), over the period 2004–2016. These countries were grouped by their stage of economic development, respectively: efficiency driven economies, in transition between efficiency and innovation and innovation driven economies. An econometric analysis on panel data was used, considering as a dependent variable the competitiveness of a country, quantified by the Global Competitiveness Index. As independent variables, we took into account a set of seven macroeconomic and business environment indicators which could have an impact on a country’s competitiveness. The results obtained show important differences between countries, but also some resemblance. Although all the considered countries are emerging ones, the factors that have a significant influence on the competitiveness differ significantly. Thereby, if for efficiency-driven countries, G.D.P., inflation rate, trade, labour productivity and costs are important determinants of competitiveness, for innovation-driven countries the determinants of competitiveness are: G.D.P., inflation rate, tax rate, F.D.I., trade and costs. As regards the C.E.E. countries in transition only G.D.P., inflation rate and labour productivity are determinants of competitiveness.

Research and innovation play a key role in generating smart and sustainable economic growth. By producing new knowledge, the research contributes to the development of new and innovative products, processes, and services, which in turn lead to increased productivity, industrial competitiveness, and, ultimately, the prosperity of the community as a whole. However, all research, development and innovation activities depend on the financial resources made available, as specific financing accelerates the production and dissemination of the best ideas and practices, as well as their role in meeting the challenges our society deals with nowadays. Our study aims to identify the determining factors for the researcher’s participation and success rates in research funding competitions. The goal of the research is to understand how variables such as age, gender, main field, affiliation, and scientific rank can affect the access to funding opportunities available for research and innovation. The study relies on a questionnaire-based survey conducted with 243 early-career and senior researchers from many state universities across Romania. For an in-depth analysis of the factors that influence the success rate in research competitions, in the present approach, we used both graphical and econometric methods. A binary logistic regression modelling was performed in order to explain the relationships between variables. Among other considerations, our findings revealed that in all main research fields, scientific rank and gender are important features for raising the participation and success rate in research funding competitions.

The short- and long-term effects of public debt on economic growth in EU countries is analyzed in this paper, using data that covers a period of 25 years (1995–2019). For public debt, we used a proxy general government gross debt (as a percentage of GDP), while for economic growth, we used the real GDP per capita growth rate. In addition, our models include a set of control variables to highlight the impact of other determinants on economic growth. We utilized several econometric methodologies related to ARDL (autoregressive distributed lag models), such as the pooled mean group (PMG), the mean group (MG), and the dynamic fixed effects (DFE) models. The results of the study show that in both the short and long term, an increase in public debt is negatively and significantly associated with economic growth. Specifically, in both the short- and long-term analyses, the estimated coefficients of public debt were statistically significant and negative, while the magnitude of the negative impact on economic growth differed. In view of these findings, we consider both the rigorous monitoring of the level of public debt and the control of public allocation to support economic growth to be of major importance.