The paper deals with the problem of taxation and its potential impact on economic growth and presents some new empirical insights into this topic. The main aim of the paper is to verify an assumed nonlinear impact of corporate tax rates on economic growth. Based on the theory of public finance and taxation, we hypothesize that at relatively low tax rates it is possible that the impact of taxation on economic growth become slightly positive. On the other hand when the tax rates are higher a negative impact of taxation on economic growth could be expected. Despite the fact that the most of the existing studies find a negative linear relationship between these variables, we can also find strong support for a non-linear relationship from several theoretical models as well as some empirical studies. Based on panel data fixed-effects econometric models, we, as well, find empirical evidence for a non-linear relationship between nominal and effective corporate tax rates and economic growth. Our data consists of annual observations for the period 1999 to 2011 for EU Member States. Based on the results, we also estimated the optimal level of the corporate tax rate in terms of maximizing economic growth in the average of the EU countries.
Research and development activities within the region are often seen as a key driving force of innovation performance. This is further important for productivity growth and economic growth of the region. These issues are part of European Union strategy for regional development called Smart Specialization. Higher education institutions play important role in the support of innovation in the region via their own research activities, knowledge creation and dissemination and improvement of the human capital in the region. The main aim of our research is to test potential link between intensity of research & development as well as specialization of the region and labour productivity in the region. In our research we compared NUTS 2 regions in the Czech Republic and Slovakia based on the selected indicators related to research and development. We used factor analysis and regression analysis based on the cross-sectional data for all NUTS 2 regions in the EU. Our results strongly suggest that focus on research & development activities is positively correlated with higher labour productivity in the region. Higher number of scientific publications and patents is also positively linked to higher productivity in the region. The same seems to be true for higher share of tertiary educated inhabitants.
Background: Transfer of knowledge from academia to business is one of the crucial issues for creating innovation. Creation of university spin-offs could significantly improve this transfer. Objectives: The main scientific aim is to examine the differences between universities in European countries and identify factors affecting the probability of creating the university spin-off. The paper is also focused on the differences in the specialization and financial sources of universities. Methods/Approach: We compare selected indicators for higher education institutions in European countries and examine potential determinants affecting the probability of academic spin-off formation. With respect to the main aim, the logit and probit regression analyses have been used. Results: Our results show that the creation of spin-offs is typical on the one hand for highly specialized universities or on the other hand for universities with a wide variety of study programs. They should also have an optimum number of doctoral students and have mostly less funding from tuition fees. Conclusions: Several indicators appear to play an important role in the formation of university spin-off. These indicators are the level of specialization, the share of tuition fees in the University budget, and the share of Ph.D. and foreign students.
The paper is focused on the problem of corporate tax competition in EU as one of the current key issues for EU member states tax policies. The main objective is to empirically verify theoretical assumptions about corporate tax competition among EU member states. Based on the available empirical data we analyzed trends in effective and statutory tax rates and tested the theoretical assumption of possible spontaneous tax coordination. We found almost no support for spontaneous tax coordination for EU as a whole, but it appears to be more evident among neighbouring member states as well as in within the same regions. The differences in corporate tax rates between neighbour countries are mostly smaller and tend to shrink over the time. We have used panel data cointegration analysis to test for, and DOLS and FMOLS panel estimators to estimate, the long-run parameters. Finally panel vector error correction models (VECM) were used to examine short-run as well as long-run dependencies among the corporate tax policies of neighbouring EU countries. Based on our results we find evidence for relatively strong relationships between neighbouring EU member states in corporate tax rate setting.
Vladimir Hiadlovsky, Jan Hunady, Marta Orviska and Peter Pisar
Background: The intensity of innovation could often be crucial for further economic development of the regions. Science and technology are often seen as the key factor supporting innovation in the regions. Furthermore, we can assume that higher intensity of research activities could lead to better economic performance.
Objectives: Research aims to examine the link between the economic performance of the region and the intensity of science and technology activities, proxied by the share of employees in science and technology.
Methods/Approach: The analysis is based on panel data for NUTS2 regions of the European Union (EU) member states. We conducted correlation analysis, panel Granger causality tests and regression analysis.
Results: Our results suggest the existence of a significant positive correlation between GDP per capita and the share of employees in science and technology. Moreover, the regions with a higher intensity of science and technology activities are mostly characterized by relatively low unemployment rates.
Conclusions: Research activities are positive correlated with regional GDP and negatively correlated with unemployment. However, increasing the share of employment in science and technology beyond a certain turning point would not lead to any further positive effects on regional economic performance.