## 4 Results and Discussions
The case of Lithuania might be explained by the fact that the birth rate in 2009 had its lowest value for all the analysed years and the death rate was very high (more than 20%) because of the manifestation of the financial crisis. _The birth rate_ for the EU enterprises varied between a maximum of 24.88% (in Lithuania, in 2012) and a minimum of 3.04% (in Malta, in 2016). On the other hand, _death rate_ reached the highest value of 29.05% in Lithuania in the context of the recent financial crisis (in 2008), and the lowest value in Ireland (0.96% in 2016). Lithuania also registered the highest business churn rate, while the smallest value of this indicator was in Cyprus. As regards the control variables, the highest values of basic education received by the population are registered in Finland (2012-2013) and the lowest in Spain (in 2010). The largest population was registered in Germany (in 2019) and the smallest in Malta (2008). The resource endowment variable had the highest value in Estonia (2011) and the lowest in Cyprus (2016). All these findings confirm our assumptions that entrepreneurial performance is different according to the country and its level of economic development, and also support the reason why we decided to carry out our further econometric analysis on groups of countries. To highlight the existent differences between the two groups of countries regarding the indicators selected in the analysis, we have compared the average values (see Table 3). The results suggest that, regarding competitiveness, the innovative countries are better situated than the countries in transition. In contrast, the situation is precisely the opposite when we consider GDP per capita growth. Additionally, the dynamics of the number of enterprises are higher in the countries in transition. These countries have higher birth rates but also higher death rates. The entry rates in transition countries are higher compared to innovative ones because in developing countries there exist fewer high-paying jobs and individuals decide to become entrepreneurs to earn their living. At the same time, in more developed and wealthier countries individuals find more attractive employment options than becoming self-employed ([PERSON] and [PERSON], 2016). However, higher entry rates do not translate into higher rates of competitiveness for transition countries. The innovative group of countries has higher competitiveness rates, almost 0.70% compared with transition economies. Thus, these results point out that successful firm entry is what determines an increase in competitiveness and not necessarily just the number of enterprise births. \begin{table}
\begin{tabular}{c c c} \hline \hline  & **Innovation Countries** & **Transition Countries** \\ \hline Global competitiveness index & 4.93\% & 4.26\% \\ GDP per capita growth & 0.35\% & 1.20\% \\ Birth rate & 9.17\% & 13.67\% \\ Death rate & 8.11\% & 11.89\% \\ Business churn & 17.26\% & 25.59\% \\ Net business population growth & 1.18\% & 2.95\% \\ Survival rate at 3 years & 62.75\% & 53.82\% \\ Survival rate at 5 years & 49.10\% & 39.90\% \\ Employment share at 3 years & 2.31\% & 3.90\% \\ Employment share at 5 years & 2.07\% & 3.55\% \\
3-year-old enterprises & 5.36\% & 6.69\% \\
5-year-old enterprises & 40.09\% & 4.65\% \\ Average size of 3-year-old enterprises & 2.43\% & 3.41\% \\ Average size of 5-year-old enterprises & 2.84\% & 4.45\% \\ Education & 5.32\% & 4.28\% \\ Total population & 21,309,693 & 11,018,867 \\ Resource endowment & 0.40\% & 0.93\% \\ \hline \hline \end{tabular} Source: authors’ own calculations.  
\end{table} 
Table 3: Comparing average values of indicators for transition and innovation countries. Likewise, in transition countries, the net business population growth is higher, almost 2%, but the survival rate at 3 at 5 years is lower by around 10%. The percentage of young enterprises is higher in transition countries, as well as employment share, at 3 and 5 years.