## 4 Results and Discussions  
Using previous research as a starting point, we have analysed the relationship between entrepreneurial performance and national competitiveness but we have differentiated our analysis by using two types of countries: in transition and innovation-driven. In Table 2, we show the results of the descriptive statistics of the independent and dependent variables considered in the analysis. The summary of the descriptive statistics emphasises the fact that the _global competitiveness index_ data are distributed between a minimum level of 3.92 (in Bulgaria, 2008) and a maximum of 5.61 (in Sweden, 2012). The value of the standard deviation showed relatively small variations in this index between the EU countries and also for the analysed period. The other dependent variable, _GDP per capita growth_, varied between a minimum of \(-14.55\%\) (in Estonia, 2009) and a maximum of 23.94% (in Ireland, in 2015). From the category of independent variables, the _survival rate_ has the highest variation. The _survival rate at 3 years_ had the highest value of 100% in Malta (2014) and the lowest of 23% in Lithuania (2010). Similar results were obtained for the _survival rate at 5 years_, which has the highest value of 86.73% in Malta (in 2016) and the lowest of 18% in Lithuania (in 2012). The positive results obtained by Malta can be explained by the support offered by the government in this country for small and medium enterprises. The initiative is called the Family Business Act and is the first of its kind in Europe, initiated in 2011 (Eurce, 2011). This initiative comprises a set of measures aimed at improving the survival rate of enterprises by two financing schemes. On the other hand, the low survival rate of enterprises in Lithuania could be determined by actual deaths, indicating a deterioration in the business environment of the country, or could be determined by break-ups or mergers. _Net business population growth_ varied significantly between countries and over the twelve years analysed. In Romania (in 2011), the highest growth rate of the business population was found (of 35%). The significant increase in the business population in Romania in 2011 was due to the fact that the economy started to recover from the depression due to the financial crisis, and entreprene had the courage to be involved in entrepreneurial activities again. This increase was registered especially at the level of micro-enterprises because most companies that were born in 2011 in Romania were micro-sized enterprises (having between one and four employees). \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline  & **Mean** & **Median** & **Max.** & **Min.** & **Standard Deviation** & **Observations** \\ \hline GCI & 4.735 & 4.548 & 5.612 & 3.928 & 0.485 & 243 \\ GDFC & 0.816 & 1.317 & 23.940 & \(-14.559\) & 3.801 & 243 \\ Birth & 10.482 & 9.995 & 24.880 & 3.040 & 3.781 & 234 \\ Death & 9.211 & 8.650 & 29.050 & 0.960 & 3.607 & 231 \\ Churn & 19.681 & 18.650 & 49.090 & 5.650 & 3.607 & 231 \\ Bpop & 1.685 & 1.300 & 35.470 & \(-13.640\) & 4.605 & 212 \\ Surv3 & 60.155 & 58.750 & 100.000 & 23.230 & 13.649 & 223 \\ Surv5 & 46.422 & 44.480 & 86.730 & 17.910 & 12.583 & 192 \\ Empl3 & 2.783 & 2.575 & 7.710 & 0.930 & 1.075 & 224 \\ Empl5 & 2.527 & 2.310 & 7.150 & 0.000 & 1.055 & 205 \\ Old3 & 5.753 & 5.630 & 12.350 & 1.960 & 1.484 & 229 \\ Old5 & 4.266 & 4.150 & 8.080 & 0.000 & 1.059 & 210 \\ Size3 & 3.335 & 2.980 & 8.670 & 1.140 & 1.274 & 207 \\ Size5 & 2.716 & 2.490 & 7.030 & 0.840 & 0.909 & 227 \\ Educ & 4.861 & 4.800 & 6.800 & 3.200 & 0.714 & 243 \\ LPop & 15.868 & 15.947 & 18.226 & 12.922 & 1.420 & 243 \\ Res & 0.570 & 0.348 & 2.579 & 0.001 & 5.800 & 234 \\ \hline \hline \end{tabular} Source: authors’ own calculations.  
\end{table} 
Table 2: Descriptive statistics of the variables. In Lithuania (in 2009), the highest decrease of the business population was found (of 13%).