MPRA

with average annual growth rate of 33%.
No regression was run for the Czech Republic due to lack of data.
Figure 10: German solar energy
10 000
8 000
6 000
4 000
2 000
0
29 34 39 44 49 54
-2 000
BMWi and own computations
Figure 10 is a scatter plot for solar RES in Germany. Y-axis and X-axis are same as
in Figure 5. Equation of the line is
̂MW = 9441.76
(3542.484) − 154.9
(77.53) F IT t
Constant is statistically significant at 5% significance level and independent variable is
statistically significant only at 10% significance level as well as whole regression is significant
only at 10% significance level. R-squared of this equation is 0.2219, i.e. independent
variable explains 22.19% of variability of dependent variable. With one cent increase in
FIT, installed capacity will decrease by 154.9 MW. But, Ramsey RESET test concludes
that we have omitted variables. Thence, we add a polynomial of second order. All coefficients
and constant become statistically significant even at 1% significance level and
regression is overall significant even at 1% significance level. R-squared increases to the
23