MPRA

much more beneficial to buy certificates than subsidize renewable energies.
Nevertheless, in 2009, about 340 million metric tonnes of CO2 emissions were saved
by the use of RES in EU. Taking the price of 15 EUR/tonne of CO2 in 2009, savings will
result in EUR 51 billion for 2009 year alone (Poser et al., 2014).
In order to see correlation between change in RES share in gross final energy consumption
and greenhouse gas (hereinafter GHG) abatement for Germany we will run the
following regressions 14 GHGE = β 0 + β 1 RESE
GHGHC = β 0 + β 1 RESHC
GHGT = β 0 + β 1 REST
where, GHGE = GHGE t − GHGE t−1 , i.e. yearly change in amount of GHG abatement
induced by change in RES-E share in gross final electricity consumption; and
RESE = RESE t − RESE t−1 , i.e.
yearly change of RES-E share in gross final electricity
consumption. Analogously, other two regressions should be read. Likewise, all
three regressions were tested for heteroskedasticity (hettest), normality (swilk) and specification
test for omitted variables (ovtest) results can be found in Appendix A in notes
under the relevant table.
No regressions were run for the Czech Republic due to lack of data.
Figure 4 is a scatter plot for all three regressions. Y-axis is measured in tonnes of CO2
equivalent and X-axis is measured in percentage points. Regression of GHG abatement
by RES-E resulted in R-squared of 0.5653, i.e. 56.53% of variability in dependent variable
is explained by the independent one. Likewise, equation of the regression – a blue line –
14 Stata outputs for all regressions can be found in Appendix A.
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