Environmental Engineering Reference
In-Depth Information
Solar
Wind
20000
70
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18000
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60
16000
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50
14000
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12000
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10000
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0
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0
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Net Deployment costs (left scale)
RDD expenditure (right scale)
Net Deployment costs (left scale)
RDD expenditure (right scale)
in mn Euro
in mn Euro
Fig. 3 Deployment versus RD&D expenditure for wind and solar in 2010 in six EU countries (in
mn Euro). Source Bruegel calculation based on IEA and datastream. Note Net deployment costs
are calculated as the difference of the deployment costs and the net present value of the future
electricity generated
goal is decarbonisation, then emission pricing might play a more prominent role. If
the concern is on industrial policy, instead, RD&D subsidies might be preferred.
Finally, if security of supply is deemed to be more important, then deployment may
be the focus. However, we cannot read the choice of a support mechanism or its
intensity only as a techno-economic optimal response to the aforementioned
challenges. In fact, every support mechanism produces substantial distributional
effects, and institutional and information barriers are high. Consequently, without
the complex political economy it is impossible to understand why different coun-
tries (and even regions) embarked on very different policy mixes.
There are different reasons why it is dif
cult to analytically identify optimal
policy mixes: (i) the different rationales for renewables support, (ii) the numerous
technology options, (iii) the substantial differences in the initial conditions, (iv) a
wide continuum of combinations of support policies. According to Fig. 2 , countries
like Germany and Italy spent on RD&D less than 0.5 % of the budget for public
support to the deployment of renewable energy technologies. Thereby,
to our
knowledge no country applies an
approach for determining the policy
mix that best suits the rationales. This resembles a
'
analytic
'
approach, and
its persistence is astonishing, given the magnitude of the corresponding public
spending (Fig. 3 ).
'
shot in the dark
'
 
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