When and How to Support Renewables?—Letting the Data Speak - Green Energy and Efficiency: An Economic Perspective - page 291

Fig. 1 Schematic picture of cost reduction for renewable energy technologies

However, too high deployment subsidies can induce lock-in into a (short-term) cost
ef cient technology preventing the development of other technology with higher

long-term potential. Additionally, large subsidies can distort market incentives in a
way that there is no net reduction in fossil energy use as the production of
renewable energy units is very energy intensive. Public R&D on the other hand can

table for private R&D.
In the US, states with transparent and openly available public R&D also attracted
signi

ll the knowledge gaps covering areas which would not pro

cantly more private R&D and venture capital in the respective sector [ 8 ].
The model can be extended with additional variables to account for other factors
that drive technological change. 9 Johnstone et al. ( 2010 ) conduct a panel regression
across 25 countries between 1978

2003 for renewable energy patents showing that
with respect to patent activity taxes, obligations and tradable certi

-

cates are the

only tools statically signi cant. The estimations exhibit that R&D spending is more

effective for wind technologies whereas solar technologies are better supported by
price incentives. Furthermore, stronger environmental legislation leads to more
patents with heterogeneity across technologies: obligations and tradable certi cates

are most important for wind energy, which can be explained by the cheapest form
of renewables hypothesis. According to their

ndings, solar energy on the other
hand requires more direct investment support. Nonetheless, Johnstone et al. ( 2010 )
argue that in general most patent estimates are awed due to country heterogeneity

and time trends (Fig. 1 ).
Bettencourt et al. [ 2 ] explain the production of new energy patents in terms of
new R&D investments and expanding markets based on a Cobb-Douglas produc-
tion function. They

most technologies show greater sensitivity to market
growth than to public R&D investments though for wind the two contributions are
similar

nd that '

.
Summing up, literature provides some evidence of (i) decreasing returns to both,
deployment and RD&D in driving innovation and (ii) a potential positive interac-
tion of the two policy measures. In addition, the price of the competing technologies

'

9 Popp [ 10 ] argues that the knowledge stock and the price of energy are important drivers of
innovation in renewable energy technologies.