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Why and How to subsidise Energy R+D?
Michael PollittCambridge Judge Business School
FTI-CL/EPRG Spring Seminar, Cambridge16 May 2014
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Outline
• R+D, innovation and productivity in theory
• Empirical evidence on R+D and market reform
• What to do about supporting energy R+D?
• Concluding thoughts
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R+D, INNOVATION AND PRODUCTIVITY IN THEORY
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Energy R+D in context
• Total Global Fossil Fuel subsidies, 2012:– $544bn (World Energy Outlook 2013)
• Total Renewable Energy Subsidies, 2012:– $100bn (World Energy Outlook 2013)
• Total Industrial Energy R+D, 2012:– $15.7bn (Battelle R+D funding forecast 2013)
• Total OECD Government Energy R+D, 2011:– $18.6bn (IEA Statistics)
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Learning by doing high, but Learning by research significant...
Technology
Learning-by-doing rate:
Two-factor curves
Learning-by-doing rate:
Single-factor curves
1 Pulverised fuel supercritical coal 3.75% 4.8%
2 Coal conventional technology 13.39% 15.1%
3 Lignite conventional technology 5.67% 7.8%
4 Combined cycle gas turbines (1980–1989) 2.20% 2.8%
Combined cycle gas turbines (1990–1998) 0.65% 3.3%
5 Large hydro 1.96% 2.9%
6 Combined heat and power 0.23% 2.1%
7 Small hydro 0.48% 2.8%
8 Waste to electricity 41.5% 57.9%
9 Nuclear light water reactor 37.6% 53.2%
10 Wind – onshore 13.1% 15.7%
11 Solar thermal power 2.2% 22.5%
12 Wind – offshore 1.0% 8.3%
NOTE SCALE OF EXISTING CAPACITYSource: Jamasb and Kohler in Grubb et al., 2008, p. 324, Table 12.1: Learning-by-doing rates using single- and two-factor curves
Q: How much do costs fall as capacity doubles?
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Directed Technical Change (Acemoglu et al, 2012)
• Path dependency in technological innovation.
• Subsidising ‘clean’ inputs vs ‘dirty’ inputs may shift technical change on to a different pathway.
• This may involve shifting scientists from working on dirty technologies to clean ones.
• This may be cheaper in the long run than directly supporting existing clean technologies.
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Characterising Innovation (Bauer, 2012, p.16, 17)
Typology Enabling conditions
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EMPIRICAL EVIDENCE ON R+D AND ENERGY MARKET REFORM
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Government R&D Spending
Source: IEA
Canada
France
Germany
Italy
Japan
Netherlands
Spain
Switzerland
United Kingdom
United States
0 1000 2000 3000 4000 5000 6000
Government Energy R+D (2012 mUSD)
2010 2005 2000* 1995 1990
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The tale of liberalisation and R+D in the UK…
Government energy R&D in the UK - Main categories Source: IEA Energy R&D statistics database
£m 2008 Prices
1974
1976
1978
1980
1982
1984
1986
1988
1990
1992
1994
1996
1998
2000
2002
2004
2006
2008
2010
2012
0
100
200
300
400
500
600
700
800
Total other technologies or research
Other power and storage techs (include transmission and distribution)
Hydrogen and fuels cells
Nuclear fission and fusion
Renewable energy sources
Fossils fuels
Energy Efficiency
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R+D by generation and transmission declines…
Figure 4: R&D spending in the UK major generation and transmission companies [
Source: Surrey (1996), CEGB and NGC Annual Reports and Accounts, BIS R&D Scoreboards, £m 2008 Prices.From Jamasb and Pollitt, 2011, updated
1981
/82
1983
/84
1985
/86
1987
/88
1989
/90
1991
/92
1993
/94
1995
/96
1997
/98
1999
/00
2001
/02
2003
/04
2005
/06
2007
/08
2009
/10
0
50
100
150
200
250
300
350
400
450
R&D spending (transmission, i.e. NGC)
R&D spending (generation)
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R+D by distribution increases from low base…
[i]
Source: Jamasb and Pollitt, 2011, updated.LCNF aiming to spend additional £64m per annum.
1989
/90
1991
/92
1993
/94
1995
/96
1997
/98
1999
/00
2001
/02
2003
/04
2005
/06
2007
/08
2009
/10
2011
/12
0
2
4
6
8
10
12
14
Distribution Company spend on Network R&D in millions of £2008 (IFI projects only)
R&D spending
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Patenting by utility companies initially stable…
Number of Patent applications from main UK ESI actors, by type (1958-2012)From Jamasb and Pollitt, 2011, updated.
1958
1960
1962
1964
1966
1968
1970
1972
1974
1976
1978
1980
1982
1984
1986
1988
1990
1992
1994
1996
1998
2000
2002
2004
2006
2008
2010
2012
0
50
100
150
200
250
Generation companies (excluding nuclear) UK Atomic Energy Authority
Others (Electricity Council and EA Technology) Transmission and Distribution Companies
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However, Renewable Technologies do well…
1958
1960
1962
1964
1966
1968
1970
1972
1974
1976
1978
1980
1982
1984
1986
1988
1990
1992
1994
1996
1998
2000
2002
2004
2006
2008
2010
2012
0
20
40
60
80
100
120
140
160
180
Number of UK Wind and Solar Patent Applications
Wind (wind AND turbine) Solar (solar* or photovoltaic*)
Source: Espacenet Database, search by publication year.
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And also total electricity patents relatively unaffected…
Electricity related UK patents publications (UK or EPO or WIPO application with UK priority number) as % of total UK patents publications.From Jamasb and Pollitt, 2011, updated.
1958
1960
1962
1964
1966
1968
1970
1972
1974
1976
1978
1980
1982
1984
1986
1988
1990
1992
1994
1996
1998
2000
2002
2004
2006
2008
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
electricity related UK patents as percentage of all published UK patents
per
cen
tag
e sh
are
(%)
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Productivity growth strong through liberalisation…
1970-1980
1980-1990
1990-2000
2000-2010
-2.0 0.0 2.0 4.0 6.0 8.0 10.0 12.0
Productivity Growth in Energy Services
Industrial Power productivity p.a. (kWh / real £) Lighting Productivity p.a. (Lumens / real £)
Source: Derived from Fouquet (2008, 2013).
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WHAT TO DO ABOUT SUPPORTING ENERGY R+D?
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Institutions for rapid economic progress (Nelson, 2008)
• Distinguish ‘physical’ technology and ‘social’ technology• Example of delivering a recipe as distinct from tools to make
food.• Old social technologies may not be appropriate and need to be
replaced by new ones.• Institutions important to enable new developments.• The ‘fundamental uncertainty’ of innovation is why it needs to
be supported.• Only a small number of sectors drive productivity in any
historical period.• A mixture of private and public actions required, but public
actions can be wrong ones.• Basically rapid progress is clearly not about the amount money
spent on R+D…
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Institution for social innovation: Low carbon networks fund
• 2010-2015 price control• ‘up to £500m to support projects sponsored by the Distribution
Network Operators (DNOs) to try out new technology, operating and commercial arrangements’
• ‘The aim of the projects is to help all DNOs understand how they can provide security of supply at value for money as Britain moves to a low carbon economy.’
• First Tier allows DNOs to recover a proportion of expenditure incurred on small scale projects.
• Second Tier annual competition evaluated by panel of experts of up to £64 million to help fund a small number of flagship projects.
• We will be monitoring the learning that emerges from these projects in order to understand its impact on the current regulatory framework.
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Who pays for RD+D in Energy?
• IFI/LCNF are customer funded. This is a regressive tax.• RD+D benefits are uncertain and shared across economy (esp.
when projects fail in their own terms).• Benefits often not lower price of energy (which justifies payment
in proportion to use), but in security and environment which are public goods whose individual value is income elastic.
• Benefits often delayed for decades, which means current poor consumers will not benefit.
• IFI/LCNF may have transaction cost savings in collection and monitoring but these are not clear (may be marginally cheaper to collect and monitor using existing systems).
• Overall public RD+D should come out of general taxation.• But also, collaborative private RD+D is possible, e.g. eFIS EV
project in Milton Keynes (Miles, 2014) led by Arup and Mitsui.
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CONCLUDING THOUGHTS
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Concluding thoughts
• Directed technical change is important but subsidised R+D is only one way to achieve this.
• We should not close off possibility of radical innovation.
• R+D expenditure in energy did decline, but recovering.• Innovation and productivity have not declined.
• R+D in energy needs to pay attention to ‘social technology’ given relative innovation in Mbits vs MWhs and path dependency of existing systems.
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Innovation in what?
• In governance and payment arrangements in energy? (e.g. SO, LMPs, connection charging)
• In the use of information from smart grids and smart meters? (e.g. in pricing, control)
• In policy making in the face of rising complexity of regulatory decision making. (e.g. in customer engagement, cost benefit assessment)
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Bibliography
• Acemoglu, D., Aghion, P., Bursztyn, L. and Hemous, D. (2012), ‘The Environment and Directed Technical Change’, American Economic Review, 102 (1): 131-166.
• Bauer, J.M. (2012), Designing Regulation to Support Innovation: Experiences and Future Challenges, CRNI Conference November 30, 2012.
• Fouquet, R. (2008) Heat Power and Light: Revolutions in Energy Services. Edward Elgar. Cheltenham and Northampton, MA.
• Fouquet, R. (2013), Long Run Demand for Energy Services: the Role of Economic and Technological Development, Basque Centre on Climate Change Working Paper.
• Jamasb, T. and Kohler, J. (2008), ‘Learning Curves for energy technologies: a critical assessment’, in Grubb et al., pp.314-332.
• Jamasb, T.J. and Pollitt, M.G. (2008), ‘Liberalisation and R&D in Network Industries: The Case of the Electricity Industry’, Research Policy 37 (6-7), pp.995-1008.
• Jamasb, T. and Pollitt, M. (2011), ‘Electricity Sector Liberalisation and Innovation: An Analysis of the UK Patenting Activities’, Research Policy, Vol.40, No.2, pp.309-324.
• Miles, J. (2014), Electric Vehicles: Cleaner, Better,…Cheaper?, EPRG Seminar 17 February 2014.
• Nelson, R.R. (2008), ‘What enables rapid economic progress: What are the needed institutions?’, Research Policy, 37: 1-11.