The Price of Renewable Energy Policy Risk

1. The Price of Renewable Energy Policy Risk Rolf Wüstenhagen (jointworkwith Sonja Lüthi) U Minnesota, April 29, 2010 Empirical Insights from Choice Experiments with European Solar Energy Project Developers

2. Good Energies Chair for Management of Renewable Energies at the University of St. Gallen (IWÖ-HSG) • Established in 2009 withsupportfrom Good Energies • Part of one of Europe‘sleading business schools • Dedicatedteam (9 people) • 30+ Bachelor/MasterTheses, ≈ 3-4 PhDdissertationsp.a. • Research and teaching on... • Investment Decisions and Venture Capital • ConsumerDecisions and Marketing RE • Business Models forRenewable Energy • Energy Policy • Forthcoming Energy Policy Special Issue: „StrategicChoices in Renewable Energy Investment“ • Handbook of Research on Energy Entrepreneurship

3. Vision of ourChair – The Road from 20:80 to 80:20 Non-Renewable Energies Renewable Energies Berlin, 24.10.2009 (...)Thenew German government‘sobjectiveis „a consistentenergypolicy, whichleadsinto a new age of renewableenergies“, saidChancellor Angela Merkel whenshepresentedthecoalitionagreement. „Renewableenergyshallaccountforthemajorpart of German energysupply“, and conventionalenergysourcesshallcontinuouslybereplaced. (Source: dpa)

4. Thepaper in a nutshell • Recent growth of renewable energies in Europe, particular solar photovoltaics (PV), largely driven by public policy • Seemingly similar policies (e.g. feed-in tariff of similar level) lead to different results in different countries • Vivid debate about what constitutes efficient and effective renewable energy policies, recently highlighting importance of both sides of the risk-return equation • Consensus that policy risk matters. BUT: Which risk factors are relevant, and how should policy makers prioritize them? • Two approaches to understanding investor behavior: • Revealed preferences (installed capacities). Limitation: Few cases, retrospective. • Stated preferences (choice experiments). • Result: Empirically measuring the price of policy risk, leading to specific policy recommendations.

5. Solar Energy: Small market share today, large future potential 2100 64% EJ/a Geothermal 1600 Other renewables Solar Thermal (Heat) 1400 1200 Solar electricity 1000 (PV and Solar Thermal) 2007 0.1% 800 Wind 600 Biomass (modern) Biomass (traditional) 400 Hydroelectricity Nuclear 200 Gas Coal Oil 0 2000 2010 2020 2030 2040 2050 2100 Global primary energy scenario: Renewables 80% of primary energy by 2100 Source: German Advisory Council on Global Change WBGU Berlin 2003 www.wbgu.de

6. Change we can believe in:New power plant investments in Europe GuessWhoisWho: Oil, Gas,Coal, Nuclear, Hydro, Wind, Solar (PV) Source: Platts, EWEA

7. Solar Photovoltaics: Towards „Grid Parity“ Political Market Pilot Self-Sustaining Market R&D

8. 2010 Grid parity European countries 0,40 Grid Parity Installed System Price: EUR 3 / Wp 0,35 0,30 Denmark Italy 0,25 Netherlands Germany 0,20 Average household electricity price [€/kWh] Portugal France Sweden 0,15 Spain Hungary 0,10 Greece 0,05 0,00 700 800 900 1000 1100 1200 1300 1400 1500 1600 1700 1800 1900 2000 Solar Irradiation [kWh/m2*a] Source: Centrotherm May 2008

9. Greening Goliaths vs. Emerging Davids Source:Hockerts and Wüstenhagen (2010)

10. Solar industry growth so far driven by Technology & Policy, increasing importance of Business Models η § €

11. Increasing number of countries with feed-in tariffs for renewable energy Source: Klein et al. (2006)

12. Influence of policy design on the deployment of renewable energy technologies - Sufficient and secure support is essential for increasing solar capacity (Mendonça, 2007; Jacobsson & Lauber, 2006; Butler & Neuhoff, 2005; Lauber & Toke, 2005; Rowlands, 2005; Wiser et al. 1997): • Provide financial security: A guaranteed level of tariffs for a sufficiently long duration (e.g. 20 years) ensures planning security and makes the investment in solar electricity systems attractive • Level of tariff higher than the marginal costs of generation (in order to ensure a sufficient return on investments) • Solar policy stability: A stable and foreseeable solar policy allows investors to plan theiractivities. - For efficient policy design, the project development and financing processes need to be understood (Wiser & Pickle, 1998, Langniss 1999) Empirical Puzzle: Why do similarpolicies (PV feed-intariffs) lead to different outcomesacrosscountries?

13. Empirical Puzzle: Level of return fails to explain level of installed PV capacity Source: Lüthi (2010)

14. Objectives • Empirically measure the price of energy policy risk in the case of support policies for photovoltaics, in order to… • provide recommendations for design of effective PV policies. • Research Questions • How important are various attributes of solar energy policies in influencing the decision of a PV project developer to invest in a given country? • What is investors' willingness-to-accept specific policy risks? ?

15. Empirical Research Design,Data and Sample • Stated preference survey among international solar energy project developers from Germany, Italy, Spain, Greece and Switzerland, conducted in October-November 2008. • Participation solicited by phone, e-mail, at a solar industry trade fair, through the University of St. Gallen website and a leaflet in a solar industry journal. • 135 respondents logged on to the survey website, 63 questionnaires were completed. • Each respondent completed 25 choice tasks, resulting in a total dataset of N=1575 decisions.

16. Methodology: Adaptive Conjoint Analysis (ACA) • Simulation of a “real” investment choice situation • Utility function and decision rule: Ujk = utility of policy k for investor j • vjk = vector of deterministic relevant decision attributes which subsumes feasible attributes of policy k for investor j (zjk) • jk = stochastic random variable which comprises unobservable policy attributes zjk*, unobservable personal attributes sj* and measurement errors jk. • Choice Analysis: Pjk = probability that investor j chooses policy k • Multinominal logit model (MNL) • Maximum likelihood estimation

17. Choice Experiments in Marketing Research: Sample Choice Task from Sammer/Wüstenhagen 2006 3-5 levels per attribute The 5-6 most important attributes of the buying decision – preferably independent of each other Respondent chooses preferredproduct e.g. 20 Choice Tasks with varying attribute levels

18. Design of the Choice Experiments Based on qualitative pre-study, the following attributes were selected for the ACA: Predefined framework conditions: solar radiation: 1500 kWh/m2 size of the installation: 500 kW

19. Sample Choice Task from ACA questionnaire(paired comparison)

20. Sample Choice Task from ACA questionnaire(calibration task)

21. Relative Importance of Attributes • How important are various attributes of solar energy policies in influencing project developers' decision to invest in a given country?

22. Normalized Part Worth Utilities of Attribute Levels

23. Implications for Policy Makers: The "Price Tag" of Poor Policies

24. Interpretation of Results • Solar energy investors are particularly sensitive to duration of administrative procedures, followed by other policy risks (policy changes, existence of cap). Duration of support is relatively less important. • For every half-year increase in the duration of the administrative process, a government has to pay investors a premium of about 4 ct/kWh (all else being equal). • Removing a loose (tight) cap will allow governments to attract the same level of investment at a feed-in tariff that is about 5 (10) ct/kWh lower.

25. Limitations and further research • Sample size > should be increased in future studies (without compromising on quality of respondents) • Stated preferences > validation of implicit willingness-to-accept by cross-checking with revealed preferences (especially as longer time series become available) • Relevance of unobserved factors (e.g. language, country size) and social interaction (e.g. "hype") • Transfer to private investors (e.g. residential homeowners buying solar panels) • Transfer to corporate finance decisions and explore role of policy aversion bias

26. Conclusions • Ultimately, the achievement of energy policy objectives hinges on whether policy instruments effectively influence investor behavior. • Applying a sophisticated research method from another field (marketing), the research presented here is one of the first empirical contributions that investigates the influence of renewable energy policies on investor decisions. • We confirm prior research that points to the importance of "non-economic" barriers to deployment of renewables, such as policy instability. • Based on a solid empirical basis, we develop specific recommendations that enable policy makers to assess the cost and benefit of reducing various elements of policy risk.

27. Thank you! Prof. Dr. Rolf Wüstenhagen Director Institute forEconomy and theEnvironment University of St. Gallen Tigerbergstrasse 2 CH-9000 St. Gallen / Switzerland Telephone: +41-71-224 25 87 Mobile: +41-76-306 43 13 E-mail: rolf.wuestenhagen@unisg.ch http://goodenergies.iwoe.unisg.ch

28. Further Reading Lüthi, S. and Wüstenhagen, R. (2010): The Price of Policy Risk – Empirical Insights from Choice Experiments with European Photovoltaic Project Developers (under review). Hockerts, K. and Wüstenhagen, R. (2010): Greening Goliaths versus Emerging Davids – Theorizing about the Role of Incumbents and New Entrants in Sustainable Entrepreneurship. Journal of Business Venturing, forthcoming. Känzig, J. and Wüstenhagen, R. (2010): The effect of life-cycle cost information on consumer investment decisions for eco-innovation. Journal of Industrial Ecology, 1 (14), 121-136. Bürer, M.J. and Wüstenhagen, R. (2009): Which renewable energy policy is a venture capitalist's best friend? Empirical evidence from a survey of international cleantech investors. Energy Policy, 37 (12), 4997-5006. Wüstenhagen, R., Wolsink, M., Bürer, M.J. (2007): Social acceptance of renewable energy innovation: An introduction to the concept. Energy Policy 35 (5): 2683-2691. Wüstenhagen, R. and Teppo, T. (2006): Do venture capitalists really invest in good industries? Risk-return perceptions and path dependence in the emerging European energy VC market. Int. J. Technology Management, 34 (1/2), 63-87. Sammer, K. and Wüstenhagen, R. (2006): The Influence of Eco-Labelling on Consumer Behaviour – Results of a Discrete Choice Analysis for Washing Machines. Business Strategy and the Environment, 15, 185-199. Wüstenhagen, R. and Bilharz, M. (2006): Green Energy Market Development in Germany: Effective Public Policy and Emerging Customer Demand. Energy Policy, 34, 1681-1696. Moore, B. and Wüstenhagen, R. (2004): Innovative and Sustainable Energy Technologies: The Role of Venture Capital, Business Strategy and the Environment, 13, 235-245.