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Knowledge spillovers between PV installers can reduce the cost of installing solar PV

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  • Nemet, Gregory F.
  • Lu, Jiaqi
  • Rai, Varun
  • Rao, Rohan

Abstract

We analyze pricing in PV systems using data from 2008-2014 to identify the effects of knowledge spillovers in reducing the installed cost of PV. This paper estimates the size of the effects of learning by doing and knowledge spillovers using multiple formulations of spillover related variables. We found knowledge spillovers between firms within a county to be a significant and substantial factor in reducing the costs of PV. However, these spillovers reduce costs only for firms over a certain size threshold, and no cost-reducing spillovers were found for smaller installers. Geographic spillovers, within a firm from one county to another were also significant although not as large as the local between-firm effects. We ran 43 specifications on the data and generally found these main results to be robust, although not in every specification. One implication of these results is that policies that subsidize demand for PV are leading to the creation of new knowledge that would not exist at lower levels of demand. That the spillovers become stronger at higher levels of experience suggests that these subsidies would need to be substantial, particularly in new markets with many small firms.

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  • Nemet, Gregory F. & Lu, Jiaqi & Rai, Varun & Rao, Rohan, 2020. "Knowledge spillovers between PV installers can reduce the cost of installing solar PV," Energy Policy, Elsevier, vol. 144(C).
    • Handle: RePEc:eee:enepol:v:144:y:2020:i:c:s0301421520303384
    DOI: 10.1016/j.enpol.2020.111600
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    as
    1. Miguélez, Ernest & Moreno, Rosina, 2015. "Knowledge flows and the absorptive capacity of regions," Research Policy, Elsevier, vol. 44(4), pages 833-848.
    2. O'Shaughnessy, Eric, 2019. "Non-monotonic effects of market concentration on prices for residential solar photovoltaics in the United States," Energy Economics, Elsevier, vol. 78(C), pages 182-191.
    3. Strandholm, John C. & Espínola-Arredondo, Ana & Munoz-Garcia, Felix, 2018. "Regulation, free-riding incentives, and investment in R&D with spillovers," Resource and Energy Economics, Elsevier, vol. 53(C), pages 133-146.
    4. Feldman, Maryann P. & Kogler, Dieter F., 2010. "Stylized Facts in the Geography of Innovation," Handbook of the Economics of Innovation, in: Bronwyn H. Hall & Nathan Rosenberg (ed.), Handbook of the Economics of Innovation, edition 1, volume 1, chapter 0, pages 381-410, Elsevier.
    5. Battke, Benedikt & Schmidt, Tobias S. & Stollenwerk, Stephan & Hoffmann, Volker H., 2016. "Internal or external spillovers—Which kind of knowledge is more likely to flow within or across technologies," Research Policy, Elsevier, vol. 45(1), pages 27-41.
    6. Patricia Laurens & Christian Le Bas & Stéphane Lhuillery & Antoine Schoen, 2017. "The determinants of cleaner energy innovations of the world’s largest firms: the impact of firm learning and knowledge capital," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 26(4), pages 311-333, May.
    7. Nemet, Gregory F. & O’Shaughnessy, Eric & Wiser, Ryan & Darghouth, Naïm & Barbose, Galen & Gillingham, Ken & Rai, Varun, 2017. "Characteristics of low-priced solar PV systems in the U.S," Applied Energy, Elsevier, vol. 187(C), pages 501-513.
    8. Kavlak, Goksin & McNerney, James & Trancik, Jessika E., 2018. "Evaluating the causes of cost reduction in photovoltaic modules," Energy Policy, Elsevier, vol. 123(C), pages 700-710.
    9. Nemet, Gregory F. & O'Shaughnessy, Eric & Wiser, Ryan & Darghouth, Naïm R. & Barbose, Galen & Gillingham, Ken & Rai, Varun, 2017. "What factors affect the prices of low-priced U.S. solar PV systems?," Renewable Energy, Elsevier, vol. 114(PB), pages 1333-1339.
    10. Gregory F. Nemet, 2012. "Subsidies for New Technologies and Knowledge Spillovers from Learning by Doing," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 31(3), pages 601-622, June.
    11. Mauleón, Ignacio, 2016. "Photovoltaic learning rate estimation: Issues and implications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 65(C), pages 507-524.
    12. Steffen, Bjarne & Matsuo, Tyeler & Steinemann, Davita & Schmidt, Tobias S., 2018. "Opening new markets for clean energy: The role of project developers in the global diffusion of renewable energy technologies," Business and Politics, Cambridge University Press, vol. 20(4), pages 553-587, December.
    13. Nemet, Gregory F., 2012. "Inter-technology knowledge spillovers for energy technologies," Energy Economics, Elsevier, vol. 34(5), pages 1259-1270.
    14. O'Shaughnessy, Eric & Nemet, Gregory F. & Pless, Jacquelyn & Margolis, Robert, 2019. "Addressing the soft cost challenge in U.S. small-scale solar PV system pricing," Energy Policy, Elsevier, vol. 134(C).
    15. O. Schmidt & A. Hawkes & A. Gambhir & I. Staffell, 2017. "The future cost of electrical energy storage based on experience rates," Nature Energy, Nature, vol. 2(8), pages 1-8, August.
    16. Pillai, Unni, 2015. "Drivers of cost reduction in solar photovoltaics," Energy Economics, Elsevier, vol. 50(C), pages 286-293.
    17. Newbery, David, 2018. "Evaluating the case for supporting renewable electricity," Energy Policy, Elsevier, vol. 120(C), pages 684-696.
    18. Patricia Laurens & Christian Le Bas & Stéphane Lhuillery & Antoine Schoen, 2017. "The determinants of cleaner energy innovations of the world’s largest firms: the impact of firm learning and knowledge capital," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 26(4), pages 311-333, May.
    19. Neij, Lena & Heiskanen, Eva & Strupeit, Lars, 2017. "The deployment of new energy technologies and the need for local learning," Energy Policy, Elsevier, vol. 101(C), pages 274-283.
    20. Hansen, Ulrich Elmer & Lema, Rasmus, 2019. "The co-evolution of learning mechanisms and technological capabilities: Lessons from energy technologies in emerging economies," Technological Forecasting and Social Change, Elsevier, vol. 140(C), pages 241-257.
    21. K. J. Arrow, 1971. "The Economic Implications of Learning by Doing," Palgrave Macmillan Books, in: F. H. Hahn (ed.), Readings in the Theory of Growth, chapter 11, pages 131-149, Palgrave Macmillan.
    22. Yuan Zhou & Meijuan Pan & Frauke Urban, 2018. "Comparing the International Knowledge Flow of China’s Wind and Solar Photovoltaic (PV) Industries: Patent Analysis and Implications for Sustainable Development," Sustainability, MDPI, vol. 10(6), pages 1-34, June.
    23. Rai, Varun & Reeves, D. Cale & Margolis, Robert, 2016. "Overcoming barriers and uncertainties in the adoption of residential solar PV," Renewable Energy, Elsevier, vol. 89(C), pages 498-505.
    24. Samadi, Sascha, 2018. "The experience curve theory and its application in the field of electricity generation technologies – A literature review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 2346-2364.
    25. Elizabeth Baldwin & Yongyang Cai & Karlygash Kuralbayeva, 2018. "To Build or Not to Build? Capital Stocks and Climate Policy," CESifo Working Paper Series 6884, CESifo.
    26. Severin Borenstein, 2017. "Private Net Benefits of Residential Solar PV: The Role of Electricity Tariffs, Tax Incentives, and Rebates," Journal of the Association of Environmental and Resource Economists, University of Chicago Press, vol. 4(S1), pages 85-122.
    27. Harald Gruber, 1998. "Learning by Doing and Spillovers: Further Evidence for the Semiconductor Industry," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 13(6), pages 697-711, December.
    28. Mauleón, Ignacio & Hamoudi, Hamid, 2017. "Photovoltaic and wind cost decrease estimation: Implications for investment analysis," Energy, Elsevier, vol. 137(C), pages 1054-1065.
    29. David Klenert & Linus Mattauch & Emmanuel Combet & Ottmar Edenhofer & Cameron Hepburn & Ryan Rafaty & Nicholas Stern, 2018. "Making carbon pricing work for citizens," Nature Climate Change, Nature, vol. 8(8), pages 669-677, August.
    30. Svetlana Ratner & ?vgenii Khrustalev, 2018. "Learning Rates in Wind Energy: Cross-country Analysis and Policy Applications for Russia," International Journal of Energy Economics and Policy, Econjournals, vol. 8(3), pages 258-266.
    31. Arthur van Benthem & Kenneth Gillingham & James Sweeney, 2008. "Learning-by-Doing and the Optimal Solar Policy in California," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3), pages 131-152.
    32. Kim, Hansung & Cheon, Hyungkyu & Ahn, Young-Hwan & Choi, Dong Gu, 2019. "Uncertainty quantification and scenario generation of future solar photovoltaic price for use in energy system models," Energy, Elsevier, vol. 168(C), pages 370-379.
    33. Kenneth Gillingham, Hao Deng, Ryan Wiser, Naim Darghouth, Gregory Nemet, Galen Barbose, Varun Rai, and Changgui Dong, 2016. "Deconstructing Solar Photovoltaic Pricing," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3).
    34. Sagar, Ambuj D. & van der Zwaan, Bob, 2006. "Technological innovation in the energy sector: R&D, deployment, and learning-by-doing," Energy Policy, Elsevier, vol. 34(17), pages 2601-2608, November.
    35. Nemet, Gregory F., 2006. "Beyond the learning curve: factors influencing cost reductions in photovoltaics," Energy Policy, Elsevier, vol. 34(17), pages 3218-3232, November.
    36. Shayegh, Soheil & Sanchez, Daniel L. & Caldeira, Ken, 2017. "Evaluating relative benefits of different types of R&D for clean energy technologies," Energy Policy, Elsevier, vol. 107(C), pages 532-538.
    37. Wei, Max & Smith, Sarah Josephine & Sohn, Michael D., 2017. "Non-constant learning rates in retrospective experience curve analyses and their correlation to deployment programs," Energy Policy, Elsevier, vol. 107(C), pages 356-369.
    38. Rubin, Edward S. & Azevedo, Inês M.L. & Jaramillo, Paulina & Yeh, Sonia, 2015. "A review of learning rates for electricity supply technologies," Energy Policy, Elsevier, vol. 86(C), pages 198-218.
    39. Lavidas, George, 2019. "Energy and socio-economic benefits from the development of wave energy in Greece," Renewable Energy, Elsevier, vol. 132(C), pages 1290-1300.
    40. Elena Verdolini & Valentina Bosetti, 2017. "Environmental Policy and the International Diffusion of Cleaner Energy Technologies," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 66(3), pages 497-536, March.
    41. Johan Lilliestam & Mercè Labordena & Anthony Patt & Stefan Pfenninger, 2017. "Empirically observed learning rates for concentrating solar power and their responses to regime change," Nature Energy, Nature, vol. 2(7), pages 1-6, July.
    42. Jonas Grafström, 2018. "International knowledge spillovers in the wind power industry: evidence from the European Union," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 27(3), pages 205-224, April.
    43. Zhang, Fang & Gallagher, Kelly Sims, 2016. "Innovation and technology transfer through global value chains: Evidence from China's PV industry," Energy Policy, Elsevier, vol. 94(C), pages 191-203.
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