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The impact of technical efficiency, innovation, and climate policy on the economic viability of renewable electricity generation

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  • Lee, Jonathan M.
  • Howard, Gregory

Abstract

Renewable energy is a promising technology for combating climate change, and state governments are increasingly implementing policies to encourage its adoption. Given these circumstances, it is important to assess the degree to which continued expansion of solar and wind generating capacity is desirable from an economic perspective. Stochastic frontier models of utility-scale renewable generation allow us to extrapolate the net present value of new solar and wind projects for 47 U.S. states (41 wind and 47 solar). Innovation has played a key role in solar and wind expansion with construction costs falling by 64% and 40% since 2013, respectively. Using current construction costs and electricity prices, continued solar expansion is profitable in 79% of states and wind expansion is profitable in 76% of states. Assuming a costless shift to the electricity generation frontier for renewables increases solar and wind viability to 87% and 90% of states, respectively. Finally, the outlook for solar and wind further improves under a first-best carbon tax that renders solar economically viable in 94% of states and wind viable in 93% of states. These findings are empirically robust to numerous stochastic frontier specifications and other sensitivity analyses.

Suggested Citation

  • Lee, Jonathan M. & Howard, Gregory, 2021. "The impact of technical efficiency, innovation, and climate policy on the economic viability of renewable electricity generation," Energy Economics, Elsevier, vol. 100(C).
  • Handle: RePEc:eee:eneeco:v:100:y:2021:i:c:s0140988321002632
    DOI: 10.1016/j.eneco.2021.105357
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    as
    1. Alex Hollingsworth & Ivan Rudik, 2019. "External Impacts of Local Energy Policy: The Case of Renewable Portfolio Standards," Journal of the Association of Environmental and Resource Economists, University of Chicago Press, vol. 6(1), pages 187-213.
    2. Pestana Barros, Carlos & Sequeira Antunes, Olinda, 2011. "Performance assessment of Portuguese wind farms: Ownership and managerial efficiency," Energy Policy, Elsevier, vol. 39(6), pages 3055-3063, June.
    3. Zhao, Xiaoli & Ma, Chunbo, 2013. "Deregulation, vertical unbundling and the performance of China's large coal-fired power plants," Energy Economics, Elsevier, vol. 40(C), pages 474-483.
    4. Francisco Munoz & Enzo Sauma & Benjamin Hobbs, 2013. "Approximations in power transmission planning: implications for the cost and performance of renewable portfolio standards," Journal of Regulatory Economics, Springer, vol. 43(3), pages 305-338, June.
    5. Meeusen, Wim & van den Broeck, Julien, 1977. "Efficiency Estimation from Cobb-Douglas Production Functions with Composed Error," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 18(2), pages 435-444, June.
    6. Shrimali, Gireesh & Kniefel, Joshua, 2011. "Are government policies effective in promoting deployment of renewable electricity resources?," Energy Policy, Elsevier, vol. 39(9), pages 4726-4741, September.
    7. Seifert, Stefan & Cullmann, Astrid & von Hirschhausen, Christian, 2016. "Technical efficiency and CO2 reduction potentials — An analysis of the German electricity and heat generating sector," Energy Economics, Elsevier, vol. 56(C), pages 9-19.
    8. Barbose, Galen & Wiser, Ryan & Heeter, Jenny & Mai, Trieu & Bird, Lori & Bolinger, Mark & Carpenter, Alberta & Heath, Garvin & Keyser, David & Macknick, Jordan & Mills, Andrew & Millstein, Dev, 2016. "A retrospective analysis of benefits and impacts of U.S. renewable portfolio standards," Energy Policy, Elsevier, vol. 96(C), pages 645-660.
    9. Gale A. Boyd and Jonathan M. Lee, 2020. "Relative Effectiveness of Energy Efficiency Programs versus Market Based Climate Policies in the Chemical Industry," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3), pages 39-62.
    10. Johnson, Erik Paul, 2014. "The cost of carbon dioxide abatement from state renewable portfolio standards," Resource and Energy Economics, Elsevier, vol. 36(2), pages 332-350.
    11. Subal Kumbhakar & Gudbrand Lien & J. Hardaker, 2014. "Technical efficiency in competing panel data models: a study of Norwegian grain farming," Journal of Productivity Analysis, Springer, vol. 41(2), pages 321-337, April.
    12. See, Kok Fong & Coelli, Tim, 2012. "An analysis of factors that influence the technical efficiency of Malaysian thermal power plants," Energy Economics, Elsevier, vol. 34(3), pages 677-685.
    13. Lin, Boqiang & Du, Kerui, 2013. "Technology gap and China's regional energy efficiency: A parametric metafrontier approach," Energy Economics, Elsevier, vol. 40(C), pages 529-536.
    14. John W. Anderson & Gordon W. Leslie & Frank A. Wolak, 2019. "Measuring the Impact of Own and Others’ Experience on Project Costs in the U.S. Wind Generation Industry," NBER Working Papers 26114, National Bureau of Economic Research, Inc.
    15. James Bushnell & Carla Peterman & Catherine Wolfram, 2008. "Local Solutions to Global Problems: Climate Change Policies and Regulatory Jurisdiction," Review of Environmental Economics and Policy, Association of Environmental and Resource Economists, vol. 2(2), pages 175-193, Summer.
    16. Burke, M. & Craxton, M. & Kolstad, C.D. & Onda, C. & Allcott, H. & Baker, E. & Barrage, L. & Carson, R. & Gillingham, K. & Graff-Zivin, J. & Greenstone, M. & Hallegatte, S. & Hanemann, W.M. & Heal, G., 2016. "Opportunities for advances in climate change economics," ISU General Staff Papers 3565, Iowa State University, Department of Economics.
    17. Kumbhakar,Subal C. & Wang,Hung-Jen & Horncastle,Alan P., 2015. "A Practitioner's Guide to Stochastic Frontier Analysis Using Stata," Cambridge Books, Cambridge University Press, number 9781107609464, January.
    18. Halvorsen, Robert & Palmquist, Raymond, 1980. "The Interpretation of Dummy Variables in Semilogarithmic Equations," American Economic Review, American Economic Association, vol. 70(3), pages 474-475, June.
    19. Wooldridge, Jeffrey M., 2019. "Correlated random effects models with unbalanced panels," Journal of Econometrics, Elsevier, vol. 211(1), pages 137-150.
    20. Brown, Patrick R. & O'Sullivan, Francis M., 2020. "Spatial and temporal variation in the value of solar power across United States electricity markets," Renewable and Sustainable Energy Reviews, Elsevier, vol. 121(C).
    21. Fischer, Carolyn & Newell, Richard G., 2008. "Environmental and technology policies for climate mitigation," Journal of Environmental Economics and Management, Elsevier, vol. 55(2), pages 142-162, March.
    22. Daniel T. Kaffine, Brannin J. McBee, and Jozef Lieskovsky, 2013. "Emissions Savings from Wind Power Generation in Texas," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1).
    23. Curtis, E. Mark & Lee, Jonathan M., 2019. "When do environmental regulations backfire? Onsite industrial electricity generation, energy efficiency and policy instruments," Journal of Environmental Economics and Management, Elsevier, vol. 96(C), pages 174-194.
    24. Joseph E. Aldy & Todd D. Gerarden & Richard L. Sweeney, 2023. "Investment versus Output Subsidies: Implications of Alternative Incentives for Wind Energy," Journal of the Association of Environmental and Resource Economists, University of Chicago Press, vol. 10(4), pages 981-1018.
    25. Jondrow, James & Knox Lovell, C. A. & Materov, Ivan S. & Schmidt, Peter, 1982. "On the estimation of technical inefficiency in the stochastic frontier production function model," Journal of Econometrics, Elsevier, vol. 19(2-3), pages 233-238, August.
    26. L. Dean Hiebert, 2002. "The Determinants of the Cost Efficiency of Electric Generating Plants: A Stochastic Frontier Approach," Southern Economic Journal, John Wiley & Sons, vol. 68(4), pages 935-946, April.
    27. Kevin Novan, 2015. "Valuing the Wind: Renewable Energy Policies and Air Pollution Avoided," American Economic Journal: Economic Policy, American Economic Association, vol. 7(3), pages 291-326, August.
    28. Carolyn Fischer, 2010. "Renewable Portfolio Standards: When Do They Lower Energy Prices?," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1), pages 101-120.
    29. Berry, David, 2002. "The market for tradable renewable energy credits," Ecological Economics, Elsevier, vol. 42(3), pages 369-379, September.
    30. Battese, George E. & Coelli, Tim J., 1988. "Prediction of firm-level technical efficiencies with a generalized frontier production function and panel data," Journal of Econometrics, Elsevier, vol. 38(3), pages 387-399, July.
    31. Tanaka, Makoto & Chen, Yihsu, 2013. "Market power in renewable portfolio standards," Energy Economics, Elsevier, vol. 39(C), pages 187-196.
    32. Mundlak, Yair, 1978. "On the Pooling of Time Series and Cross Section Data," Econometrica, Econometric Society, vol. 46(1), pages 69-85, January.
    33. Dong, C.G., 2012. "Feed-in tariff vs. renewable portfolio standard: An empirical test of their relative effectiveness in promoting wind capacity development," Energy Policy, Elsevier, vol. 42(C), pages 476-485.
    34. Riju Joshi & Jeffrey M. Wooldridge, 2019. "Correlated Random Effects Models with Endogenous Explanatory Variables and Unbalanced Panels," Annals of Economics and Statistics, GENES, issue 134, pages 243-268.
    35. Burke, M & Craxton, M & Kolstad, CD & Onda, C & Allcott, H & Baker, E & Barrage, L & Carson, R & Gillingham, K & Graf-Zivin, J & Greenstone, M & Hallegatte, S & Hanemann, WM & Heal, G & Hsiang, S & Jo, 2016. "Opportunities for advances in climate change economics," University of California at Santa Barbara, Recent Works in Economics qt4tc5d9pb, Department of Economics, UC Santa Barbara.
    36. Joseph Cullen, 2013. "Measuring the Environmental Benefits of Wind-Generated Electricity," American Economic Journal: Economic Policy, American Economic Association, vol. 5(4), pages 107-133, November.
    37. Iglesias, Guillermo & Castellanos, Pablo & Seijas, Amparo, 2010. "Measurement of productive efficiency with frontier methods: A case study for wind farms," Energy Economics, Elsevier, vol. 32(5), pages 1199-1208, September.
    38. Christopher R. Knittel, 2002. "Alternative Regulatory Methods And Firm Efficiency: Stochastic Frontier Evidence From The U.S. Electricity Industry," The Review of Economics and Statistics, MIT Press, vol. 84(3), pages 530-540, August.
    39. Aigner, Dennis & Lovell, C. A. Knox & Schmidt, Peter, 1977. "Formulation and estimation of stochastic frontier production function models," Journal of Econometrics, Elsevier, vol. 6(1), pages 21-37, July.
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    3. Li, Siying & Cifuentes-Faura, Javier & Talbi, Besma & Sadiq, Muhammad & Si Mohammed, Kamel & Bashir, Muhammad Farhan, 2023. "Dynamic correlated effects of electricity prices, biomass energy, and technological innovation in Tunisia's energy transition," Utilities Policy, Elsevier, vol. 82(C).
    4. Carla Cristiane Sokulski & Murillo Vetroni Barros & Rodrigo Salvador & Evandro Eduardo Broday & Antonio Carlos de Francisco, 2022. "Trends in Renewable Electricity Generation in the G20 Countries: An Analysis of the 1990–2020 Period," Sustainability, MDPI, vol. 14(4), pages 1-21, February.

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    More about this item

    Keywords

    Renewable portfolio standard; Solar; Wind; Renewable generation; Stochastic frontier;
    All these keywords.

    JEL classification:

    • Q47 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy Forecasting
    • Q48 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Government Policy
    • Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters and their Management; Global Warming
    • H23 - Public Economics - - Taxation, Subsidies, and Revenue - - - Externalities; Redistributive Effects; Environmental Taxes and Subsidies
    • L94 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Electric Utilities

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