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PV adoption: the role of distribution tariffs under net metering

Author

Listed:
  • Axel Gautier

    (HEC Liege, LCII, University of Liege
    CORE, UCLouvain
    CESifo)

  • Julien Jacqmin

    (NEOMA Business School)

Abstract

The deployment of decentralized productions units (DPU) like rooftop solar panels is a major challenge for a transition towards greener energy sources. Under a net metering system where the meter runs backward when there is excessive PV production, the electricity produced by a solar panel is valued at the retail price. Higher retail prices thus encourage the deployment of DPU. To identify this relationship, we use data from Wallonia where tariffs are paid on a mostly volumetric base and where there are 13 different tariff zones. Using various specifications, our results suggest that in a municipality where the distribution tariff is one eurocent per kWh higher, the investment in solar PV is, all else equal, around 8% higher.

Suggested Citation

  • Axel Gautier & Julien Jacqmin, 2020. "PV adoption: the role of distribution tariffs under net metering," Journal of Regulatory Economics, Springer, vol. 57(1), pages 53-73, February.
    • Handle: RePEc:kap:regeco:v:57:y:2020:i:1:d:10.1007_s11149-019-09397-6
    DOI: 10.1007/s11149-019-09397-6
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    1. Axel Gautier & Julien Jacqmin & Jean-Christophe Poudou, 2018. "The prosumers and the grid," Journal of Regulatory Economics, Springer, vol. 53(1), pages 100-126, February.
    2. Crago, Christine Lasco & Chernyakhovskiy, Ilya, 2017. "Are policy incentives for solar power effective? Evidence from residential installations in the Northeast," Journal of Environmental Economics and Management, Elsevier, vol. 81(C), pages 132-151.
    3. Jean-Christophe Poudou & Axel Gautier & Julien Jacqmin, 2018. "The prosumers and the grid," Post-Print hal-01810028, HAL.
    4. Newell, Richard G. & Pizer, William A. & Raimi, Daniel, 2019. "U.S. federal government subsidies for clean energy: Design choices and implications," Energy Economics, Elsevier, vol. 80(C), pages 831-841.
    5. Houde, Sébastien & Myers, Erica, 2021. "Are consumers attentive to local energy costs? Evidence from the appliance market," Journal of Public Economics, Elsevier, vol. 201(C).
    6. Anderson, Soren T. & Kellogg, Ryan & Sallee, James M., 2013. "What do consumers believe about future gasoline prices?," Journal of Environmental Economics and Management, Elsevier, vol. 66(3), pages 383-403.
    7. 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.
    8. Jonathan E. Hughes & Molly Podolefsky, 2015. "Getting Green with Solar Subsidies: Evidence from the California Solar Initiative," Journal of the Association of Environmental and Resource Economists, University of Chicago Press, vol. 2(2), pages 235-275.
    9. Menz, Fredric C. & Vachon, Stephan, 2006. "The effectiveness of different policy regimes for promoting wind power: Experiences from the states," Energy Policy, Elsevier, vol. 34(14), pages 1786-1796, September.
    10. David P. Brown & David E. M. Sappington, 2017. "Optimal policies to promote efficient distributed generation of electricity," Journal of Regulatory Economics, Springer, vol. 52(2), pages 159-188, October.
    11. Vasseur, Véronique & Kemp, René, 2015. "The adoption of PV in the Netherlands: A statistical analysis of adoption factors," Renewable and Sustainable Energy Reviews, Elsevier, vol. 41(C), pages 483-494.
    12. Sven Müller & Johannes Rode, 2013. "The adoption of photovoltaic systems in Wiesbaden, Germany," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 22(5), pages 519-535, July.
    13. Olivier De Groote & Frank Verboven, 2019. "Subsidies and Time Discounting in New Technology Adoption: Evidence from Solar Photovoltaic Systems," American Economic Review, American Economic Association, vol. 109(6), pages 2137-2172, June.
    14. De Groote, Olivier & Pepermans, Guido & Verboven, Frank, 2016. "Heterogeneity in the adoption of photovoltaic systems in Flanders," Energy Economics, Elsevier, vol. 59(C), pages 45-57.
    15. Bryan Bollinger & Kenneth Gillingham, 2012. "Peer Effects in the Diffusion of Solar Photovoltaic Panels," Marketing Science, INFORMS, vol. 31(6), pages 900-912, November.
    16. Julien Jacqmin, 2018. "The role of market-oriented institutions in the deployment of renewable energies: evidences from Europe," Applied Economics, Taylor & Francis Journals, vol. 50(2), pages 202-215, January.
    17. Germeshausen, Robert, 2016. "Effects of Attribute-Based Regulation on Technology Adoption - The Case of Feed-In Tariffs for Solar Photovoltaic," VfS Annual Conference 2016 (Augsburg): Demographic Change 145712, Verein für Socialpolitik / German Economic Association.
    18. Hinz, Fabian & Schmidt, Matthew & Möst, Dominik, 2018. "Regional distribution effects of different electricity network tariff designs with a distributed generation structure: The case of Germany," Energy Policy, Elsevier, vol. 113(C), pages 97-111.
    19. Wooldridge, Jeffrey M., 1999. "Distribution-free estimation of some nonlinear panel data models," Journal of Econometrics, Elsevier, vol. 90(1), pages 77-97, May.
    20. Jacksohn, Anke & Grösche, Peter & Rehdanz, Katrin & Schröder, Carsten, 2019. "Drivers of renewable technology adoption in the household sector," Energy Economics, Elsevier, vol. 81(C), pages 216-226.
    21. Darghouth, Naïm R. & Wiser, Ryan H. & Barbose, Galen & Mills, Andrew D., 2016. "Net metering and market feedback loops: Exploring the impact of retail rate design on distributed PV deployment," Applied Energy, Elsevier, vol. 162(C), pages 713-722.
    22. Jacobsen, Grant D., 2015. "Do energy prices influence investment in energy efficiency? Evidence from energy star appliances," Journal of Environmental Economics and Management, Elsevier, vol. 74(C), pages 94-106.
    23. repec:aen:journl:ej38-3-brown is not listed on IDEAS
    24. Matisoff, Daniel C. & Johnson, Erik P., 2017. "The comparative effectiveness of residential solar incentives," Energy Policy, Elsevier, vol. 108(C), pages 44-54.
    25. Cai, Desmond W.H. & Adlakha, Sachin & Low, Steven H. & De Martini, Paul & Mani Chandy, K., 2013. "Impact of residential PV adoption on Retail Electricity Rates," Energy Policy, Elsevier, vol. 62(C), pages 830-843.
    26. Ross Baldick, 2018. "Incentive properties of coincident peak pricing," Journal of Regulatory Economics, Springer, vol. 54(2), pages 165-194, October.
    27. Koichiro Ito, 2014. "Do Consumers Respond to Marginal or Average Price? Evidence from Nonlinear Electricity Pricing," American Economic Review, American Economic Association, vol. 104(2), pages 537-563, February.
    28. Schittekatte, Tim & Momber, Ilan & Meeus, Leonardo, 2018. "Future-proof tariff design: Recovering sunk grid costs in a world where consumers are pushing back," Energy Economics, Elsevier, vol. 70(C), pages 484-498.
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    JEL classification:

    • Q42 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Alternative Energy Sources
    • L51 - Industrial Organization - - Regulation and Industrial Policy - - - Economics of Regulation
    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis

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