IDEAS home Printed from https://ideas.repec.org/a/eee/enepol/v109y2017icp270-278.html
   My bibliography  Save this article

When do households invest in solar photovoltaics? An application of prospect theory

Author

Listed:
  • Klein, Martin
  • Deissenroth, Marc

Abstract

While investments in renewable energy sources (RES) are incentivized around the world, the policy tools that do so are still poorly understood, leading to costly misadjustments in many cases. As a case study, the deployment dynamics of residential solar photovoltaics (PV) invoked by the German feed-in tariff legislation are investigated. Here we report a model showing that the question of when people invest in residential PV systems is found to be not only determined by profitability, but also by profitability's change compared to the status quo. This finding is interpreted in the light of loss aversion, a concept developed in Kahneman and Tversky's prospect theory. The model is able to reproduce most of the dynamics of the uptake with only a few financial and behavioral assumptions.

Suggested Citation

  • Klein, Martin & Deissenroth, Marc, 2017. "When do households invest in solar photovoltaics? An application of prospect theory," Energy Policy, Elsevier, vol. 109(C), pages 270-278.
    • Handle: RePEc:eee:enepol:v:109:y:2017:i:c:p:270-278
    DOI: 10.1016/j.enpol.2017.06.067
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0301421517304317
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.enpol.2017.06.067?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to look for a different version below or search for a different version of it.

    Other versions of this item:

    References listed on IDEAS

    as
    1. A. Hacura & M. Jadamus-Hacura & A. Kocot, 2001. "Risk analysis in investment appraisal based on the Monte Carlo simulation technique," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 20(4), pages 551-553, April.
    2. Frederick S. Hillier, 1963. "The Derivation of Probabilistic Information for the Evaluation of Risky Investments," Management Science, INFORMS, vol. 9(3), pages 443-457, April.
    3. 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.
    4. Salm, Sarah & Hille, Stefanie Lena & Wüstenhagen, Rolf, 2016. "What are retail investors' risk-return preferences towards renewable energy projects? A choice experiment in Germany," Energy Policy, Elsevier, vol. 97(C), pages 310-320.
    5. Luthander, Rasmus & Widén, Joakim & Nilsson, Daniel & Palm, Jenny, 2015. "Photovoltaic self-consumption in buildings: A review," Applied Energy, Elsevier, vol. 142(C), pages 80-94.
    6. Farmer, J. Doyne & Lafond, François, 2016. "How predictable is technological progress?," Research Policy, Elsevier, vol. 45(3), pages 647-665.
    7. Wand, Robert & Leuthold, Florian, 2011. "Feed-in tariffs for photovoltaics: Learning by doing in Germany?," Applied Energy, Elsevier, vol. 88(12), pages 4387-4399.
    8. Grau, Thilo, 2014. "Responsive feed-in tariff adjustment to dynamic technology development," Energy Economics, Elsevier, vol. 44(C), pages 36-46.
    9. Kwan, Calvin Lee, 2012. "Influence of local environmental, social, economic and political variables on the spatial distribution of residential solar PV arrays across the United States," Energy Policy, Elsevier, vol. 47(C), pages 332-344.
    10. Daniel Kahneman & Amos Tversky, 2013. "Prospect Theory: An Analysis of Decision Under Risk," World Scientific Book Chapters, in: Leonard C MacLean & William T Ziemba (ed.), HANDBOOK OF THE FUNDAMENTALS OF FINANCIAL DECISION MAKING Part I, chapter 6, pages 99-127, World Scientific Publishing Co. Pte. Ltd..
    11. Hoppmann, Joern & Volland, Jonas & Schmidt, Tobias S. & Hoffmann, Volker H., 2014. "The economic viability of battery storage for residential solar photovoltaic systems – A review and a simulation model," Renewable and Sustainable Energy Reviews, Elsevier, vol. 39(C), pages 1101-1118.
    12. Bauner, Christoph & Crago, Christine L., 2015. "Adoption of residential solar power under uncertainty: Implications for renewable energy incentives," Energy Policy, Elsevier, vol. 86(C), pages 27-35.
    13. Tversky, Amos & Kahneman, Daniel, 1992. "Advances in Prospect Theory: Cumulative Representation of Uncertainty," Journal of Risk and Uncertainty, Springer, vol. 5(4), pages 297-323, October.
    14. Zhang, M.M. & Zhou, D.Q. & Zhou, P. & Liu, G.Q., 2016. "Optimal feed-in tariff for solar photovoltaic power generation in China: A real options analysis," Energy Policy, Elsevier, vol. 97(C), pages 181-192.
    15. Amos Tversky & Daniel Kahneman, 1991. "Loss Aversion in Riskless Choice: A Reference-Dependent Model," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 106(4), pages 1039-1061.
    16. Seel, Joachim & Barbose, Galen L. & Wiser, Ryan H., 2014. "An analysis of residential PV system price differences between the United States and Germany," Energy Policy, Elsevier, vol. 69(C), pages 216-226.
    17. Palmer, J. & Sorda, G. & Madlener, R., 2015. "Modeling the diffusion of residential photovoltaic systems in Italy: An agent-based simulation," Technological Forecasting and Social Change, Elsevier, vol. 99(C), pages 106-131.
    18. Bryan Bollinger & Kenneth Gillingham, 2012. "Peer Effects in the Diffusion of Solar Photovoltaic Panels," Marketing Science, INFORMS, vol. 31(6), pages 900-912, November.
    19. Rode, Johannes & Weber, Alexander, 2016. "Does localized imitation drive technology adoption? A case study on rooftop photovoltaic systems in Germany," Journal of Environmental Economics and Management, Elsevier, vol. 78(C), pages 38-48.
    20. Ron Davis, 2008. "Teaching Note ---Teaching Project Simulation in Excel Using PERT- Beta Distributions," INFORMS Transactions on Education, INFORMS, vol. 8(3), pages 139-148, May.
    21. Hoppmann, Joern & Peters, Michael & Schneider, Malte & Hoffmann, Volker H., 2013. "The two faces of market support—How deployment policies affect technological exploration and exploitation in the solar photovoltaic industry," Research Policy, Elsevier, vol. 42(4), pages 989-1003.
    22. Michail Chronopoulos, Verena Hagspiel, and Stein-Erik Fleten, 2016. "Stepwise Green Investment under Policy Uncertainty," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4).
    23. Luthander, Rasmus & Widén, Joakim & Munkhammar, Joakim & Lingfors, David, 2016. "Self-consumption enhancement and peak shaving of residential photovoltaics using storage and curtailment," Energy, Elsevier, vol. 112(C), pages 221-231.
    24. Leepa, Claudia & Unfried, Matthias, 2013. "Effects of a cut-off in feed-in tariffs on photovoltaic capacity: Evidence fromGermany," Energy Policy, Elsevier, vol. 56(C), pages 536-542.
    25. Candelise, Chiara & Winskel, Mark & Gross, Robert J.K., 2013. "The dynamics of solar PV costs and prices as a challenge for technology forecasting," Renewable and Sustainable Energy Reviews, Elsevier, vol. 26(C), pages 96-107.
    26. Nicholas C. Barberis, 2013. "Thirty Years of Prospect Theory in Economics: A Review and Assessment," Journal of Economic Perspectives, American Economic Association, vol. 27(1), pages 173-196, Winter.
    27. Rode, Johannes & Weber, Alexander, 2016. "Does localized imitation drive technology adoption? A case study on rooftop photovoltaic systems in Germany," Journal of Environmental Economics and Management, Elsevier, vol. 78(C), pages 38-48.
    28. Korcaj, Liridon & Hahnel, Ulf J.J. & Spada, Hans, 2015. "Intentions to adopt photovoltaic systems depend on homeowners' expected personal gains and behavior of peers," Renewable Energy, Elsevier, vol. 75(C), pages 407-415.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Candas, Soner & Siala, Kais & Hamacher, Thomas, 2019. "Sociodynamic modeling of small-scale PV adoption and insights on future expansion without feed-in tariffs," Energy Policy, Elsevier, vol. 125(C), pages 521-536.
    2. Nuñez-Jimenez, Alejandro & Knoeri, Christof & Rottmann, Fabian & Hoffmann, Volker H., 2020. "The role of responsiveness in deployment policies: A quantitative, cross-country assessment using agent-based modelling," Applied Energy, Elsevier, vol. 275(C).
    3. Strupeit, Lars, 2017. "An innovation system perspective on the drivers of soft cost reduction for photovoltaic deployment: The case of Germany," Renewable and Sustainable Energy Reviews, Elsevier, vol. 77(C), pages 273-286.
    4. Sommerfeldt, Nelson & Madani, Hatef, 2017. "Revisiting the techno-economic analysis process for building-mounted, grid-connected solar photovoltaic systems: Part one – Review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 74(C), pages 1379-1393.
    5. Esplin, Ryan & Nelson, Tim, 2022. "Redirecting solar feed in tariffs to residential battery storage: Would it be worth it?," Economic Analysis and Policy, Elsevier, vol. 73(C), pages 373-389.
    6. Paul Simshauser & Tim Nelson & Joel Gilmore, 2022. "The sunshine state: implications from mass rooftop solar PV take-up rates in Queensland," Working Papers EPRG2219, Energy Policy Research Group, Cambridge Judge Business School, University of Cambridge.
    7. Collier, Samuel H.C. & House, Jo I. & Connor, Peter M. & Harris, Richard, 2023. "Distributed local energy: Assessing the determinants of domestic-scale solar photovoltaic uptake at the local level across England and Wales," Renewable and Sustainable Energy Reviews, Elsevier, vol. 171(C).
    8. 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.
    9. Fabian Scheller & Isabel Doser & Daniel Sloot & Russell McKenna & Thomas Bruckner, 2020. "Exploring the Role of Stakeholder Dynamics in Residential Photovoltaic Adoption Decisions: A Synthesis of the Literature," Energies, MDPI, vol. 13(23), pages 1-31, November.
    10. Stewart, Fraser, 2022. "Friends with benefits: How income and peer diffusion combine to create an inequality “trap” in the uptake of low-carbon technologies," Energy Policy, Elsevier, vol. 163(C).
    11. Jakusch, Sven Thorsten, 2017. "On the applicability of maximum likelihood methods: From experimental to financial data," SAFE Working Paper Series 148, Leibniz Institute for Financial Research SAFE, revised 2017.
    12. Mariya Burdina & Scott Hiller, 2021. "When Falling Just Short is a Good Thing: The Effect of Past Performance on Improvement," Journal of Sports Economics, , vol. 22(7), pages 777-798, October.
    13. Häckel, Björn & Pfosser, Stefan & Tränkler, Timm, 2017. "Explaining the energy efficiency gap - Expected Utility Theory versus Cumulative Prospect Theory," Energy Policy, Elsevier, vol. 111(C), pages 414-426.
    14. Edsel L. Beja, 2017. "The Asymmetric Effects of Macroeconomic Performance on Happiness: Evidence for the EU," Intereconomics: Review of European Economic Policy, Springer;ZBW - Leibniz Information Centre for Economics;Centre for European Policy Studies (CEPS), vol. 52(3), pages 184-190, May.
    15. Stefan Lamp, 2023. "Sunspots That Matter: The Effect of Weather on Solar Technology Adoption," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 84(4), pages 1179-1219, April.
    16. Moon-Hyun Kim & Tae-Hyoung Tommy Gim, 2021. "Spatial Characteristics of the Diffusion of Residential Solar Photovoltaics in Urban Areas: A Case of Seoul, South Korea," IJERPH, MDPI, vol. 18(2), pages 1-16, January.
    17. Giacoletti, Marco & Parsons, Christopher A., 2022. "Peak-Bust rental spreads," Journal of Financial Economics, Elsevier, vol. 143(1), pages 504-526.
    18. Aurélien Baillon & Han Bleichrodt & Vitalie Spinu, 2020. "Searching for the Reference Point," Management Science, INFORMS, vol. 66(1), pages 93-112, January.
    19. Gerda Ana Melnik-Leroy & Gintautas Dzemyda, 2021. "How to Influence the Results of MCDM?—Evidence of the Impact of Cognitive Biases," Mathematics, MDPI, vol. 9(2), pages 1-25, January.
    20. Wenhui Zhou & Dongmei Wang & Weixiang Huang & Pengfei Guo, 2021. "To Pool or Not to Pool? The Effect of Loss Aversion on Queue Configurations," Production and Operations Management, Production and Operations Management Society, vol. 30(11), pages 4258-4272, November.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:enepol:v:109:y:2017:i:c:p:270-278. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/enpol .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.