IDEAS home Printed from https://ideas.repec.org/p/cpr/ceprdp/11438.html
   My bibliography  Save this paper

Subsidies and Myopia in Technology Adoption: Evidence from Solar Photovoltaic Systems

Author

Listed:
  • Verboven, Frank
  • De Groote, Olivier

Abstract

Many countries have relied on subsidies to promote the adoption of renewable energy technologies. We study a generous program to promote the adoption of solar photovoltaic (PV) systems through subsidies on future electricity production, rather than through upfront investment subsidies. We develop and estimate a tractable dynamic model of technology adoption, also accounting for local market heterogeneity. We exploit rich variation at pre-announced dates in the future production subsidies. Although the program led to a massive adoption, we find that households significantly undervalued the future benefits from the new technology. This implies that an upfront investment subsidy program would have promoted the technology at a much lower budgetary cost, so that the government essentially shifted the subsidy burden to future generations of electricity consumers.

Suggested Citation

  • Verboven, Frank & De Groote, Olivier, 2016. "Subsidies and Myopia in Technology Adoption: Evidence from Solar Photovoltaic Systems," CEPR Discussion Papers 11438, C.E.P.R. Discussion Papers.
  • Handle: RePEc:cpr:ceprdp:11438
    as

    Download full text from publisher

    File URL: https://cepr.org/publications/DP11438
    Download Restriction: CEPR Discussion Papers are free to download for our researchers, subscribers and members. If you fall into one of these categories but have trouble downloading our papers, please contact us at subscribers@cepr.org
    ---><---

    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. Gautam Gowrisankaran & Marc Rysman, 2012. "Dynamics of Consumer Demand for New Durable Goods," Journal of Political Economy, University of Chicago Press, vol. 120(6), pages 1173-1219.
    2. Rust, John, 1987. "Optimal Replacement of GMC Bus Engines: An Empirical Model of Harold Zurcher," Econometrica, Econometric Society, vol. 55(5), pages 999-1033, September.
    3. Reynaert, Mathias & Verboven, Frank, 2014. "Improving the performance of random coefficients demand models: The role of optimal instruments," Journal of Econometrics, Elsevier, vol. 179(1), pages 83-98.
    4. Meghan R. Busse & Christopher R. Knittel & Florian Zettelmeyer, 2013. "Are Consumers Myopic? Evidence from New and Used Car Purchases," American Economic Review, American Economic Association, vol. 103(1), pages 220-256, February.
    5. Thierry Magnac & David Thesmar, 2002. "Identifying Dynamic Discrete Decision Processes," Econometrica, Econometric Society, vol. 70(2), pages 801-816, March.
    6. James Levinsohn & Steven Berry & Ariel Pakes, 1999. "Voluntary Export Restraints on Automobiles: Evaluating a Trade Policy," American Economic Review, American Economic Association, vol. 89(3), pages 400-430, June.
    7. Steven Berry & James Levinsohn & Ariel Pakes, 2004. "Differentiated Products Demand Systems from a Combination of Micro and Macro Data: The New Car Market," Journal of Political Economy, University of Chicago Press, vol. 112(1), pages 68-105, February.
    8. Hunt Allcott & Michael Greenstone, 2012. "Is There an Energy Efficiency Gap?," Journal of Economic Perspectives, American Economic Association, vol. 26(1), pages 3-28, Winter.
    9. Hunt Allcott & Nathan Wozny, 2014. "Gasoline Prices, Fuel Economy, and the Energy Paradox," The Review of Economics and Statistics, MIT Press, vol. 96(5), pages 779-795, December.
    10. Brian C. Murray & Maureen L. Cropper & Francisco C. de la Chesnaye & John M. Reilly, 2014. "How Effective Are US Renewable Energy Subsidies in Cutting Greenhouse Gases?," American Economic Review, American Economic Association, vol. 104(5), pages 569-574, May.
    11. Laura Nurski & Frank Verboven, 2016. "Exclusive Dealing as a Barrier to Entry? Evidence from Automobiles," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 83(3), pages 1156-1188.
    12. Peter Arcidiacono & Robert A. Miller, 2011. "Conditional Choice Probability Estimation of Dynamic Discrete Choice Models With Unobserved Heterogeneity," Econometrica, Econometric Society, vol. 79(6), pages 1823-1867, November.
    13. Oleg Melnikov, 2013. "Demand For Differentiated Durable Products: The Case Of The U.S. Computer Printer Market," Economic Inquiry, Western Economic Association International, vol. 51(2), pages 1277-1298, April.
    14. Bryan Bollinger, 2015. "Green technology adoption: An empirical study of the Southern California garment cleaning industry," Quantitative Marketing and Economics (QME), Springer, vol. 13(4), pages 319-358, December.
    15. Steven T. Berry, 1994. "Estimating Discrete-Choice Models of Product Differentiation," RAND Journal of Economics, The RAND Corporation, vol. 25(2), pages 242-262, Summer.
    16. Audenaert, Amaryllis & De Boeck, Liesje & De Cleyn, Sven & Lizin, Sebastien & Adam, Jean-François, 2010. "An economic evaluation of photovoltaic grid connected systems (PVGCS) in Flanders for companies: A generic model," Renewable Energy, Elsevier, vol. 35(12), pages 2674-2682.
    17. Jean-Pierre H. Dube & Günter J. Hitsch & Pranav Jindal, 2012. "The Joint Identification of Utility and Discount Functions From Stated Choice Data: An Application to Durable Goods Adoption," NBER Working Papers 18393, National Bureau of Economic Research, Inc.
    18. Robin S. Lee, 2013. "Vertical Integration and Exclusivity in Platform and Two-Sided Markets," American Economic Review, American Economic Association, vol. 103(7), pages 2960-3000, December.
    19. 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.
    20. Bryan Bollinger, 2015. "Green technology adoption: An empirical study of the Southern California garment cleaning industry," Quantitative Marketing and Economics (QME), Springer, vol. 13(4), pages 319-358, December.
    21. 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.
    22. Audenaert, Amaryllis & De Boeck, Liesje & De Cleyn, Sven & Lizin, Sebastien & Adam, Jean-Franois, 2010. "An economic evaluation of photovoltaic grid connected systems (PVGCS) in Flanders for companies: a generic model," Working Papers 2010/16, Hogeschool-Universiteit Brussel, Faculteit Economie en Management.
    23. Peter Arcidiacono & Paul B. Ellickson, 2011. "Practical Methods for Estimation of Dynamic Discrete Choice Models," Annual Review of Economics, Annual Reviews, vol. 3(1), pages 363-394, September.
    24. Manski, Charles F., 1993. "Dynamic choice in social settings : Learning from the experiences of others," Journal of Econometrics, Elsevier, vol. 58(1-2), pages 121-136, July.
    25. Frank Verboven, 2002. "Quality-Based Price Discrimination and Tax Incidence: Evidence from Gasoline and Diesel Cars," RAND Journal of Economics, The RAND Corporation, vol. 33(2), pages 275-297, Summer.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Pavanini, Nicola & Feger, Fabian & Radulescu, Doina, 2017. "Welfare and Redistribution in Residential Electricity Markets with Solar Power," CEPR Discussion Papers 12517, C.E.P.R. Discussion Papers.
    2. Buchheim, Lukas & Watzinger, Martin & Wilhelm, Matthias, 2020. "Job creation in tight and slack labor markets," Journal of Monetary Economics, Elsevier, vol. 114(C), pages 126-143.
    3. 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.
    4. Rebecca Diamond & Tim McQuade & Franklin Qian, 2019. "The Effects of Rent Control Expansion on Tenants, Landlords, and Inequality: Evidence from San Francisco," American Economic Review, American Economic Association, vol. 109(9), pages 3365-3394, September.
    5. Valentin Bertsch & Valeria Di Cosmo, 2018. "Are Renewables Profitable in 2030? A Comparison between Wind and Solar across Europe," Working Papers 2018.28, Fondazione Eni Enrico Mattei.
    6. Øystein Daljord & Denis Nekipelov & Minjung Park, 2019. "Comments on “identification and semiparametric estimation of a finite horizon dynamic discrete choice model with a terminating action”," Quantitative Marketing and Economics (QME), Springer, vol. 17(4), pages 439-449, December.
    7. He, Chen & Klein, Tobias, 2018. "Advertising as a Reminder : Evidence from the Dutch State Lottery," Other publications TiSEM 0791692c-433c-4e8d-8374-a, Tilburg University, School of Economics and Management.
    8. He, Chen, 2018. "Essays on the role and effects of advertising," Other publications TiSEM 47a3272a-54f1-4a90-9714-c, Tilburg University, School of Economics and Management.
    9. Kalouptsidi, Myrto & Scott, Paul T. & Souza-Rodrigues, Eduardo, 2018. "Linear IV Regression Estimators for Structural Dynamic Discrete Choice Models," CEPR Discussion Papers 13240, C.E.P.R. Discussion Papers.
    10. Myrto Kalouptsidi & Paul T. Scott & Eduardo Souza-Rodrigues, 2018. "Linear IV Regression Estimators for Structural Dynamic Discrete Choice Models," NBER Working Papers 25134, National Bureau of Economic Research, Inc.
    11. Sébastien Houde & Joseph E. Aldy, 2017. "The Efficiency Consequences of Heterogeneous Behavioral Responses to Energy Fiscal Policies," NBER Working Papers 24103, National Bureau of Economic Research, Inc.
    12. Houde, Sebastien & Aldy, Joseph E., 2017. "The Efficiency Consequences of Heterogeneous Behavioral Responses to Energy Fiscal Policies," RFF Working Paper Series 17-24, Resources for the Future.
    13. Best, Rohan & Trück, Stefan, 2020. "Capital and policy impacts on Australian small-scale solar installations," Energy Policy, Elsevier, vol. 136(C).
    14. Bertsch, Valentin & Di Cosmo, Valeria, 2020. "Are renewables profitable in 2030 and do they reduce carbon emissions effectively? A comparison across Europe," MPRA Paper 101822, University Library of Munich, Germany.

    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. 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.
    2. Kalouptsidi, Myrto & Scott, Paul T. & Souza-Rodrigues, Eduardo, 2021. "Linear IV regression estimators for structural dynamic discrete choice models," Journal of Econometrics, Elsevier, vol. 222(1), pages 778-804.
    3. Gautam Gowrisankaran & Marc Rysman, 2012. "Dynamics of Consumer Demand for New Durable Goods," Journal of Political Economy, University of Chicago Press, vol. 120(6), pages 1173-1219.
    4. Myrto Kalouptsidi & Paul T. Scott & Eduardo Souza-Rodrigues, 2018. "Linear IV Regression Estimators for Structural Dynamic Discrete Choice Models," NBER Working Papers 25134, National Bureau of Economic Research, Inc.
    5. Masakazu Ishihara & Andrew T. Ching, 2019. "Dynamic Demand for New and Used Durable Goods Without Physical Depreciation: The Case of Japanese Video Games," Marketing Science, INFORMS, vol. 38(3), pages 392-416, May.
    6. Verboven, Frank & Grigolon, Laura & Reynaert, Mathias, 2014. "Consumer valuation of fuel costs and the effectiveness of tax policy: Evidence from the European car market," CEPR Discussion Papers 10301, C.E.P.R. Discussion Papers.
    7. Sun, Yutec & Ishihara, Masakazu, 2019. "A computationally efficient fixed point approach to dynamic structural demand estimation," Journal of Econometrics, Elsevier, vol. 208(2), pages 563-584.
    8. Arakawa, Kiyoshi, 2022. "Assessing consumer valuations of future costs versus purchase prices in Japan's auto market," Economics of Transportation, Elsevier, vol. 30(C).
    9. Kalouptsidi, Myrto & Scott, Paul T. & Souza-Rodrigues, Eduardo, 2018. "Linear IV Regression Estimators for Structural Dynamic Discrete Choice Models," CEPR Discussion Papers 13240, C.E.P.R. Discussion Papers.
    10. Todd D. Gerarden & Richard G. Newell & Robert N. Stavins, 2017. "Assessing the Energy-Efficiency Gap," Journal of Economic Literature, American Economic Association, vol. 55(4), pages 1486-1525, December.
    11. Chun‐Yu Ho, 2015. "Switching Cost And Deposit Demand In China," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 56(3), pages 723-749, August.
    12. Donna, Javier D., 2018. "Measuring Long-Run Price Elasticities in Urban Travel Demand," MPRA Paper 90059, University Library of Munich, Germany.
    13. Yufeng Huang, 2022. "Tied Goods and Consumer Switching Costs," Marketing Science, INFORMS, vol. 41(1), pages 93-114, January.
    14. Victor Aguirregabiria & Margaret Slade, 2017. "Empirical models of firms and industries," Canadian Journal of Economics, Canadian Economics Association, vol. 50(5), pages 1445-1488, December.
    15. Joseph Cullen & Nicolas Schutz & Oleksandr Shcherbakov, 2020. "The Welfare Effects of Early Termination Fees in the US Wireless Industry," CRC TR 224 Discussion Paper Series crctr224_2020_247, University of Bonn and University of Mannheim, Germany.
    16. Cohen, François & Glachant, Matthieu & Söderberg, Magnus, 2017. "Consumer myopia, imperfect competition and the energy efficiency gap: Evidence from the UK refrigerator market," European Economic Review, Elsevier, vol. 93(C), pages 1-23.
    17. Rambha, Tarun & Nozick, Linda K. & Davidson, Rachel, 2021. "Modeling hurricane evacuation behavior using a dynamic discrete choice framework," Transportation Research Part B: Methodological, Elsevier, vol. 150(C), pages 75-100.
    18. Cheng Chou & Tim Derdenger & Vineet Kumar, 2019. "Linear Estimation of Aggregate Dynamic Discrete Demand for Durable Goods: Overcoming the Curse of Dimensionality," Marketing Science, INFORMS, vol. 38(5), pages 888-909, September.
    19. Jaap H. Abbring & Øystein Daljord, 2020. "Identifying the discount factor in dynamic discrete choice models," Quantitative Economics, Econometric Society, vol. 11(2), pages 471-501, May.
    20. An, Yonghong & Hu, Yingyao & Xiao, Ruli, 2021. "Dynamic decisions under subjective expectations: A structural analysis," Journal of Econometrics, Elsevier, vol. 222(1), pages 645-675.

    More about this item

    Keywords

    Renewable energy technologies; Dynamic discrete choice; Myopia;
    All these keywords.

    JEL classification:

    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • Q48 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Government Policy
    • Q58 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Environmental Economics: Government Policy

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    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:cpr:ceprdp:11438. 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: the person in charge (email available below). General contact details of provider: https://www.cepr.org .

    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.