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Subsidies and myopia in technology adoption: evidence from solar photovoltaic systems

Author

Listed:
  • Olivier De Groote
  • Frank Verboven
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

  • Olivier De Groote & Frank Verboven, 2016. "Subsidies and myopia in technology adoption: evidence from solar photovoltaic systems," Working Papers of Department of Economics, Leuven 547933, KU Leuven, Faculty of Economics and Business (FEB), Department of Economics, Leuven.
    • Handle: RePEc:ete:ceswps:547933
    Note: paper number DPS 15.16
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    References listed on IDEAS

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    Cited by:

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    4. 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.
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    6. 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.
    7. Sebastien Houde & Joseph E. Aldy, 2017. "The Efficiency Consequences of Heterogeneous Behavioral Responses to Energy Fiscal Policies," CER-ETH Economics working paper series 17/282, CER-ETH - Center of Economic Research (CER-ETH) at ETH Zurich.
    8. 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.
    9. Best, Rohan & Trück, Stefan, 2020. "Capital and policy impacts on Australian small-scale solar installations," Energy Policy, Elsevier, vol. 136(C).
    10. 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.
    11. 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.
    12. 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.
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    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.

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    More about this item

    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

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