IDEAS home Printed from https://ideas.repec.org/p/ags/aaea13/150018.html
   My bibliography  Save this paper

Uncertainty in Renewable Energy Policy: How do Renewable Energy Credit markets and Production Tax Credits affect decisions to invest in renewable energy?

Author

Listed:
  • Eryilmaz, Derya
  • Homans, Frances

Abstract

This paper examines the impacts of uncertainties in the US renewable energy policy on the investment decisions of renewable electricity producers. We develop a dynamic optimization model to understand how investment in wind energy depends on market and policy uncertainties in renewable energy markets. These uncertainties include the stochastic prices in the market for Renewable Electricity Credits (RECs) and the federal government's uncertain decision about continuation of Production Tax Credit (PTC) program. Results contribute to our understanding of the impact of the REC market and policy decisions on the profitability threshold required for investors to commit to renewable energy investments. Uncertainty about the renewable energy policy raises the threshold to invest in renewable energy. This paper also examines the relationship between two important renewable energy policies and their impacts on these investments. This paper has the potential to significantly contribute to the existing renewable energy development debate because the RECs prices are introduced explicitly as a random factor in a model of investment in renewable energy.

Suggested Citation

  • Eryilmaz, Derya & Homans, Frances, 2013. "Uncertainty in Renewable Energy Policy: How do Renewable Energy Credit markets and Production Tax Credits affect decisions to invest in renewable energy?," 2013 Annual Meeting, August 4-6, 2013, Washington, D.C. 150018, Agricultural and Applied Economics Association.
    • Handle: RePEc:ags:aaea13:150018
    DOI: 10.22004/ag.econ.150018
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/150018/files/AAEA%20submissions.pdf
    Download Restriction: no
    File URL: https://libkey.io/10.22004/ag.econ.150018?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
    ---><---

    References listed on IDEAS

    as
    1. Robert S. Pindyck, 1984. "Uncertainty in the Theory of Renewable Resource Markets," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 51(2), pages 289-303.
    2. Ray C. Fair, 1993. "Estimating Event Probabilities from Macroeconometric Models Using Stochastic Simulation," NBER Chapters, in: Business Cycles, Indicators, and Forecasting, pages 157-178, National Bureau of Economic Research, Inc.
    3. Balikcioglu, Metin & Fackler, Paul L. & Pindyck, Robert S., 2011. "Solving optimal timing problems in environmental economics," Resource and Energy Economics, Elsevier, vol. 33(3), pages 761-768, September.
    4. Pindyck, Robert S, 1980. "Uncertainty and Exhaustible Resource Markets," Journal of Political Economy, University of Chicago Press, vol. 88(6), pages 1203-1225, December.
    5. Fuss, Sabine & Szolgayova, Jana & Obersteiner, Michael & Gusti, Mykola, 2008. "Investment under market and climate policy uncertainty," Applied Energy, Elsevier, vol. 85(8), pages 708-721, August.
    6. Fuss, Sabine & Szolgayová, Jana & Khabarov, Nikolay & Obersteiner, Michael, 2012. "Renewables and climate change mitigation: Irreversible energy investment under uncertainty and portfolio effects," Energy Policy, Elsevier, vol. 40(C), pages 59-68.
    7. Pindyck, Robert S, 1993. "A Note on Competitive Investment under Uncertainty," American Economic Review, American Economic Association, vol. 83(1), pages 273-277, March.
    8. Pindyck, Robert S., 2000. "Irreversibilities and the timing of environmental policy," Resource and Energy Economics, Elsevier, vol. 22(3), pages 233-259, July.
    9. James H. Stock & Mark W. Watson, 1993. "Business Cycles, Indicators, and Forecasting," NBER Books, National Bureau of Economic Research, Inc, number stoc93-1.
    10. Stock, James H. & Watson, Mark W. (ed.), 1993. "Business Cycles, Indicators, and Forecasting," National Bureau of Economic Research Books, University of Chicago Press, edition 1, number 9780226774886.
    11. Palmer, Karen & Burtraw, Dallas, 2005. "Cost-effectiveness of renewable electricity policies," Energy Economics, Elsevier, vol. 27(6), pages 873-894, November.
    12. Fell, Harrison & Linn, Joshua & Munnings, Clayton, 2012. "Designing Renewable Electricity Policies to Reduce Emissions," RFF Working Paper Series dp-12-54, Resources for the Future.
    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. Farid, Saqib & Zafar, Quratulain, 2024. "Impact of economic policy uncertainty on global carbon emissions," Research in Economics, Elsevier, vol. 78(2).

    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. Mosiño, Alejandro, 2012. "Producing energy in a stochastic environment: Switching from non-renewable to renewable resources," Resource and Energy Economics, Elsevier, vol. 34(4), pages 413-430.
    2. E. Agliardi & L. Sereno, 2012. "On the optimal timing of switching from non-renewable to renewable resources: dirty vs clean energy sources and the relative efficiency of generators," Working Papers wp855, Dipartimento Scienze Economiche, Universita' di Bologna.
    3. Dury, Karen & Pina, Alvaro M., 2003. "Fiscal policy in EMU: simulating the operation of the Stability Pact," Journal of Policy Modeling, Elsevier, vol. 25(2), pages 179-206, February.
    4. George Athanasopoulos & Heather M. Anderson & Farshid Vahid, 2007. "Nonlinear autoregressive leading indicator models of output in G-7 countries," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(1), pages 63-87.
    5. Carriero, Andrea & Marcellino, Massimiliano, 2007. "A comparison of methods for the construction of composite coincident and leading indexes for the UK," International Journal of Forecasting, Elsevier, vol. 23(2), pages 219-236.
    6. Dag Kolsrud, 2008. "Stochastic Ceteris Paribus Simulations," Computational Economics, Springer;Society for Computational Economics, vol. 31(1), pages 21-43, February.
    7. Duarte, Agustin & Venetis, Ioannis A. & Paya, Ivan, 2005. "Predicting real growth and the probability of recession in the Euro area using the yield spread," International Journal of Forecasting, Elsevier, vol. 21(2), pages 261-277.
    8. Urooj Khan & N. Bugra Ozel, 2016. "Real Activity Forecasts Using Loan Portfolio Information," Journal of Accounting Research, Wiley Blackwell, vol. 54(3), pages 895-937, June.
    9. Garratt, Anthony & Lee, Kevin C & Pesaran, M. Hashem & Shin, Yongcheol, 1998. "A Structural Cointegrating VAR Approach to Macroeconometric Modelling," Cambridge Working Papers in Economics 9823, Faculty of Economics, University of Cambridge.
    10. Ana Beatriz C. Galvão, 2006. "Structural break threshold VARs for predicting US recessions using the spread," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(4), pages 463-487, May.
    11. Debby Lanser & Henk Kranendonk, 2008. "Investigating uncertainty in macroeconomic forecasts by stochastic simulation," CPB Discussion Paper 112.rdf, CPB Netherlands Bureau for Economic Policy Analysis.
    12. Lopez, Jose A, 2001. "Evaluating the Predictive Accuracy of Volatility Models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 20(2), pages 87-109, March.
    13. Lazzarini, S. G. & Madalozzo, R. C & Artes, R. & Siqueira, J. O., 2004. "Measuring trust: An experiment in Brazil," Insper Working Papers wpe_42, Insper Working Paper, Insper Instituto de Ensino e Pesquisa.
    14. Tsur, Yacov & Zemel, Amos, 2012. "Dynamic and stochastic analysis of environmental and natural resources," Discussion Papers 120017, Hebrew University of Jerusalem, Department of Agricultural Economics and Management.
    15. Plantinga, Andrew J. & Provencher, Bill, 2001. "Internal Consistency In Models Of Optimal Resource Use Under Uncertainty," 2001 Annual meeting, August 5-8, Chicago, IL 20712, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    16. Quah, Danny, 1994. "One business cycle and one trend from (many,) many disaggregates," European Economic Review, Elsevier, vol. 38(3-4), pages 605-614, April.
    17. Ricardo Caballero & Arvind Krishnamurthy, 2005. "Financial System Risk and Flight to Quality," NBER Working Papers 11834, National Bureau of Economic Research, Inc.
    18. DAVID E. ALLEN & MICHAEL McALEER & ROBERT J. POWELL & ABHAY K. SINGH, 2018. "Non-Parametric Multiple Change Point Analysis Of The Global Financial Crisis," Annals of Financial Economics (AFE), World Scientific Publishing Co. Pte. Ltd., vol. 13(02), pages 1-23, June.
    19. Esther Fernández Galar & Javier Gómez Biscarri, 2003. "Revisiting the Ability of Interest Rate Spreads to Predict Recessions: Evidence for a," Faculty Working Papers 04/03, School of Economics and Business Administration, University of Navarra.
    20. Claessens, Stijn & Kose, M. Ayhan & Terrones, Marco E., 2012. "How do business and financial cycles interact?," Journal of International Economics, Elsevier, vol. 87(1), pages 178-190.

    More about this item

    Keywords

    Environmental Economics and Policy; Resource/Energy Economics and 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:ags:aaea13:150018. 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: AgEcon Search (email available below). General contact details of provider: https://edirc.repec.org/data/aaeaaea.html .

    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.