IDEAS home Printed from https://ideas.repec.org/a/eee/enepol/v106y2017icp129-137.html
   My bibliography  Save this article

A dynamic approach to environmental compliance decisions in U.S. Electricity Market: The Acid Rain Program revisited

Author

Listed:
  • Hancevic, Pedro Ignacio

Abstract

The Acid Rain Program (ARP) was implemented in 1995. Since then, coal-fired boilers have had to choose among three main compliance alternatives: purchase pollution permits; switch to an alternative lower-sulfur coal; or adopt a scrubber. This decision problem is driven by the evolution of several economic variables and is revised when significant changes (to prices, quality of inputs, output level, technology, transport costs, regulations, among others) occur. Using a structural dynamic discrete choice model, I recover cost parameters and use them to evaluate two different counterfactual policies. The results confirm there is a trade-off between fuel switching and scrubbing costs (with the latter having a higher investment cost and a lower variable cost), and also the existence of regional heterogeneity. Finally, the ARP implied cost savings of approximately $4.7 billions if compared to a uniform emission rate standard and $14.8 billions if compared to compulsory scrubbing for the 1995–2005 period.

Suggested Citation

  • Hancevic, Pedro Ignacio, 2017. "A dynamic approach to environmental compliance decisions in U.S. Electricity Market: The Acid Rain Program revisited," Energy Policy, Elsevier, vol. 106(C), pages 129-137.
  • Handle: RePEc:eee:enepol:v:106:y:2017:i:c:p:129-137
    DOI: 10.1016/j.enpol.2017.03.050
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0301421517301957
    Download Restriction: Full text for ScienceDirect subscribers only

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

    References listed on IDEAS

    as
    1. 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.
    2. Mortensen, Dale & Pissarides, Christopher, 2011. "Job Creation and Job Destruction in the Theory of Unemployment," Economic Policy, Russian Presidential Academy of National Economy and Public Administration, vol. 1, pages 1-19.
    3. Aguirregabiria, Victor & Mira, Pedro, 2010. "Dynamic discrete choice structural models: A survey," Journal of Econometrics, Elsevier, vol. 156(1), pages 38-67, May.
    4. Curtis Carlson & Dallas Burtraw & Maureen Cropper & Karen L. Palmer, 2000. "Sulfur Dioxide Control by Electric Utilities: What Are the Gains from Trade?," Journal of Political Economy, University of Chicago Press, vol. 108(6), pages 1292-1326, December.
    5. Victor Aguirregabiria & Pedro Mira, 2002. "Swapping the Nested Fixed Point Algorithm: A Class of Estimators for Discrete Markov Decision Models," Econometrica, Econometric Society, vol. 70(4), pages 1519-1543, July.
    6. John R. Swinton, 2002. "The Potential for Cost Savings in the Sulfur Dioxide Allowance Market: Empirical Evidence from Florida," Land Economics, University of Wisconsin Press, vol. 78(3), pages 390-404.
    7. Canova, Fabio & Ciccarelli, Matteo, 2013. "Panel Vector Autoregressive Models: A Survey," CEPR Discussion Papers 9380, C.E.P.R. Discussion Papers.
    8. V. Joseph Hotz & Robert A. Miller, 1993. "Conditional Choice Probabilities and the Estimation of Dynamic Models," Review of Economic Studies, Oxford University Press, vol. 60(3), pages 497-529.
    9. Richard Schmalensee & Robert N. Stavins, 2013. "The SO 2 Allowance Trading System: The Ironic History of a Grand Policy Experiment," Journal of Economic Perspectives, American Economic Association, vol. 27(1), pages 103-122, Winter.
    10. Tauchen, George, 1986. "Finite state markov-chain approximations to univariate and vector autoregressions," Economics Letters, Elsevier, vol. 20(2), pages 177-181.
    11. Bellas, Allen S., 1998. "Empirical evidence of advances in scrubber technology," Resource and Energy Economics, Elsevier, vol. 20(4), pages 327-343, December.
    12. Holtz-Eakin, Douglas & Newey, Whitney & Rosen, Harvey S, 1988. "Estimating Vector Autoregressions with Panel Data," Econometrica, Econometric Society, vol. 56(6), pages 1371-1395, November.
    13. Richard Ericson & Ariel Pakes, 1995. "Markov-Perfect Industry Dynamics: A Framework for Empirical Work," Review of Economic Studies, Oxford University Press, vol. 62(1), pages 53-82.
    14. Michael P. Keane & Kenneth I. Wolpin, 2009. "Empirical Applications of Discrete Choice Dynamic Programming Models," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 12(1), pages 1-22, January.
    15. Rothwell, Geoffrey & Rust, John, 1997. "On the Optimal Lifetime of Nuclear Power Plants," Journal of Business & Economic Statistics, American Statistical Association, vol. 15(2), pages 195-208, April.
    16. Elaine F. Frey, 2013. "Technology Diffusion and Environmental Regulation: The Adoption of Scrubbers by Coal-Fired Power Plants," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1).
    17. Zvi Eckstein & Kenneth I. Wolpin, 1989. "The Specification and Estimation of Dynamic Stochastic Discrete Choice Models: A Survey," Journal of Human Resources, University of Wisconsin Press, vol. 24(4), pages 562-598.
    18. 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.
    19. Joskow, Paul L & Schmalensee, Richard & Bailey, Elizabeth M, 1998. "The Market for Sulfur Dioxide Emissions," American Economic Review, American Economic Association, vol. 88(4), pages 669-685, September.
    20. Rust, John, 1996. "Numerical dynamic programming in economics," Handbook of Computational Economics, in: H. M. Amman & D. A. Kendrick & J. Rust (ed.), Handbook of Computational Economics, edition 1, volume 1, chapter 14, pages 619-729, Elsevier.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

    Scrubbers; Fuel switching; Coal-fired boilers; Sulfur dioxide emissions; Dynamic discrete choice;

    JEL classification:

    • L94 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Electric Utilities
    • D92 - Microeconomics - - Micro-Based Behavioral Economics - - - Intertemporal Firm Choice, Investment, Capacity, and Financing
    • Q52 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Pollution Control Adoption and Costs; Distributional Effects; Employment Effects

    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:eee:enepol:v:106:y:2017:i:c:p:129-137. See general information about how to correct material in RePEc.

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

    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 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.