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A nonparametric method to estimate a technical change effect on marginal abatement costs of U.S. coal power plants

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  • Mekaroonreung, Maethee
  • Johnson, Andrew L.

Abstract

The literature usually assumes that technical change reduces marginal abatement cost; however, recent results suggest that precisely the opposite occurs. This paper proposes a nonparametric method to determine the effect of technical change on marginal abatement cost. The method decomposes NOx marginal abatement cost changes in 2000–2004 and in 2004–2008 for 325 boilers operating in 134 U.S. bituminous coal power plant into technical and non-technical change effects. We find that technical change reduces the NOx marginal cost about 28.3% in 2000–2004 and 26.5% in 2004–2008. However, more stringent regulations enacted the NOx budget program results in lower NOx emission levels as plant operators install more advanced NOx abatement equipment which in turn causes an overall increase in marginal abatement cost.

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  • Mekaroonreung, Maethee & Johnson, Andrew L., 2014. "A nonparametric method to estimate a technical change effect on marginal abatement costs of U.S. coal power plants," Energy Economics, Elsevier, vol. 46(C), pages 45-55.
    • Handle: RePEc:eee:eneeco:v:46:y:2014:i:c:p:45-55
    DOI: 10.1016/j.eneco.2014.08.027
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    1. Ray, Subhash C & Desli, Evangelia, 1997. "Productivity Growth, Technical Progress, and Efficiency Change in Industrialized Countries: Comment," American Economic Review, American Economic Association, vol. 87(5), pages 1033-1039, December.
    2. Robert M. Solow, 1956. "A Contribution to the Theory of Economic Growth," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 70(1), pages 65-94.
    3. Afriat, Sidney N, 1972. "Efficiency Estimation of Production Function," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 13(3), pages 568-598, October.
    4. Henry Tulkens & Philippe Eeckaut, 2006. "Nonparametric Efficiency, Progress and Regress Measures For Panel Data: Methodological Aspects," Springer Books, in: Parkash Chander & Jacques Drèze & C. Knox Lovell & Jack Mintz (ed.), Public goods, environmental externalities and fiscal competition, chapter 0, pages 395-429, Springer.
    5. Timo Kuosmanen & Mogens Fosgerau, 2009. "Neoclassical versus Frontier Production Models? Testing for the Skewness of Regression Residuals," Scandinavian Journal of Economics, Wiley Blackwell, vol. 111(2), pages 351-367, June.
    6. Pasurka, Carl Jr., 2006. "Decomposing electric power plant emissions within a joint production framework," Energy Economics, Elsevier, vol. 28(1), pages 26-43, January.
    7. Joe Zhu, 2014. "Data Envelopment Analysis," International Series in Operations Research & Management Science, in: Quantitative Models for Performance Evaluation and Benchmarking, edition 3, chapter 1, pages 1-9, Springer.
    8. Victoria Shestalova, 2003. "Sequential Malmquist Indices of Productivity Growth: An Application to OECD Industrial Activities," Journal of Productivity Analysis, Springer, vol. 19(2), pages 211-226, April.
    9. Rolf Färe & Shawna Grosskopf & Carl A. Pasurka & William L. Weber, 2012. "Substitutability among undesirable outputs," Applied Economics, Taylor & Francis Journals, vol. 44(1), pages 39-47, January.
    10. Bert Balk, 2001. "Scale Efficiency and Productivity Change," Journal of Productivity Analysis, Springer, vol. 15(3), pages 159-183, May.
    11. Johnson, Andrew L. & Kuosmanen, Timo, 2012. "One-stage and two-stage DEA estimation of the effects of contextual variables," European Journal of Operational Research, Elsevier, vol. 220(2), pages 559-570.
    12. Charnes, A. & Cooper, W. W. & Golany, B. & Seiford, L. & Stutz, J., 1985. "Foundations of data envelopment analysis for Pareto-Koopmans efficient empirical production functions," Journal of Econometrics, Elsevier, vol. 30(1-2), pages 91-107.
    13. E. Grifell-Tatjé & C. A. K. Lovell, 1999. "Profits and Productivity," Management Science, INFORMS, vol. 45(9), pages 1177-1193, September.
    14. Dan Rosen & Claire Schaffnit & Joseph Paradi, 1998. "Marginal Rates and Two-dimensional Level Curves in DEA," Journal of Productivity Analysis, Springer, vol. 9(3), pages 205-232, March.
    15. Baker, Erin & Clarke, Leon & Shittu, Ekundayo, 2008. "Technical change and the marginal cost of abatement," Energy Economics, Elsevier, vol. 30(6), pages 2799-2816, November.
    16. Milliman, Scott R. & Prince, Raymond, 1989. "Firm incentives to promote technological change in pollution control," Journal of Environmental Economics and Management, Elsevier, vol. 17(3), pages 247-265, November.
    17. Bramoulle, Yann & Olson, Lars J., 2005. "Allocation of pollution abatement under learning by doing," Journal of Public Economics, Elsevier, vol. 89(9-10), pages 1935-1960, September.
    18. Rosendahl, Knut Einar, 2004. "Cost-effective environmental policy: implications of induced technological change," Journal of Environmental Economics and Management, Elsevier, vol. 48(3), pages 1099-1121, November.
    19. Lee, Chia-Yen & Johnson, Andrew L. & Moreno-Centeno, Erick & Kuosmanen, Timo, 2013. "A more efficient algorithm for Convex Nonparametric Least Squares," European Journal of Operational Research, Elsevier, vol. 227(2), pages 391-400.
    20. Andrew Johnson & Timo Kuosmanen, 2011. "One-stage estimation of the effects of operational conditions and practices on productive performance: asymptotically normal and efficient, root-n consistent StoNEZD method," Journal of Productivity Analysis, Springer, vol. 36(2), pages 219-230, October.
    21. Timo Kuosmanen, 2008. "Representation theorem for convex nonparametric least squares," Econometrics Journal, Royal Economic Society, vol. 11(2), pages 308-325, July.
    22. Fischer, Carolyn & Parry, Ian W. H. & Pizer, William A., 2003. "Instrument choice for environmental protection when technological innovation is endogenous," Journal of Environmental Economics and Management, Elsevier, vol. 45(3), pages 523-545, May.
    23. Färe, Rolf & Grosskopf, Shawna & Pasurka, Carl Jr., 2010. "Toxic releases: An environmental performance index for coal-fired power plants," Energy Economics, Elsevier, vol. 32(1), pages 158-165, January.
    24. Färe, Rolf & Grosskopf, Shawna & Pasurka, Carl A., 2014. "Potential gains from trading bad outputs: The case of U.S. electric power plants," Resource and Energy Economics, Elsevier, vol. 36(1), pages 99-112.
    25. Fare, Rolf & Grosskopf, Shawna & Noh, Dong-Woon & Weber, William, 2005. "Characteristics of a polluting technology: theory and practice," Journal of Econometrics, Elsevier, vol. 126(2), pages 469-492, June.
    26. Timo Kuosmanen & Andrew L. Johnson, 2010. "Data Envelopment Analysis as Nonparametric Least-Squares Regression," Operations Research, INFORMS, vol. 58(1), pages 149-160, February.
    27. Ray, Subhash C & Mukherjee, Kankana, 1996. "Decomposition of the Fisher Ideal Index of Productivity: A Non-parametric Dual Analysis of US Airlines Data," Economic Journal, Royal Economic Society, vol. 106(439), pages 1659-1678, November.
    28. Rolf Färe & Shawna Grosskopf & Carl Pasurka, 2006. "Social responsibility: U.S. power plants 1985–1998," Journal of Productivity Analysis, Springer, vol. 26(3), pages 259-267, December.
    29. Fare, Rolf & Grosskopf, Shawna & Pasurka, Carl Jr., 2007. "Pollution abatement activities and traditional productivity," Ecological Economics, Elsevier, vol. 62(3-4), pages 673-682, May.
    30. Michael E. Porter & Claas van der Linde, 1995. "Toward a New Conception of the Environment-Competitiveness Relationship," Journal of Economic Perspectives, American Economic Association, vol. 9(4), pages 97-118, Fall.
    31. Vijay, Samudra & DeCarolis, Joseph F. & Srivastava, Ravi K., 2010. "A bottom-up method to develop pollution abatement cost curves for coal-fired utility boilers," Energy Policy, Elsevier, vol. 38(5), pages 2255-2261, May.
    32. Mekaroonreung, Maethee & Johnson, Andrew L., 2012. "Estimating the shadow prices of SO2 and NOx for U.S. coal power plants: A convex nonparametric least squares approach," Energy Economics, Elsevier, vol. 34(3), pages 723-732.
    33. Timo Kuosmanen & Mika Kortelainen, 2012. "Stochastic non-smooth envelopment of data: semi-parametric frontier estimation subject to shape constraints," Journal of Productivity Analysis, Springer, vol. 38(1), pages 11-28, August.
    34. Diewert, W E, 1980. "Capital and the Theory of Productivity Measurement," American Economic Review, American Economic Association, vol. 70(2), pages 260-267, May.
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    2. Jose M. Cordero & Cristina Polo & Daniel Santín, 2020. "Assessment of new methods for incorporating contextual variables into efficiency measures: a Monte Carlo simulation," Operational Research, Springer, vol. 20(4), pages 2245-2265, December.
    3. Tiziano De Angelis & Peter Tankov & Olivier David Zerbib, 2022. "Climate Impact Investing," Carlo Alberto Notebooks 676 JEL Classification: G, Collegio Carlo Alberto.
    4. Dai, Sheng & Zhou, Xun & Kuosmanen, Timo, 2020. "Forward-looking assessment of the GHG abatement cost: Application to China," Energy Economics, Elsevier, vol. 88(C).
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    6. Bowen Xiao & Dongxiao Niu & Han Wu & Haichao Wang, 2017. "Marginal Abatement Cost of CO 2 in China Based on Directional Distance Function: An Industry Perspective," Sustainability, MDPI, vol. 9(1), pages 1-19, January.
    7. Kuosmanen, Timo & Zhou, Xun, 2021. "Shadow prices and marginal abatement costs: Convex quantile regression approach," European Journal of Operational Research, Elsevier, vol. 289(2), pages 666-675.
    8. Wei, Xiao & Zhang, Ning, 2020. "The shadow prices of CO2 and SO2 for Chinese Coal-fired Power Plants: A partial frontier approach," Energy Economics, Elsevier, vol. 85(C).
    9. Shirong Zhao & Guangshun Qiao, 2022. "The shadow prices of CO2, SO2 and NOx for U.S. coal power industry 2010–2017: a convex quantile regression method," Journal of Productivity Analysis, Springer, vol. 57(3), pages 243-253, June.
    10. Wu, F. & Wang, S.Y. & Zhou, P., 2023. "Marginal abatement cost of carbon dioxide emissions: The role of abatement options," European Journal of Operational Research, Elsevier, vol. 310(2), pages 891-901.
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    More about this item

    Keywords

    Multiplicative decomposition; Technical change; Marginal abatement cost; Sequential frontier estimation;
    All these keywords.

    JEL classification:

    • C43 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Index Numbers and Aggregation
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
    • Q55 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Environmental Economics: Technological Innovation

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