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Relative Effectiveness of Energy Efficiency Programs versus Market Based Climate Policies in the Chemical Industry

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  • Gale A. Boyd
  • Jonathan M. Lee

Abstract

This paper addresses the relative effectiveness of market vs program based climate policies. We compute the carbon price resulting in an equivalent reduction in energy from programs that eliminate the efficiency gap. A reduced-form stochastic frontier energy demand analysis of plant level electricity and fuel data, from energy-intensive chemical sectors, jointly estimates the distribution of energy efficiency and underlying price elasticities. The analysis obtains a decomposition of efficiency into persistent (PE) and time-varying (TVE) components. Total inefficiency is relatively small in most sectors and price elasticities are relatively high. If all plants performed at the 90th percentile of their efficiency distribution, the reduction in energy is between 4% and 37%. A carbon price averaging around $31.51/ton CO2 would achieve reductions in energy use equivalent to all manufacturing plants making improvements to close the efficiency gap.

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  • Gale A. Boyd & Jonathan M. Lee, 2020. "Relative Effectiveness of Energy Efficiency Programs versus Market Based Climate Policies in the Chemical Industry," The Energy Journal, , vol. 41(3), pages 39-62, May.
    • Handle: RePEc:sae:enejou:v:41:y:2020:i:3:p:39-62
    DOI: 10.5547/01956574.41.3.gboy
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    1. Filippini, Massimo & Hunt, Lester C., 2012. "US residential energy demand and energy efficiency: A stochastic demand frontier approach," Energy Economics, Elsevier, vol. 34(5), pages 1484-1491.
    2. Lundgren, Tommy & Marklund, Per-Olov & Zhang, Shanshan, 2016. "Industrial energy demand and energy efficiency – Evidence from Sweden," Resource and Energy Economics, Elsevier, vol. 43(C), pages 130-152.
    3. Filippini, Massimo & Hunt, Lester C., 2015. "Measurement of energy efficiency based on economic foundations," Energy Economics, Elsevier, vol. 52(S1), pages 5-16.
    4. Massimo Filippini & Lester C. Hunt, 2011. "Energy Demand and Energy Efficiency in the OECD Countries: A Stochastic Demand Frontier Approach," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2), pages 59-80.
    5. Gale A. Boyd, 2008. "Estimating Plant Level Energy Efficiency with a Stochastic Frontier," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2), pages 23-44.
    6. Bardazzi, Rossella & Oropallo, Filippo & Pazienza, Maria Grazia, 2015. "Do manufacturing firms react to energy prices? Evidence from Italy," Energy Economics, Elsevier, vol. 49(C), pages 168-181.
    7. Zhang, Shanshan & Lundgren, Tommy & Zhou, Wenchao, 2016. "Energy efficiency in Swedish industry," Energy Economics, Elsevier, vol. 55(C), pages 42-51.
    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. Boyd, Gale A. & Lee, Jonathan M., 2019. "Measuring plant level energy efficiency and technical change in the U.S. metal-based durable manufacturing sector using stochastic frontier analysis," Energy Economics, Elsevier, vol. 81(C), pages 159-174.
    10. Morakinyo O. Adetutu, Anthony J. Glass, and Thomas G. Weyman-Jones, 2016. "Economy-wide Estimates of Rebound Effects: Evidence from Panel Data," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3).
    11. 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.
    12. Amsler, Christine & Prokhorov, Artem & Schmidt, Peter, 2016. "Endogeneity in stochastic frontier models," Journal of Econometrics, Elsevier, vol. 190(2), pages 280-288.
    13. Lucia Foster & Cheryl Grim & John Haltiwanger, 2016. "Reallocation in the Great Recession: Cleansing or Not?," Journal of Labor Economics, University of Chicago Press, vol. 34(S1), pages 293-331.
    14. Eric J. Bartelsman & Wayne Gray, 1996. "The NBER Manufacturing Productivity Database," NBER Technical Working Papers 0205, National Bureau of Economic Research, Inc.
    15. Subal Kumbhakar & Gudbrand Lien & J. Hardaker, 2014. "Technical efficiency in competing panel data models: a study of Norwegian grain farming," Journal of Productivity Analysis, Springer, vol. 41(2), pages 321-337, April.
    16. Lutz, Benjamin Johannes & Massier, Philipp & Sommerfeld, Katrin & Löschel, Andreas, 2017. "Drivers of energy efficiency in German manufacturing: A firm-level stochastic frontier analysis," ZEW Discussion Papers 17-068, ZEW - Leibniz Centre for European Economic Research.
    17. Sang V Nguyen & Mary L Streitwieser, 1997. "Capital-Energy Substitution Revisted: New Evidence From Micro Data," Working Papers 97-4, Center for Economic Studies, U.S. Census Bureau.
    18. Boyd, Gale A. & Curtis, E. Mark, 2014. "Evidence of an “Energy-Management Gap” in U.S. manufacturing: Spillovers from firm management practices to energy efficiency," Journal of Environmental Economics and Management, Elsevier, vol. 68(3), pages 463-479.
    19. Willam Greene, 2005. "Fixed and Random Effects in Stochastic Frontier Models," Journal of Productivity Analysis, Springer, vol. 23(1), pages 7-32, January.
    20. Jondrow, James & Knox Lovell, C. A. & Materov, Ivan S. & Schmidt, Peter, 1982. "On the estimation of technical inefficiency in the stochastic frontier production function model," Journal of Econometrics, Elsevier, vol. 19(2-3), pages 233-238, August.
    21. Bostian, Moriah & Färe, Rolf & Grosskopf, Shawna & Lundgren, Tommy, 2016. "Environmental investment and firm performance: A network approach," Energy Economics, Elsevier, vol. 57(C), pages 243-255.
    22. Jaffe, Adam B. & Stavins, Robert N., 1994. "The energy-efficiency gap What does it mean?," Energy Policy, Elsevier, vol. 22(10), pages 804-810, October.
    23. Boyd, Gale A., 2014. "Estimating the changes in the distribution of energy efficiency in the U.S. automobile assembly industry," Energy Economics, Elsevier, vol. 42(C), pages 81-87.
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    Cited by:

    1. Lee, Jonathan M. & Howard, Gregory, 2021. "The impact of technical efficiency, innovation, and climate policy on the economic viability of renewable electricity generation," Energy Economics, Elsevier, vol. 100(C).
    2. Xu, Bin & Lin, Boqiang, 2020. "Investigating drivers of CO2 emission in China’s heavy industry: A quantile regression analysis," Energy, Elsevier, vol. 206(C).
    3. Gale Boyd & Matt Doolin, 2020. "The Energy Efficiency Gap and Energy Price Responsiveness in Food Processing," Working Papers 20-18, Center for Economic Studies, U.S. Census Bureau.

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    More about this item

    Keywords

    Energy efficiency; Price elasticities; Manufacturing; Stochastic frontier; Plant-level data;
    All these keywords.

    JEL classification:

    • F0 - International Economics - - General

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