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Implied discount rate and payback threshold of energy efficiency investment in the industrial sector

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  • Yueming Qiu
  • Yi David Wang
  • Jianfeng Wang

Abstract

The industrial sector is responsible for about a third of the energy usage in the United States, and there is significant energy saving potential from the industrial sector. However, the phenomenon of "energy efficiency gap" - the scenario in which cost-effective energy efficient technologies enjoy only limited market success - appears frequently in the industrial sector. This article tries to explain this efficiency gap in the industrial sector by empirically estimating the implied discount rates and payback thresholds industrial firms use to evaluate their energy efficiency investments. Using the Industrial Assessment Centers (IAC) database from 2002 to 2011, with more than 30 000 energy efficiency recommendations, this article builds structural models of firms' evaluation of an energy efficiency project. The model results show that the implied discount rates of medium to small industrial firms range from 40 to 45%, and the average payback threshold is about 9 months.

Suggested Citation

  • Yueming Qiu & Yi David Wang & Jianfeng Wang, 2015. "Implied discount rate and payback threshold of energy efficiency investment in the industrial sector," Applied Economics, Taylor & Francis Journals, vol. 47(21), pages 2218-2233, May.
    • Handle: RePEc:taf:applec:v:47:y:2015:i:21:p:2218-2233
    DOI: 10.1080/00036846.2015.1005820
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    Cited by:

    1. Zhu, Tong & Curtis, John & Clancy, Matthew, 2023. "Modelling barriers to low-carbon technologies in energy system analysis: The example of renewable heat in Ireland," Applied Energy, Elsevier, vol. 330(PA).
    2. Yueming (Lucy) Qiu & Xin Su & Yi David Wang, 2017. "Factors influencing commercial buildings to obtain green certificates," Applied Economics, Taylor & Francis Journals, vol. 49(20), pages 1937-1949, April.
    3. Aida Sa & Patrik Thollander & Majid Rafiee, 2018. "Industrial Energy Management Systems and Energy-Related Decision-Making," Energies, MDPI, vol. 11(10), pages 1-12, October.
    4. Lang, Corey & Qiu, Yueming (Lucy) & Dong, Luran, 2023. "Increasing voluntary enrollment in time-of-use electricity rates: Findings from a survey experiment," Energy Policy, Elsevier, vol. 173(C).
    5. Safarzadeh, Soroush & Rasti-Barzoki, Morteza & Hejazi, Seyed Reza, 2020. "A review of optimal energy policy instruments on industrial energy efficiency programs, rebound effects, and government policies," Energy Policy, Elsevier, vol. 139(C).
    6. Andersen, Kristoffer Steen & Wiese, Catharina & Petrovic, Stefan & McKenna, Russell, 2020. "Exploring the role of households’ hurdle rates and demand elasticities in meeting Danish energy-savings target," Energy Policy, Elsevier, vol. 146(C).
    7. Di Foggia, Giacomo, 2021. "Drivers and challenges of electric vehicles integration in corporate fleet: An empirical survey," SocArXiv b3e56, Center for Open Science.
    8. Dimitar Blagoev & Radostin Boyadzhiev, 2020. "Methodological Aspects of Management of Portfolios of Investment Projects for Real Assets of Business Organizations," Economic Archive, D. A. Tsenov Academy of Economics, Svishtov, Bulgaria, issue 3 Year 20, pages 71-90.
    9. Andersen, Kristoffer Steen & Dockweiler, Steffen & Klinge Jacobsen, Henrik, 2019. "Squaring the energy efficiency circle: evaluating industry energy efficiency policy in a hybrid model setting," MPRA Paper 96546, University Library of Munich, Germany.

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