IDEAS home Printed from https://ideas.repec.org/a/aen/journl/ej41-4-zhang.html
   My bibliography  Save this article

Herding Cats: Firm Non-Compliance in Chinas Industrial Energy Efficiency Program

Author

Listed:
  • Valerie J. Karplus, Xingyao Shen, and Da Zhang

Abstract

We study firm responses to a large-scale energy efficiency program in China, focusing on the quality of reporting and compliance outcomes. Using statistical methods to detect data manipulation in compliance reports, we find evidence that firms deliberately exaggerated performance during the first phase of the program (2006-2010), suggesting the high compliance rate was overstated. In its second phase (2011-2015), the number of firms in the program expanded by an order of magnitude, and the compliance rate decreased. We develop a simple model to show how the observed increase in non-compliance is consistent with reduced misreporting. Statistical tests find no evidence of manipulation in the second phase. Larger firms, especially those not controlled by the state, and firms in cities with relatively low growth were more likely to report non-compliance, which suggests a role for state control and local protectionism in shaping compliance decisions. Based on our findings, we offer several lessons for future program design.

Suggested Citation

  • Valerie J. Karplus, Xingyao Shen, and Da Zhang, 2020. "Herding Cats: Firm Non-Compliance in Chinas Industrial Energy Efficiency Program," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4), pages 1-30.
    • Handle: RePEc:aen:journl:ej41-4-zhang
    as

    Download full text from publisher

    File URL: http://www.iaee.org/en/publications/ejarticle.aspx?id=3525
    Download Restriction: Access to full text is restricted to IAEE members and subscribers.
    ---><---

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

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Qiming Yang & Jun He & Ting Liu & Zhitao Zhu, 2021. "Environmental Effects of Credit Allocation Structure and Environmental Expenditures: Evidence from China," Sustainability, MDPI, vol. 13(11), pages 1-16, May.
    2. Steffen, Bjarne & Karplus, Valerie & Schmidt, Tobias S., 2022. "State ownership and technology adoption: The case of electric utilities and renewable energy," Research Policy, Elsevier, vol. 51(6).
    3. Dan Xie, 2024. "China’s Manufacturing Pollution, Environmental Regulation and Trade," FIW Working Paper series 198, FIW.

    More about this item

    JEL classification:

    • F0 - International Economics - - General

    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:aen:journl:ej41-4-zhang. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: David Williams (email available below). General contact details of provider: https://edirc.repec.org/data/iaeeeea.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.