IDEAS home Printed from https://ideas.repec.org/p/stc/stcp3e/2019013e.html
   My bibliography  Save this paper

Environmentally Adjusted Multifactor Productivity Growth for the Canadian Manufacturing Sector

Author

Listed:
  • Gu, Wulong
  • Willox, Michael
  • Hussain , Jakir

Abstract

The need to measure both the desirable outputs (goods and services) and the undesirable outputs (emissions of greenhouse gases [GHGs] and criteria air contaminants [CACs]) from economic activity is becoming increasingly important as economic performance and environmental performance become ever more intertwined. Standard measures of multifactor productivity (MFP) growth provide insights into rising standards of living and the performance of economies, but they may be misleading if only desirable outputs are considered. This study presents estimates of environmentally adjusted multifactor productivity (EAMFP) growth using a new comprehensive database. This database contains information on GHG and CAC emissions, as well as on the production activities of Canadian manufacturers.

Suggested Citation

  • Gu, Wulong & Willox, Michael & Hussain , Jakir, 2019. "Environmentally Adjusted Multifactor Productivity Growth for the Canadian Manufacturing Sector," Analytical Studies Branch Research Paper Series 2019013e, Statistics Canada, Analytical Studies Branch.
  • Handle: RePEc:stc:stcp3e:2019013e
    as

    Download full text from publisher

    File URL: https://www150.statcan.gc.ca/n1/en/catalogue/11F0019M2019013
    Download Restriction: no
    ---><---

    Citations

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


    Cited by:

    1. Djula Borozan, 2021. "Technical Efficiency and Productivity Change in the European Union with Undesirable Output Considered," Energies, MDPI, vol. 14(16), pages 1-15, August.

    More about this item

    Keywords

    Consumer goods and services; Economic performance; Greenhouse gas emissions; Multifactor Productivity; Outputs; Productivity growth;
    All these keywords.

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:stc:stcp3e:2019013e. 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: Mark Brown (email available below). General contact details of provider: https://edirc.repec.org/data/stagvca.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.