IDEAS home Printed from https://ideas.repec.org/a/taf/applec/v52y2020i1p68-84.html
   My bibliography  Save this article

Aggregate earnings and gross domestic product: International evidence

Author

Listed:
  • Vaibhav Lalwani
  • Madhumita Chakraborty

Abstract

Recent studies in macro accounting suggest that changes in aggregate accounting earnings can predict quarterly GDP growth in the USA. Our objective in this study is to test the robustness of the association between aggregate earnings and real GDP growth across multiple countries and for different definitions of aggregate earnings. We test whether aggregate earnings changes predict future economic growth in eight countries – Australia, Canada, China, India, Japan, South Korea, the UK, and the USA. We find positive evidence regarding the generalisability of the aggregate earnings – real GDP relation in an international context. In additional tests, we find that economic forecasters appear to underreact to aggregate earnings information. Our results show that aggregate earnings lead economic growth and forecasts of real GDP growth can be improved by incorporating aggregate earnings information. Further, we also test if negative earnings changes contain more information than positive earnings changes and find only modest evidence in favour of this hypothesis. The results are robust to alternative statistical methodology and the removal of the USA data from the sample.

Suggested Citation

  • Vaibhav Lalwani & Madhumita Chakraborty, 2020. "Aggregate earnings and gross domestic product: International evidence," Applied Economics, Taylor & Francis Journals, vol. 52(1), pages 68-84, January.
  • Handle: RePEc:taf:applec:v:52:y:2020:i:1:p:68-84
    DOI: 10.1080/00036846.2019.1640859
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/00036846.2019.1640859
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/00036846.2019.1640859?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    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. Thanh NGUYEN, Phong & Le Hoang Thuy To NGUYEN, Quyen, 2020. "Critical Factors Affecting Construction Price Index: An Integrated Fuzzy Logic and Analytical Hierarchy Process," MPRA Paper 103437, University Library of Munich, Germany, revised 31 May 2020.

    More about this item

    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:taf:applec:v:52:y:2020:i:1:p:68-84. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/RAEC20 .

    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.