IDEAS home Printed from https://ideas.repec.org/a/cje/issued/v47y2014i1p1-34.html

Viewpoint: Boosting Recessions

Author

Listed:
  • Serena Ng

Abstract

This paper explores the effectiveness of boosting, often regarded as the state of the art classification tool, in giving warning signals of recessions 3, 6, and 12 months ahead. Boosting is used to screen as many as 1,500 potentially relevant predictors consisting of 132 real and financial time series and their lags. Estimation over the full sample 1961:12011:12 finds that there are fewer than 10 important predictors and the identity of these variables changes with the forecast horizon. There is a distinct difference in the size and composition of the relevant predictor set before and after mid1980. Rolling window estimation reveals that the importance of the term and default spreads are recession specific. The Aaa spread is the most robust predictor of recessions three and 6 months ahead, while the risky bond and 5year spreads are important for 12 months ahead predictions. Certain employment variables have predictive power for the two most recent recessions when the interest rate spreads were uninformative. Warning signals for the post1990 recessions have been sporadic and easy to miss. The results underscore the challenge that changing characteristics of business cycles pose for predicting recessions.

Suggested Citation

  • Serena Ng, 2014. "Viewpoint: Boosting Recessions," Canadian Journal of Economics, Canadian Economics Association, vol. 47(1), pages 1-34, February.
    • Handle: RePEc:cje:issued:v:47:y:2014:i:1:p:1-34
    DOI: 10.1111/caje.12070
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/caje.12070
    Download Restriction: access restricted to subscribers
    File URL: https://libkey.io/10.1111/caje.12070?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 look for a different version below or

    for a different version of it.

    Other versions of this item:

    More about this item

    JEL classification:

    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • C6 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling
    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions

    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:cje:issued:v:47:y:2014:i:1:p:1-34. 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: Prof. Werner Antweiler (email available below). General contact details of provider: https://edirc.repec.org/data/ceaaaea.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.