IDEAS home Printed from https://ideas.repec.org/a/oup/jfinec/v22y2024i5p1482-1502..html
   My bibliography  Save this article

Do Recessions and Bear Markets Occur Concurrently across Countries? A Multinomial Logistic Approach

Author

Listed:
  • Aubrey Poon
  • Dan Zhu

Abstract

We introduce a novel multinomial logistic model for detecting and forecasting concurrent recessions and bear markets across multiple countries. Our framework leverages cross-country panel features and provides additional information for robust analysis. Through a comprehensive simulation study, we demonstrate the computational efficiency and accuracy of our model, even when handling multiple binary indicators. Applying our framework to empirical data from the United States, the UK, and Euro Area, we find that the multinomial logistic model produces superior medium-term forecasting of concurrent recession and bear market events across countries compared to multiple independent single logistic models. Additionally, our counterfactual analysis reveals that specific events, such as a recession and bear market in the United States, along with the tightening of financial conditions and a negative interest rate spread in the United States, increase the probability of concurrent and individual recession and bear market occurrences in the UK and Euro Area.

Suggested Citation

  • Aubrey Poon & Dan Zhu, 2024. "Do Recessions and Bear Markets Occur Concurrently across Countries? A Multinomial Logistic Approach," Journal of Financial Econometrics, Oxford University Press, vol. 22(5), pages 1482-1502.
  • Handle: RePEc:oup:jfinec:v:22:y:2024:i:5:p:1482-1502.
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1093/jjfinec/nbae003
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

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

    More about this item

    Keywords

    recession prediction; bear markets; multinomial logistic; cross-country; mixed frequency; Bayesian estimation;
    All these keywords.

    JEL classification:

    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities

    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:oup:jfinec:v:22:y:2024:i:5:p:1482-1502.. 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: Oxford University Press (email available below). General contact details of provider: https://edirc.repec.org/data/sofieea.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.