IDEAS home Printed from https://ideas.repec.org/p/cnf/wpaper/1105.html
   My bibliography  Save this paper

Using a Leading Credit Index to Predict Turning Points in the U.S. Business Cycle

Author

Listed:
  • Gad Levanon

    (The Conference Board)

  • Jean-Claude Manini

    (The Conference Board)

  • Ataman Ozyildirim

    (The Conference Board)

  • Brian Schaitkin

    (The Conference Board)

  • Jennelyn Tanchua

    (The Conference Board)

Abstract

Financial indicators such as yield curves and stock prices have been extensively used as leading indicators of economic activity due to their forward looking content. Indeed, the Leading Economic Index (LEI) for the United States, a widely used forecasting tool for business cycle turning points, includes several financial components. However, we argue that the coverage of financial and credit market activity in the LEI can be improved to account for some of the structural changes in the U.S. economy (especially in financial markets) and we present evidence that at least one of the existing components, namely real money supply does not perform as well as it used to as a leading indicator in the past several decades. Over the past three decades, many new financial indicators, such as interest rate swaps, credit default swaps, certain corporate-treasury spreads, the Federal Reserve’s senior loan officer survey, etc. have become available, but, since most of these new indicators have not been available for a long enough period, very little research has been conducted to evaluate their utility as leading indicators. In this paper we evaluate the usefulness of a large number of financial indicators according to their ability to predict recessions (i.e. peaks in the business cycle). First, we establish the criteria which are helpful for assessing whether and when such financial indicators generate signals of recessions. We then choose the best ones and aggregate them into a single composite index of financial indicators which we name the Leading Credit Index (LCI). Our approach differs from others in the literature in that we focus on a small, carefully selected set of indicators as index components and, additionally, in our selection criteria we target business cycle turning points rather than financial stability. We argue that this leading credit index can be helpful to estimate recession probabilities better than individual indicators, including some of the existing components of the LEI, especially real money supply. As opposed to other recent financial indexes created to measure financial instability or volatility, the purpose of ours is to signal recessions in the US economy, and as such it could serve as an appropriate new component for the U.S. LEI.

Suggested Citation

  • Gad Levanon & Jean-Claude Manini & Ataman Ozyildirim & Brian Schaitkin & Jennelyn Tanchua, 2011. "Using a Leading Credit Index to Predict Turning Points in the U.S. Business Cycle," Economics Program Working Papers 11-05, The Conference Board, Economics Program.
  • Handle: RePEc:cnf:wpaper:1105
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    Citations

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


    Cited by:

    1. Liu, Weiling & Moench, Emanuel, 2016. "What predicts US recessions?," International Journal of Forecasting, Elsevier, vol. 32(4), pages 1138-1150.
    2. Lahiri, Kajal & Yang, Liu, 2016. "Asymptotic variance of Brier (skill) score in the presence of serial correlation," Economics Letters, Elsevier, vol. 141(C), pages 125-129.

    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:cnf:wpaper:1105. 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: A Ozyildirim (email available below). General contact details of provider: https://edirc.repec.org/data/confbus.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.