IDEAS home Printed from https://ideas.repec.org/p/ris/albaec/2011_005.html
   My bibliography  Save this paper

Dating U.S. Business Cycles with Macro Factors

Author

Listed:
  • Fossati, Sebastian

    () (University of Alberta, Department of Economics)

Abstract

A probit model is used to show that latent common factors estimated by principal components from a large number of macroeconomic time series have important predictive power for NBER recession dates. A pseudo out-of-sample forecasting exercise shows that predicted recession probabilities consistently rise during subsequently declared NBER recession dates. The latent variable in the factor-augmented probit model is interpreted as an index of real business conditions which can be used to assess the strength of an expansion or the depth of a recession.

Suggested Citation

  • Fossati, Sebastian, 2011. "Dating U.S. Business Cycles with Macro Factors," Working Papers 2011-5, University of Alberta, Department of Economics, revised 01 Feb 2012.
  • Handle: RePEc:ris:albaec:2011_005
    as

    Download full text from publisher

    File URL: https://sites.ualberta.ca/~econwps/2011/wp2011-05.pdf
    File Function: Full text
    Download Restriction: no

    Other versions of this item:

    References listed on IDEAS

    as
    1. Chang-Jin Kim & Charles R. Nelson, 1998. "Business Cycle Turning Points, A New Coincident Index, And Tests Of Duration Dependence Based On A Dynamic Factor Model With Regime Switching," The Review of Economics and Statistics, MIT Press, vol. 80(2), pages 188-201, May.
    2. Dueker, Michael, 1999. "Conditional Heteroscedasticity in Qualitative Response Models of Time Series: A Gibbs-Sampling Approach to the Bank Prime Rate," Journal of Business & Economic Statistics, American Statistical Association, vol. 17(4), pages 466-472, October.
    3. Chang-Jin Kim & Charles R. Nelson, 1999. "State-Space Models with Regime Switching: Classical and Gibbs-Sampling Approaches with Applications," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262112388, January.
    Full references (including those not matched with items on IDEAS)

    Citations

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


    Cited by:

    1. Egger, Peter & Pfaffermayr, Michael, 2011. "Structural Estimation of Gravity Models with Path-dependent Market Entry," CEPR Discussion Papers 8458, C.E.P.R. Discussion Papers.
    2. Fossati, Sebastian, 2017. "Testing for State-Dependent Predictive Ability," Working Papers 2017-9, University of Alberta, Department of Economics.

    More about this item

    Keywords

    business cycle; forecasting; factors; probit model; Bayesian methods;

    JEL classification:

    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • 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
    • 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

    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:ris:albaec:2011_005. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Joseph Marchand). General contact details of provider: http://edirc.repec.org/data/deualca.html .

    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.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with 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.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.