IDEAS home Printed from https://ideas.repec.org/a/wly/jmoncb/v47y2015i5p847-866.html
   My bibliography  Save this article

Forecasting National Recessions Using State‐Level Data

Author

Listed:
  • MICHAEL T. OWYANG
  • JEREMY PIGER
  • HOWARD J. WALL

Abstract

We investigate whether there is information useful for identifying U.S. business cycle phases contained in subnational measures of economic activity. Using a probit model to forecast the National Bureau of Economic Research expansion and recession classification, we assess the incremental information content of state‐level employment growth over a commonly used set of national‐level predictors. As state‐level data adds a large number of predictors to the model, we employ a Bayesian model averaging procedure to construct forecasts. Based on a variety of forecast evaluation metrics, we find that including state‐level employment growth substantially improves nowcasts and very short‐horizon forecasts of the business cycle phase. The gains in forecast accuracy are concentrated during months of national recession.

Suggested Citation

  • Michael T. Owyang & Jeremy Piger & Howard J. Wall, 2015. "Forecasting National Recessions Using State‐Level Data," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 47(5), pages 847-866, August.
  • Handle: RePEc:wly:jmoncb:v:47:y:2015:i:5:p:847-866
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1111/jmcb.12228
    Download Restriction: no

    Other versions of this item:

    References listed on IDEAS

    as
    1. Thomas B. King & Andrew T. Levin & Roberto Perli, 2007. "Financial market perceptions of recession risk," Finance and Economics Discussion Series 2007-57, Board of Governors of the Federal Reserve System (U.S.).
    2. Michael T. Owyang & Jeremy Piger & Howard J. Wall, 2005. "Business Cycle Phases in U.S. States," The Review of Economics and Statistics, MIT Press, vol. 87(4), pages 604-616, November.
    3. Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-384, March.
    4. Wesley Clair Mitchell, 1927. "Business Cycles: The Problem and Its Setting," NBER Books, National Bureau of Economic Research, Inc, number mitc27-1, January.
    5. James D. Hamilton & Michael T. Owyang, 2012. "The Propagation of Regional Recessions," The Review of Economics and Statistics, MIT Press, pages 935-947.
    6. Hernandez-Murillo, Ruben & Owyang, Michael T., 2006. "The information content of regional employment data for forecasting aggregate conditions," Economics Letters, Elsevier, pages 335-339.
    7. Chauvet, Marcelle & Piger, Jeremy, 2008. "A Comparison of the Real-Time Performance of Business Cycle Dating Methods," Journal of Business & Economic Statistics, American Statistical Association, vol. 26, pages 42-49, January.
    8. Jeffrey C. Fuhrer & Scott Schuh, 1998. "Beyond shocks: what causes business cycles?," Conference Series ; [Proceedings], Federal Reserve Bank of Boston, vol. 42(Jun).
    9. Wesley Clair Mitchell, 1927. "Introductory pages to "Business Cycles: The Problem and Its Setting"," NBER Chapters,in: Business Cycles: The Problem and Its Setting, pages -23 National Bureau of Economic Research, Inc.
    10. Hamilton, James D., 2011. "Calling recessions in real time," International Journal of Forecasting, Elsevier, vol. 27(4), pages 1006-1026, October.
    11. Estrella, Arturo, 1998. "A New Measure of Fit for Equations with Dichotomous Dependent Variables," Journal of Business & Economic Statistics, American Statistical Association, vol. 16(2), pages 198-205, April.
    12. Arthur F. Burns & Wesley C. Mitchell, 1946. "Measuring Business Cycles," NBER Books, National Bureau of Economic Research, Inc, number burn46-1, 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. Guérin, Pierre & Leiva-Leon, Danilo, 2017. "Model averaging in Markov-switching models: Predicting national recessions with regional data," Economics Letters, Elsevier, vol. 157(C), pages 45-49.
    2. Sylvia Kaufmann, 2016. "Hidden Markov models in time series, with applications in economics," Working Papers 16.06, Swiss National Bank, Study Center Gerzensee.
    3. Chauvet, Marcelle & Potter, Simon, 2013. "Forecasting Output," Handbook of Economic Forecasting, Elsevier.

    More about this item

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection

    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:wly:jmoncb:v:47:y:2015:i:5:p:847-866. 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: (Wiley-Blackwell Digital Licensing) or (Christopher F. Baum). General contact details of provider: http://www.blackwellpublishing.com/journal.asp?ref=0022-2879 .

    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.