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Dating U.S. Business Cycles with Macro Factors

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Author Info

  • 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.

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File URL: http://www.uofaweb.ualberta.ca/economics2/pdfs/WP2011-05-Fossati.pdf
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Bibliographic Info

Paper provided by University of Alberta, Department of Economics in its series Working Papers with number 2011-5.

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Length: 35 pages
Date of creation: 01 May 2011
Date of revision:
Handle: RePEc:ris:albaec:2011_005

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Related research

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

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Cited by:
  1. Peter Egger & Michael Pfaffermayr, 2011. "Structural Estimation of Gravity Models with Path-Dependent Market Entry," FIW Research Reports series, FIW III-007, FIW.

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