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Forecasting US recessions with various risk factors and dynamic probit models

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  • Ng, Eric C.Y.

Abstract

This paper extends probit recession forecasting models by incorporating various recession risk factors and using the advanced dynamic probit modeling approaches. The proposed risk factors include financial market expectations of a gloomy economic outlook, credit or liquidity risks in the general economy, the risks of negative wealth effects resulting from the bursting of asset price bubbles, and signs of deteriorating macroeconomic fundamentals. The model specifications include three different dynamic probit models and the standard static model. The out-of-sample analysis suggests that the four probit models with the proposed risk factors can generate more accurate forecasts for the duration of recessions than the conventional static models with only yield spread and equity price index as the predictors. Among the four probit models, the dynamic and dynamic autoregressive probit models outperform the static and autoregressive models in terms of predicting the recession duration. With respect to forecasting the business cycle turning points, the static probit model is as good as the dynamic probit models by being able to flag an early warning signal of a recession.

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Bibliographic Info

Article provided by Elsevier in its journal Journal of Macroeconomics.

Volume (Year): 34 (2012)
Issue (Month): 1 ()
Pages: 112-125

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Handle: RePEc:eee:jmacro:v:34:y:2012:i:1:p:112-125

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Web page: http://www.elsevier.com/locate/inca/622617

Related research

Keywords: Recession forecasts; Recession risks; Dynamic probit models;

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References

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Cited by:
  1. Schreiber, Sven, 2013. "Forecasting business-cycle turning points with (relatively large) linear systems in real time," Annual Conference 2013 (Duesseldorf): Competition Policy and Regulation in a Global Economic Order 79709, Verein für Socialpolitik / German Economic Association.
  2. Schreiber, Sven, 2014. "Anticipating business-cycle turning points in real time using density forecasts from a VAR," Discussion Papers 2014/2, Free University Berlin, School of Business & Economics.

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