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Recession Forecasting with Dynamic Probit Models under Real Time Conditions

Author

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  • Christian Proano

    (IMK at the Hans Boeckler Foundation)

Abstract

In this paper a dynamic probit model for recession forecasing under pseudo-real time is set up using a large set of macroeconomic and financial monthly indicators for Germany. Using different initial sets of explanatory variables, alternative dynamic probit specifications are obtained through an automatized general-to-specific lag selection procedure, which are then pooled in order to decrease the volatility of the estimated recession probabilities and increase their forecasting accuracy. As it is shown in the paper, this procedure does not only feature good in-sample forecast statistics, but has also good out-of-sample performance, as pseudo-real time evaluation exercises show.

Suggested Citation

  • Christian Proano, 2010. "Recession Forecasting with Dynamic Probit Models under Real Time Conditions," IMK Working Paper 10-2010, IMK at the Hans Boeckler Foundation, Macroeconomic Policy Institute.
    • Handle: RePEc:imk:wpaper:10-2010
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    File URL: http://www.boeckler.de/pdf/p_imk_wp_10_2010.pdf
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    Cited by:

    1. Proaño, Christian R. & Theobald, Thomas, 2014. "Predicting recessions with a composite real-time dynamic probit model," International Journal of Forecasting, Elsevier, vol. 30(4), pages 898-917.

    More about this item

    Keywords

    Dynamic probit models; out-of-sample forecasting; yield curve; real-time econometrics;
    All these keywords.

    JEL classification:

    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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