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Forecasting Recessions in Canada: An Autoregressive Probit Model Approach

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  • Antoine Poulin-Moore
  • Kerem Tuzcuoglu

Abstract

We forecast recessions in Canada using an autoregressive (AR) probit model. In this model, the presence of the lagged latent variable, which captures the autocorrelation in the recession binary variable, results in an intractable likelihood with a high dimensional integral. Therefore, we employ composite likelihood methods to facilitate the estimation of this complex model, and we provide their asymptotic results. We perform a variable selection procedure on a large variety of Canadian and foreign macro-financial variables by using the area under the receiver operating characteristic curve (AUROC) as the performance criterion. Our findings suggest that the AR model meaningfully improves the ability to forecast Canadian recessions, relative to a variety of probit models proposed in the Canadian literature. These results are robust to changes in the performance criteria or the sample considered. Our findings also highlight the short-term predictive power of US economic activity and suggest that financial indicators are reliable predictors of Canadian recessions.

Suggested Citation

  • Antoine Poulin-Moore & Kerem Tuzcuoglu, 2024. "Forecasting Recessions in Canada: An Autoregressive Probit Model Approach," Staff Working Papers 24-10, Bank of Canada.
  • Handle: RePEc:bca:bocawp:24-10
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    References listed on IDEAS

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    1. Bragoli, Daniela & Modugno, Michele, 2017. "A now-casting model for Canada: Do U.S. variables matter?," International Journal of Forecasting, Elsevier, vol. 33(4), pages 786-800.
    2. Whitney K. Newey & Kenneth D. West, 1994. "Automatic Lag Selection in Covariance Matrix Estimation," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 61(4), pages 631-653.
    3. Estrella, Arturo & Hardouvelis, Gikas A, 1991. "The Term Structure as a Predictor of Real Economic Activity," Journal of Finance, American Finance Association, vol. 46(2), pages 555-576, June.
    4. Joseph Atta-Mensah & Greg Tkacz, 1998. "Predicting Canadian Recessions Using Financial Variables: A Probit Approach," Staff Working Papers 98-5, Bank of Canada.
    5. Francesco Bartolucci & Valentina Nigro, 2010. "A Dynamic Model for Binary Panel Data With Unobserved Heterogeneity Admitting a √n-Consistent Conditional Estimator," Econometrica, Econometric Society, vol. 78(2), pages 719-733, March.
    6. Varin, Cristiano & Vidoni, Paolo, 2006. "Pairwise likelihood inference for ordinal categorical time series," Computational Statistics & Data Analysis, Elsevier, vol. 51(4), pages 2365-2373, December.
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    More about this item

    Keywords

    Business fluctuations and cycles; Econometric and statistical methods;

    JEL classification:

    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation

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