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A dynamic factor model for nowcasting Canadian GDP growth

Author

Listed:
  • Tony Chernis

    (Bank of Canada)

  • Rodrigo Sekkel

    (Bank of Canada)

Abstract

This paper estimates a dynamic factor model (DFM) for nowcasting Canadian gross domestic product. The model is estimated with a mix of soft and hard indicators, and it features a high share of international data. The model is then used to generate nowcasts, predictions of the recent past and current state of the economy. In a pseudo-real-time setting, we show that the DFM outperforms univariate benchmarks, as well as other commonly used nowcasting models, such as MIDAS and bridge regressions.

Suggested Citation

  • Tony Chernis & Rodrigo Sekkel, 2017. "A dynamic factor model for nowcasting Canadian GDP growth," Empirical Economics, Springer, vol. 53(1), pages 217-234, August.
    • Handle: RePEc:spr:empeco:v:53:y:2017:i:1:d:10.1007_s00181-017-1254-1
    DOI: 10.1007/s00181-017-1254-1
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    More about this item

    Keywords

    Nowcasting; Dynamic factor model; Canada;
    All these keywords.

    JEL classification:

    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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