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A note on GDP now-/forecasting with dynamic versus static factor models along a business cycle

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  • Buss, Ginters

Abstract

We build a small-scale factor model for the GDP of one of the hardest hit economies during the latest recession to study the exact dynamic versus static factor model performance along a business cycle, with an emphasis placing on nowcasting performance during a pronounced switch of business cycle phases due to the latest recession. We compare the factor models' nowcasting performance to a random walk, autoregressive and the best-performing nowcasting models at our hands, which are vector autoregressive (VAR) models. It is shown that a small-scale static factor-augmented VAR (FAVAR) model tends to improve upon the nowcasting performance of the VAR models when the model span and the nowcasting period stretch beyond a single business cycle phase, while exact dynamic factor models tend to fail to detect the timing and depth of the recession regardless of ARMA specifications. As regards the case when the model span and the nowcasting period are contained within a single business cycle phase, static and dynamic factor models appear to show similar performance with potentially slight superiority of dynamic factor models if the factor-forming set of variables and factor dynamics are carefully selected.

Suggested Citation

  • Buss, Ginters, 2010. "A note on GDP now-/forecasting with dynamic versus static factor models along a business cycle," MPRA Paper 22147, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:22147
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    References listed on IDEAS

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    More about this item

    Keywords

    nowcasting; business cycle; static versus dynamic factors; small-scale FAVAR; VAR; GDP;

    JEL classification:

    • 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
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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