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Short-term Forecasting of Real GDP Using Monthly Data

Author

Listed:
  • Juraj Hucek

    () (National Bank of Slovakia, Economic and Monetary Analyses Department)

  • Alexander Karsay

    () (National Bank of Slovakia, Economic and Monetary Analyses Department)

  • Marian Vavra

    () (National Bank of Slovakia, Research Department)

Abstract

This occasional paper considers the problem of forecasting, nowcasting, and backcasting the Slovak real GDP growth rate using approximate factor models. Three different versions of approximate factor models are proposed. Forecast comparison with other models such as bridge equation models and ARMA models is also provided. Our results reveal that factor models clearly outperform an ARMA model and can compete with bridge models currently used at the Bank. Therefore, we tend to incorporate factor models into the regular forecasting process at the Bank.Finally, we hold the view that future research should be devoted to further improvements of bridge models since these models are simple to construct, easy to understand, and widely used in central banks.

Suggested Citation

  • Juraj Hucek & Alexander Karsay & Marian Vavra, 2015. "Short-term Forecasting of Real GDP Using Monthly Data," Working and Discussion Papers OP 1/2015, Research Department, National Bank of Slovakia.
  • Handle: RePEc:svk:wpaper:1035
    as

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    References listed on IDEAS

    as
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    Citations

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    as


    Cited by:

    1. Tomas Adam & Filip Novotny, 2018. "Assessing the External Demand of the Czech Economy: Nowcasting Foreign GDP Using Bridge Equations," Working Papers 2018/18, Czech National Bank.
    2. Tóth, Peter, 2014. "Malý dynamický faktorový model na krátkodobé prognózovanie slovenského HDP
      [A Small Dynamic Factor Model for the Short-Term Forecasting of Slovak GDP]
      ," MPRA Paper 63713, University Library of Munich, Germany.

    More about this item

    Keywords

    factor models; principal components; bridge equations; short-term forecasting; GDP;

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E27 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Forecasting and Simulation: Models and Applications

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