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Nowcasting and Short-term Forecasting Turkish GDP: Factor-MIDAS Approach

Author

Listed:
  • Selcuk Gul
  • Abdullah Kazdal

Abstract

This paper compares several nowcast approaches that account for mixed-data frequency and “ragged-edge” problems. More specifically, it examines the relative performance of the factor-augmented MIDAS approach (Marcellino and Schumacher; 2010) in nowcasting Turkish GDP with respect to benchmark forecasts. By using 40 monthly indicators in factor extraction, several combinations of the factor-MIDAS models are estimated. Recursive pseudo-out-of sample forecasting exercise in evaluating the alternative models’ performance suggests that factor-augmented MIDAS performs better than the benchmarks, especially in nowcasting. However, they do not provide much information content to forecasting a quarter ahead. Results indicate that taking into account the “ragged-edge” characteristic of the data helps improve the predictive ability of the nowcast models. Besides, dynamic factor extraction methods provide better predictions than the static factor extraction methods.

Suggested Citation

  • Selcuk Gul & Abdullah Kazdal, 2021. "Nowcasting and Short-term Forecasting Turkish GDP: Factor-MIDAS Approach," Working Papers 2111, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
    • Handle: RePEc:tcb:wpaper:2111
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    File URL: https://www.tcmb.gov.tr/wps/wcm/connect/EN/TCMB+EN/Main+Menu/Publications/Research/Working+Paperss/2021/21-11
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    More about this item

    Keywords

    Forecasting; Mixed frequency; Factor-MIDAS;
    All these keywords.

    JEL classification:

    • 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
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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