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Nowcasting during the Pandemic: Lessons from Argentina

Author

Listed:
  • Emilio Blanco

    (Central Bank of Argentina)

  • Fiorella Dogliolo
  • Lorena Garegnani

Abstract

We forecast economic activity in Argentina on a quarterly real-time basis using dynamic factors models (DFM) (Blanco et al. 2018) and evaluate their forecasting performance during the COVID- 19 pandemic of 2020. We compare the results of forecasts based on a pre-pandemic estimation of the parameters in the DFM and a re-estimated DFM with updated parameters using the most recent information. Considering the extreme observations that occurred during this particular year, we explore whether including new high frequency indicators (such as energy consumption and mobility) help capture more accurately the severe downturn.

Suggested Citation

  • Emilio Blanco & Fiorella Dogliolo & Lorena Garegnani, 2022. "Nowcasting during the Pandemic: Lessons from Argentina," BCRA Working Paper Series 202299, Central Bank of Argentina, Economic Research Department.
    • Handle: RePEc:bcr:wpaper:202299
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    References listed on IDEAS

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    More about this item

    Keywords

    nowcasting; dynamic factor models; COVID-19;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • 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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