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Exploiting the monthly data flow in structural forecasting

Author

Listed:
  • Giannone, Domenico

    (LUISS and Centre for Economic Policy Research)

  • Monti , Francesca

    (Bank of England)

  • Reichlin , Lucrezia

    (London Business School and Centre for Economic Policy Research)

Abstract
This paper shows how and when it is possible to obtain a mapping from a quarterly dynamic stochastic general equilibrium (DSGE) model to a monthly specification that maintains the same economic restrictions and has real coefficients. We use this technique to derive the monthly counterpart of the well-known DSGE model by Galí, Smets and Wouters (GSW) for the US economy. We then augment it with auxiliary macro indicators which, because of their timeliness, can be used to obtain a nowcast of the structural model. We show empirical results for the quarterly growth rate of GDP, the monthly unemployment rate and GSW’s welfare-relevant output gap. Results show that the augmented monthly model does best for nowcasting.

Suggested Citation

  • Giannone, Domenico & Monti , Francesca & Reichlin , Lucrezia, 2014. "Exploiting the monthly data flow in structural forecasting," Bank of England working papers 509, Bank of England.
  • Handle: RePEc:boe:boeewp:0509
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    References listed on IDEAS

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    Full references (including those not matched with items on IDEAS)

    Citations

    Blog mentions

    As found by EconAcademics.org, the blog aggregator for Economics research:
    1. Hey, Economist! How Do You Forecast the Present?
      by Blog Author in Liberty Street Economics on 2017-06-16 20:15:00
    2. Exploiting the monthly data flow in structural forecasting
      by Christian Zimmermann in NEP-DGE blog on 2014-10-05 22:06:38

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    8. Meyer-Gohde, Alexander & Shabalina, Ekaterina, 2022. "Estimation and forecasting using mixed-frequency DSGE models," IMFS Working Paper Series 175, Goethe University Frankfurt, Institute for Monetary and Financial Stability (IMFS).
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    More about this item

    Keywords

    Forecasting; temporal aggregation; mixed frequency data; large data sets;
    All these keywords.

    JEL classification:

    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E30 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - General (includes Measurement and Data)

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