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Exploiting the monthly data-flow in structural forecasting

Author Info

Listed author(s):
  • Domenico Giannone

    ()

    (Libera Università Internazionale degli Studi Sociali Guido Carli (LUISS)
    Centre for Economic Policy Research (CEPR))

  • Francesca Monti

    ()

    (Bank of England
    Centre for Macroeconomics (CFM))

  • Lucrezia Reichlin

    ()

    (London Business School (LBS)
    Centre for Economic Policy Research (CEPR))

Abstract

This paper shows how and when it is possible to obtain a mapping from a quarterly 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 Gali et al (2011) model. We then augment it with auxiliary macro indicators which, because of their timeliness, can be used to obtain a now-cast of the structural model. We show empirical results for the quarterly growth rate of GDP, the monthly unemployment rate and the welfare relevant output gap defined in Gali, Smets and Wouters (2011). Results show that the augmented monthly model does best for now-casting.

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File URL: http://www.centreformacroeconomics.ac.uk/Discussion-Papers/2014/CFMDP2014-16-Paper.pdf
File Function: First version, 2014
Download Restriction: no

Paper provided by Centre for Macroeconomics (CFM) in its series Discussion Papers with number 1416.

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Length: 23 pages
Date of creation: Jun 2014
Handle: RePEc:cfm:wpaper:1416
Contact details of provider: Web page: http://www.centreformacroeconomics.ac.uk/

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Keywords: DSGE Models; Forecasting; Temporal Aggregation; Mixed Frequency Data; Large Datasets;

Other versions of this item:

Find related papers by 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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  1. Elena Angelini & Gonzalo Camba‐Mendez & Domenico Giannone & Lucrezia Reichlin & Gerhard Rünstler, 2011. "Short‐term forecasts of euro area GDP growth," Econometrics Journal, Royal Economic Society, vol. 14(1), pages 25-44, February.
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  4. Giannone, Domenico & Reichlin, Lucrezia & Small, David, 2008. "Nowcasting: The real-time informational content of macroeconomic data," Journal of Monetary Economics, Elsevier, vol. 55(4), pages 665-676, May.
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  11. Catherine Doz & Domenico Giannone & Lucrezia Reichlin, 2012. "A Quasi–Maximum Likelihood Approach for Large, Approximate Dynamic Factor Models," The Review of Economics and Statistics, MIT Press, vol. 94(4), pages 1014-1024, November.
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  25. Frank Smets & Rafael Wouters, 2007. "Shocks and Frictions in US Business Cycles: A Bayesian DSGE Approach," American Economic Review, American Economic Association, vol. 97(3), pages 586-606, June.
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  27. Giannone, Domenico & Reichlin, Lucrezia & Small, David, 2005. "Nowcasting GDP and Inflation: The Real Time Informational Content of Macroeconomic Data Releases," CEPR Discussion Papers 5178, C.E.P.R. Discussion Papers.
  28. Červená, Marianna & Schneider, Martin, 2014. "Short-term forecasting of GDP with a DSGE model augmented by monthly indicators," International Journal of Forecasting, Elsevier, vol. 30(3), pages 498-516.
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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 15:15:00
  2. Exploiting the monthly data flow in structural forecasting
    by Christian Zimmermann in NEP-DGE blog on 2014-10-05 17:06:38
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Cited by:

  1. Christensen, Bent Jesper & Posch, Olaf & van der Wel, Michel, 2016. "Estimating dynamic equilibrium models using mixed frequency macro and financial data," Journal of Econometrics, Elsevier, vol. 194(1), pages 116-137.
  2. Fabian Krüger & Todd E. Clark & Francesco Ravazzolo, 2015. "Using Entropic Tilting to Combine BVAR Forecasts with External Nowcasts," Working Papers No 8/2015, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.

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