New Eurocoin: Tracking Economic Growth in Real Time

By Filippo Altissimo, Riccardo Cristadoro, M. Forni, Marco Lippi, Giovanni Veronese. Review of Economics and Statistics, 2007

387 citations recorded by the source corpus.

Removal of short-run dynamics from a stationary time series to isolate the medium- to long-run component can be obtained by a bandpass filter. However, bandpass filters are infinite moving averages and can therefore deteriorate at the end of the sample. This is a well-known result in the literature isolating the business cycle in integrated series. We show that the same problem arises with our application to stationary time series. In this paper, we develop a method to obtain smoothing of a stationary time series by using only contemporaneous values of a large data set, so that no end-of-sample deterioration occurs. Our method is applied to the construction of New Eurocoin, an indicator of economic activity for the euro area, which is an estimate, in real time, of the medium- to long-run component of GDP growth. As our data set is monthly and most of the series are updated with a short delay, we are able to produce a monthly real-time indicator. As an estimate of the medium- to long-run GDP growth, Eurocoin performs better than the bandpass filter at the end of the sample in terms of both fitting and turning-point signaling.

Subfields: Economics and Econometrics, Finance

View Paper: https://www.semanticscholar.org/paper/7a92448822f17d499a9035a3abc47896b2b0a782

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Citations in the corpus

Dynamic Factor Models, Factor-Augmented Vector Autoregressions, and Structural Vector Autoregressions in Macroeconomics (2016, methodology): “EuroCOIN was developed by Altissimo et al. (2001) and initially incorporated 951 Euro-area activity variables. The index was updated in Altissimo et al. (2010); that version entails estimating the factors by principal”
A Survey of Econometric Methods for Mixed-Frequency Data (2013, methodology): “Smoothed MIDAS A different way to formulate a mixed-frequency projection is proposed by Altissimo et al. (2010).”
Testing for Structural Breaks in Dynamic Factor Models (2011, methodology): “We apply the LM test procedure presented in sections 2 and 3 to a dataset used in Altissimo et al. (2007).(9) This dataset has originally been compiled to construct the Eurocoin indicator provided by the Banca d’ Italia and published on the CEPR’s web page. This indicator has become a benchmark for ”