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New Eurocoin: Tracking Economic Growth in Real Time

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Author Info
Mario Forni ()
Filippo Altissimo
Riccardo Cristadoro
Marco Lippi
Giovanni Veronese.

Additional information is available for the following registered author(s):

Abstract

Removal of short-run dynamics from a stationary time series to isolate the medium to long-run component, can be obtained by a band-pass filter. However, band pass 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 dataset, so that no end-of-sample deterioration occurs. Our construction is based on a special version of Generalized Principal Components, which is designed to use leading variables in the dataset as proxies for missing future values in the variable of interest. Our method is applied to the construction of New Eurocoin, an indicator of economic activity for the euro area. New Eurocoin is an estimate, in real time, of the medium to long-run component of the euro area GDP growth, which performs equally well within and at the end of the sample. As our dataset is monthly and most of the series are updated with a short delay, we are able to produce a monthly, real-time indicator. An assessment of its performance as an approximation of the medium to long-run GDP growth, both in terms of fitting and turning-point signaling, is provided.

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Publisher Info
Paper provided by University of Modena and Reggio E., Dept. of Economics in its series Center for Economic Research (RECent) with number 020.

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Length: pages 47
Date of creation: May 2008
Date of revision:
Handle: RePEc:mod:recent:020

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Related research
Keywords: Coincident Indicator; Band-pass Filter; Large-dataset Factor Models; Generalized Principal Components;

Other versions of this item:

Find related papers by JEL classification:
C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
O30 - Economic Development, Technological Change, and Growth - - Technological Change - - - General

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References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
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Full references

Cited by:
(explanations, Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.)

  1. Massimiliano Marcellino & Christian Schumacher, 2008. "Factor-MIDAS for Now- and Forecasting with Ragged-Edge Data: A Model Comparison for German GDP," Economics Working Papers ECO2008/16, European University Institute. [Downloadable!]
    Other versions:
  2. Ard den Reijer, 2007. "Identifying Regional and Sectoral Dynamics of the Dutch Staffing Labour Cycle," DNB Working Papers 153, Netherlands Central Bank, Research Department. [Downloadable!]
  3. Beate Schirwitz, 2009. "A comprehensive German business cycle chronology," Empirical Economics, Springer, vol. 37(2), pages 287-301, October. [Downloadable!] (restricted)
  4. Proietti, Tommaso, 2008. "Estimation of Common Factors under Cross-Sectional and Temporal Aggregation Constraints: Nowcasting Monthly GDP and its Main Components," MPRA Paper 6860, University Library of Munich, Germany. [Downloadable!]
  5. Andrea Carriero & Massimiliano Marcellino, 2007. "Monitoring the Economy of the Euro Area: A Comparison of Composite Coincident Indexes," Working Papers 319, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University. [Downloadable!]
  6. Jonas Dovern & Christina Ziegler, 2008. "Predicting Growth Rates and Recessions. Assessing U.S. Leading Indicators Under Real-Time Conditions," Kiel Working Papers 1397, Kiel Institute for the World Economy. [Downloadable!]
    Other versions:
  7. Marta Banbura & Gerhard Rünstler, 2007. "A look into the factor model black box - publication lags and the role of hard and soft data in forecasting GDP," Working Paper Series 751, European Central Bank. [Downloadable!]
  8. Riccardo Cristadoro & Fabrizio Venditti & Giuseppe Saporito, 2008. "Forecasting inflation and tracking monetary policy in the euro area - does national information help?," Working Paper Series 900, European Central Bank. [Downloadable!]
    Other versions:
  9. Maximo Camacho & Gabriel Perez-Quiros, 2008. "Introducing the EURO-STING: Short Term INdicator of Euro Area Growth," Banco de España Working Papers 0807, Banco de España. [Downloadable!]
    Other versions:
  10. Mark W. Watson, 2007. "How accurate are real-time estimates of output trends and gaps?," Economic Quarterly, Federal Reserve Bank of Richmond, issue Spr, pages 143-161. [Downloadable!]
  11. Barhoumi, K. & Rünstler, G. & Cristadoro, R. & Den Reijer, A. & Jakaitiene, A. & Jelonek, P. & Rua, A. & Ruth, K. & Benk, S. & Van Nieuwenhuyze, C., 2008. "Short-term forecasting of GDP using large monthly datasets: a pseudo real-time forecast evaluation exercise," Documents de Travail 215, Banque de France. [Downloadable!]
    Other versions:
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