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A monthly indicator of Economic activity for Luxembourg

  • Muriel Nguiffo-Boyom

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    This paper presents a new indicator of economic activity for Luxembourg, developed using a large database of 99 economic and financial time series. The methodology used corresponds to the generalised dynamic-factor models that has been introduced in the literature by Forni et al (2005), and the model as been estimated over the period from June 1995 to June 2007. Several means have been used to evaluate its forecasting performances and results are satisfactory. They in particular give clear evidence that our indicator allows to obtain better forecasts of the GDP growth relative to a more classical approach that relies on GDP past values only. This indicator is calculated on an experimental basis and changes may be integrated.

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    File URL: http://www.bcl.lu/fr/publications/cahiers_etudes/31/BCLWP031.pdf
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    Paper provided by Central Bank of Luxembourg in its series BCL working papers with number 31.

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    Length: 35 pages
    Date of creation: Mar 2008
    Date of revision:
    Handle: RePEc:bcl:bclwop:bclwp031
    Contact details of provider: Web page: http://www.bcl.lu/

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    1. Forni, Mario, et al, 2001. "Coincident and Leading Indicators for the Euro Area," Economic Journal, Royal Economic Society, vol. 111(471), pages C62-85, May.
    2. Martin Schneider & Martin Spitzer, 2004. "Forecasting Austrian GDP using the generalized dynamic factor model," Working Papers 89, Oesterreichische Nationalbank (Austrian Central Bank).
    3. Rünstler, Gerhard, 2002. "The information content of real-time output gap estimates, an application to the euro area," Working Paper Series 0182, European Central Bank.
    4. Domenico Giannone & Troy Matheson, 2006. "A new core inflation indicator for New Zealand," Reserve Bank of New Zealand Discussion Paper Series DP2006/02, Reserve Bank of New Zealand.
    5. Schumacher, Christian, 2005. "Forecasting German GDP using alternative factor models based on large datasets," Discussion Paper Series 1: Economic Studies 2005,24, Deutsche Bundesbank, Research Centre.
    6. Marcellino, Massimiliano, 2005. "Leading Indicators: What Have We Learned?," CEPR Discussion Papers 4977, C.E.P.R. Discussion Papers.
    7. Giannone, Domenico & Reichlin, Lucrezia & Small, David H., 2006. "Nowcasting GDP and inflation: the real-time informational content of macroeconomic data releases," Working Paper Series 0633, European Central Bank.
    8. Mario Forni & Marc Hallin & Marco Lippi & Lucrezia Reichlin, 2003. "The Generalized Dynamic Factor Model. One-Sided Estimation and Forecasting," LEM Papers Series 2003/13, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    9. Hallin, Marc & Liska, Roman, 2007. "Determining the Number of Factors in the General Dynamic Factor Model," Journal of the American Statistical Association, American Statistical Association, vol. 102, pages 603-617, June.
    10. Filippo Altissimo & Antonio Bassanetti & Riccardo Cristadoro & Lucrezia Reichlin & Giovanni Veronese, 2001. "The construction of coincident and leading indicators for the euro area business cycler of the euro area business cycle," Temi di discussione (Economic working papers) 434, Bank of Italy, Economic Research and International Relations Area.
    11. Schumacher, Christian & Breitung, Jörg, 2006. "Real-time forecasting of GDP based on a large factor model with monthly and quarterly data," Discussion Paper Series 1: Economic Studies 2006,33, Deutsche Bundesbank, Research Centre.
    12. Daniel Grenouilleau, 2004. "A sorted leading indicators dynamic (SLID) factor model for short-run euro-area GDP forecasting," European Economy - Economic Papers 219, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission.
    13. Chang-Jin Kim & Charles R. Nelson, 1998. "Business Cycle Turning Points, A New Coincident Index, And Tests Of Duration Dependence Based On A Dynamic Factor Model With Regime Switching," The Review of Economics and Statistics, MIT Press, vol. 80(2), pages 188-201, May.
    14. Christophe Planas & Alessandro Rossi, 2004. "Can inflation data improve the real-time reliability of output gap estimates?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 19(1), pages 121-133.
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