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A monthly indicator of Economic activity for Luxembourg

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  • Muriel Nguiffo-Boyom

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    Abstract

    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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    Bibliographic Info

    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

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    Web page: http://www.bcl.lu/

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    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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    1. Mario Forni & Marc Hallin & Marco Lippi & Lucrezia Reichlin, 2005. "The generalised dynamic factor model: one sided estimation and forecasting," ULB Institutional Repository 2013/10129, ULB -- Universite Libre de Bruxelles.
    2. 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.
    3. Domenico Giannone & Troy Matheson, 2007. "A new core inflation indicator for New Zealand," ULB Institutional Repository 2013/6407, ULB -- Universite Libre de Bruxelles.
    4. Massimiliano Marcellino, 2005. "Leading Indicators: What Have We Learned?," Working Papers 286, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    5. 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.
    6. Christian Schumacher, 2007. "Forecasting German GDP using alternative factor models based on large datasets," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 26(4), pages 271-302.
    7. 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.
    8. Martin Schneider & Martin Spitzer, 2004. "Forecasting Austrian GDP using the generalized dynamic factor model," Working Papers 89, Oesterreichische Nationalbank (Austrian Central Bank).
    9. 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.
    10. 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.
    11. 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.
    12. 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.
    13. 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 Monetary Affairs (DG ECFIN), European Commission.
    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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