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Common stationary and non-stationary factors in the euro area analyzed in a large-scale factor model

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  • Eickmeier, Sandra

Abstract

In this paper we rely on techniques recently developed by Bai and Ng (2004a) to estimate common euro-area stationary and non-stationary factors using a large-scale dynamic factor model. We find that euro-area economies share four non-stationary factors or trends and one stationary factor. By means of rotation techniques, we estimate a euro-area business cycle which is a fairly good match to EuroCOIN, the euro-area coincident business cycle indicator published by the CEPR. Fluctuations of common euro-area factors mainly reflect variations of German and French real economic activity as well as of producer prices and financial prices (long-term interest rates and/or real effective exchange rates) in various countries. As concerns the transmission channels, macroeconomic shocks seem to proliferate in the euro area more strongly through trade, exchange rates and long-term interest rates than through stock prices. Among the external driving forces, shocks to US economic activity seem to be more strongly linked to shocks to the euro-area factors than oil price shocks. We finally find evidence of mild overall convergence; results for individual countries are mixed.

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  • Eickmeier, Sandra, 2005. "Common stationary and non-stationary factors in the euro area analyzed in a large-scale factor model," Discussion Paper Series 1: Economic Studies 2005,02, Deutsche Bundesbank.
  • Handle: RePEc:zbw:bubdp1:2936
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    Cited by:

    1. Eickmeier, Sandra, 2006. "Comovements and heterogeneity in the Comovements and heterogeneity in the dynamic factor model," Discussion Paper Series 1: Economic Studies 2006,31, Deutsche Bundesbank.
    2. Bodha Hannadige, Sium & Gao, Jiti & Silvapulle, Mervyn & Silvapulle, Param, 2021. "Time Series Forecasting using a Mixture of Stationary and Nonstationary Predictors," MPRA Paper 108669, University Library of Munich, Germany, revised 30 Apr 2021.
    3. Eickmeier, Sandra & Breitung, Jörg, 2005. "How synchronized are central and east European economies with the euro area? Evidence from a structural factor model," Discussion Paper Series 1: Economic Studies 2005,20, Deutsche Bundesbank.
    4. Sandra Eickmeier & Joerg Breitung, 2006. "Business cycle transmission from the euro area to CEECs," Computing in Economics and Finance 2006 229, Society for Computational Economics.
    5. Eickmeier, Sandra, 2007. "Business cycle transmission from the US to Germany--A structural factor approach," European Economic Review, Elsevier, vol. 51(3), pages 521-551, April.
    6. Eickmeier, Sandra & Breitung, Jorg, 2006. "How synchronized are new EU member states with the euro area? Evidence from a structural factor model," Journal of Comparative Economics, Elsevier, vol. 34(3), pages 538-563, September.
    7. Sylvia Kaufmann & Christian Schumacher, 2013. "Bayesian estimation of sparse dynamic factor models with order-independent identification," Working Papers 13.04, Swiss National Bank, Study Center Gerzensee.
    8. Zlatina Balabanova & Ralf Brüggemann, 2012. "External Information and Monetary Policy Transmission in New EU Member States: Results from FAVAR Models," Working Paper Series of the Department of Economics, University of Konstanz 2012-05, Department of Economics, University of Konstanz.
    9. Olivier Bandt & Catherine Bruneau & Alexis Flageollet, 2006. "Assessing Aggregate Comovements in France, Germany and Italy Using a Non Stationary Factor Model of the Euro Area," Springer Books, in: Convergence or Divergence in Europe?, pages 95-120, Springer.
    10. Karim Barhoumi & Olivier Darné & Laurent Ferrara, 2014. "Dynamic factor models: A review of the literature," OECD Journal: Journal of Business Cycle Measurement and Analysis, OECD Publishing, Centre for International Research on Economic Tendency Surveys, vol. 2013(2), pages 73-107.
    11. Heather Anderson & Mardi Dungey & Denise Osborn & Farshid Vahid, 2007. "Constructing Historical Euro Area Data," Money Macro and Finance (MMF) Research Group Conference 2006 99, Money Macro and Finance Research Group.
    12. László Békési & Lorant Kaszab & Szabolcs Szentmihályi, 2017. "The EAGLE model for Hungary - a global perspective," MNB Working Papers 2017/7, Magyar Nemzeti Bank (Central Bank of Hungary).
    13. Tibor Szendrei & Katalin Varga, 2020. "FISS – A Factor-based Index of Systemic Stress in the Financial System," Russian Journal of Money and Finance, Bank of Russia, vol. 79(1), pages 3-34, March.
    14. Kaufmann, Sylvia & Schumacher, Christian, 2019. "Bayesian estimation of sparse dynamic factor models with order-independent and ex-post mode identification," Journal of Econometrics, Elsevier, vol. 210(1), pages 116-134.
    15. Sium Bodha Hannadige & Jiti Gao & Mervyn J. Silvapulle & Param Silvapulle, 2020. "Forecasting a Nonstationary Time Series with a Mixture of Stationary and Nonstationary Factors as Predictors," Monash Econometrics and Business Statistics Working Papers 19/20, Monash University, Department of Econometrics and Business Statistics.
    16. Bettina Becker & Stephen G. Hall, 2009. "A new look at economic convergence in Europe: a common factor approach," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 14(1), pages 85-97.
    17. Kappler, Marcus & Schleer, Frauke, 2017. "A financially stressed euro area," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 11, pages 1-37.
    18. Kappler, Marcus & Schleer, Frauke, 2013. "How many factors and shocks cause financial stress?," ZEW Discussion Papers 13-100, ZEW - Leibniz Centre for European Economic Research.

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    More about this item

    Keywords

    Dynamic factor models; factor rotation; common trends; international business cycles; international transmission channels;
    All these keywords.

    JEL classification:

    • C50 - Mathematical and Quantitative Methods - - Econometric Modeling - - - General
    • F40 - International Economics - - Macroeconomic Aspects of International Trade and Finance - - - General
    • F02 - International Economics - - General - - - International Economic Order and Integration
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

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