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EuroMInd-C: a Disaggregate Monthly Indicator of Economic Activity for the Euro Area and member countries

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Author Info

  • Cecilia Frale

    ()
    (Ministry of the Economy and Finance)

  • Stefano Grassi

    ()
    (University of Kent and CREATES)

  • Massimiliano Marcellino

    ()
    (EUI Florence)

  • Gianluigi Mazzi

    ()
    (EUROSTAT)

  • Tommaso Proietti

    ()
    (University of Rome "Tor Vergata")

Abstract

The paper deals with the estimation of monthly indicators of economic activity for the Euro area and its largest member countries that possess the following attributes: relevance, representativeness and timeliness. Relevance is obtained by referring our monthly indicators to gross domestic product at chained volumes, the most important measure of the level of economic activity. Representativeness is achieved by entertaining a very large number of (timely) time series on monthly indicators relating to the level of economic activity, providing a more or less complete coverage. The indicators are modelled with a large scale parametric factor model. We discuss its specification and provide details on the statistical treatment. Computational efficiency is crucial to estimate a large scale parametric factor model of the dimension considered in our application (considering about 170 series). To achieve it we apply state of the art state space methods that can handle temporal aggregation, and any pattern of missing values.

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File URL: ftp://www.ceistorvergata.it/repec/rpaper/RP287.pdf
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Bibliographic Info

Paper provided by Tor Vergata University, CEIS in its series CEIS Research Paper with number 287.

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Length: 40 pages
Date of creation: 01 Oct 2013
Date of revision: 01 Oct 2013
Handle: RePEc:rtv:ceisrp:287

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Postal: CEIS - Centre for Economic and International Studies - Faculty of Economics - University of Rome "Tor Vergata" - Via Columbia, 2 00133 Roma
Phone: +390672595601
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Web page: http://www.ceistorvergata.it
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Postal: CEIS - Centre for Economic and International Studies - Faculty of Economics - University of Rome "Tor Vergata" - Via Columbia, 2 00133 Roma
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Web: http://www.ceistorvergata.it

Related research

Keywords: Index of coincident indicators; Temporal Disaggregation; Multivariate State Space Models; Dynamic factor Models; Quarterly National accounts;

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References

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  1. Mario Forni & Marc Hallin & Marco Lippi & Lucrezia Reichlin, 2003. "The Generalized Dynamic Factor Model. One-Sided Estimation and Forecasting," LEM Papers Series, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy 2003/13, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
  2. Cecilia Frale & Massimiliano Marcellino & Gian Luigi Mazzi & Tommaso Proietti, 2011. "EUROMIND: a monthly indicator of the euro area economic conditions," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 174(2), pages 439-470, 04.
  3. Filippo Altissimo & Riccardo Cristadoro & Mario Forni & Marco Lippi & Giovanni Veronese, 2007. "New Eurocoin: Tracking Economic Growth in Real Time," Temi di discussione (Economic working papers), Bank of Italy, Economic Research and International Relations Area 631, Bank of Italy, Economic Research and International Relations Area.
  4. Cecilia Frale & Massimiliano Marcellino & Gian Luigi Mazzi & Tommaso Proietti, . "Survey Data as Coincident or Leading Indicators," Working Papers, Department of the Treasury, Ministry of the Economy and of Finance 3, Department of the Treasury, Ministry of the Economy and of Finance.
  5. Mario Forni & Marc Hallin & Lucrezia Reichlin & Marco Lippi, 2000. "The generalised dynamic factor model: identification and estimation," ULB Institutional Repository 2013/10143, ULB -- Universite Libre de Bruxelles.
  6. Neil Shephard & Gabriele Fiorentini & Enrique Sentana, 2003. "Likelihood-based estimation of latent generalised ARCH structures," FMG Discussion Papers, Financial Markets Group dp453, Financial Markets Group.
  7. Doz, Catherine & Giannone, Domenico & Reichlin, Lucrezia, 2011. "A two-step estimator for large approximate dynamic factor models based on Kalman filtering," Journal of Econometrics, Elsevier, Elsevier, vol. 164(1), pages 188-205, September.
  8. Tommaso Proietti, 2011. "Estimation of Common Factors under Cross‐Sectional and Temporal Aggregation Constraints," International Statistical Review, International Statistical Institute, International Statistical Institute, vol. 79(3), pages 455-476, December.
  9. Roberto S. Mariano & Yasutomo Murasawa, 2010. "A Coincident Index, Common Factors, and Monthly Real GDP," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 72(1), pages 27-46, 02.
  10. Maximo Camacho & Gabriel Perez-Quiros, 2008. "Introducing the EURO-STING: Short Term INdicator of Euro Area Growth," Banco de Espa�a Working Papers 0807, Banco de Espa�a.
  11. Forni, Mario, et al, 2001. "Coincident and Leading Indicators for the Euro Area," Economic Journal, Royal Economic Society, Royal Economic Society, vol. 111(471), pages C62-85, May.
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  13. Kose, M. Ayhan & Otrok, Christopher & Prasad, Eswar, 2008. "Global Business Cycles: Convergence or Decoupling?," IZA Discussion Papers 3442, Institute for the Study of Labor (IZA).
  14. Tommaso Proietti & Filippo Moauro, 2006. "Dynamic factor analysis with non-linear temporal aggregation constraints," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 55(2), pages 281-300.
  15. Roberto S. Mariano & Yasutomo Murasawa, 2003. "A new coincident index of business cycles based on monthly and quarterly series," Journal of Applied Econometrics, John Wiley & Sons, Ltd., John Wiley & Sons, Ltd., vol. 18(4), pages 427-443.
  16. Stock, J.H. & Watson, M.W., 1989. "New Indexes Of Coincident And Leading Economic Indicators," Papers, Harvard - J.F. Kennedy School of Government 178d, Harvard - J.F. Kennedy School of Government.
  17. Bańbura, Marta & Modugno, Michele, 2010. "Maximum likelihood estimation of factor models on data sets with arbitrary pattern of missing data," Working Paper Series, European Central Bank 1189, European Central Bank.
  18. B. Jungbacker & S.J. Koopman & M. van der Wel, 2009. "Dynamic Factor Analysis in The Presence of Missing Data," Tinbergen Institute Discussion Papers 09-010/4, Tinbergen Institute, revised 11 Mar 2011.
  19. Andrew Harvey & Chia-Hui Chung, 2000. "Estimating the underlying change in unemployment in the UK," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 163(3), pages 303-309.
  20. Stock, James H & Watson, Mark W, 2002. "Macroeconomic Forecasting Using Diffusion Indexes," Journal of Business & Economic Statistics, American Statistical Association, American Statistical Association, vol. 20(2), pages 147-62, April.
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