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

Author

Listed:
  • 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.

Suggested Citation

  • Cecilia Frale & Stefano Grassi & Massimiliano Marcellino & Gianluigi Mazzi & Tommaso Proietti, 2013. "EuroMInd-C: a Disaggregate Monthly Indicator of Economic Activity for the Euro Area and member countries," CEIS Research Paper 287, Tor Vergata University, CEIS, revised 01 Oct 2013.
  • Handle: RePEc:rtv:ceisrp:287
    as

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    References listed on IDEAS

    as
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    Cited by:

    1. Katja Heinisch & Rolf Scheufele, 2018. "Bottom-up or direct? Forecasting German GDP in a data-rich environment," Empirical Economics, Springer, vol. 54(2), pages 705-745, March.
    2. Bisio, Laura & Moauro, Filippo, 2017. "Temporal disaggregation by dynamic regressions: recent developments in Italian quarterly national accounts," MPRA Paper 80211, University Library of Munich, Germany, revised 14 Jul 2017.

    More about this item

    Keywords

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

    JEL classification:

    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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