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EuroMInd-C: a Disaggregate Monthly Indicator of Economic Activity for the Euro

Author

Listed:
  • Stefano Grassi
  • Tommaso Proietti
  • Cecilia Frale
  • Massimiliano Marcellino
  • Gianluigi Mazzi

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 for estimating 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

  • Stefano Grassi & Tommaso Proietti & Cecilia Frale & Massimiliano Marcellino & Gianluigi Mazzi, 2014. "EuroMInd-C: a Disaggregate Monthly Indicator of Economic Activity for the Euro," Studies in Economics 1406, School of Economics, University of Kent.
    • Handle: RePEc:ukc:ukcedp:1406
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    File URL: https://www.kent.ac.uk/economics/repec/1406.pdf
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    Citations

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    Cited by:

    1. Laura Bisio & Filippo Moauro, 2018. "Temporal disaggregation by dynamic regressions: Recent developments in Italian quarterly national accounts," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 72(4), pages 471-494, November.
    2. Joan Paredes & Javier J. Pérez & Gabriel Perez Quiros, 2023. "Fiscal targets. A guide to forecasters?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(4), pages 472-492, June.
    3. María Gil & Javier J. Pérez & Alberto Urtasun, 2019. "Nowcasting private consumption: traditional indicators, uncertainty measures, credit cards and some internet data," IFC Bulletins chapters, in: Bank for International Settlements (ed.), The use of big data analytics and artificial intelligence in central banking, volume 50, Bank for International Settlements.

    More about this item

    Keywords

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

    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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