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Clustered panel data models: an efficient approach for nowcasting from poor data

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  • MOUCHART, Michel
  • ROMBOUTS, Jeroen

Abstract

Nowcasting regards the inference on the present realization of random variables, on the basis of information available until a recent past. This paper proposes a modelling strategy aimed at a best use of the data for nowcasting based on panel data with severe deficiencies, namely short times series and many missing data. The basic idea consists of introducing a clustering approach into the usual panel data model specification. A case study in the field of R&D variables illustrates the proposed modelling strategy.

Suggested Citation

  • MOUCHART, Michel & ROMBOUTS, Jeroen, 2003. "Clustered panel data models: an efficient approach for nowcasting from poor data," LIDAM Discussion Papers CORE 2003090, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    • Handle: RePEc:cor:louvco:2003090
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    References listed on IDEAS

    as
    1. Clemen, Robert T., 1989. "Combining forecasts: A review and annotated bibliography," International Journal of Forecasting, Elsevier, vol. 5(4), pages 559-583.
    2. Jan R. Magnus & Dmitry Danilov, 2004. "Forecast accuracy after pretesting with an application to the stock market," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 23(4), pages 251-274.
    3. Hendry, David F. & Clements, Michael P., 2003. "Economic forecasting: some lessons from recent research," Economic Modelling, Elsevier, vol. 20(2), pages 301-329, March.
    4. David F. Hendry & Michael P. Clements, 2004. "Pooling of forecasts," Econometrics Journal, Royal Economic Society, vol. 7(1), pages 1-31, June.
    5. Marcellino, Massimiliano & Stock, James H. & Watson, Mark W., 2003. "Macroeconomic forecasting in the Euro area: Country specific versus area-wide information," European Economic Review, Elsevier, vol. 47(1), pages 1-18, February.
    6. Islam, Towhidul & Fiebig, Denzil G. & Meade, Nigel, 2002. "Modelling multinational telecommunications demand with limited data," International Journal of Forecasting, Elsevier, vol. 18(4), pages 605-624.
    Full references (including those not matched with items on IDEAS)

    Citations

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    Cited by:

    1. Baltagi, Badi H., 2013. "Panel Data Forecasting," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 995-1024, Elsevier.
    2. Badi H. Baltagi, 2008. "Forecasting with panel data," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(2), pages 153-173.
    3. A. Mahabbati & A. Izady & M. Mousavi Baygi & K. Davary & S. M. Hasheminia, 2017. "Daily soil temperature modeling using ‘panel-data’ concept," Journal of Applied Statistics, Taylor & Francis Journals, vol. 44(8), pages 1385-1401, June.

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    More about this item

    Keywords

    panel data; forecast; nowcast; missing data; clustering; R&D data;
    All these keywords.

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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