Clustered panel data models: an efficient approach for nowcasting from poor data
AbstractNowcasting 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.
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Bibliographic InfoArticle provided by Elsevier in its journal International Journal of Forecasting.
Volume (Year): 21 (2005)
Issue (Month): 3 ()
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Web page: http://www.elsevier.com/locate/ijforecast
Other versions of this item:
- MOUCHART, Michel & ROMBOUTS, Jeroen, 2003. "Clustered panel data models: an efficient approach for nowcasting from poor data," CORE Discussion Papers 2003090, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Longitudinal Data; Spatial Time Series
- 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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