Clustered Panel Data Models: An Efficient Approach for Nowcasting from Poor Data
CORE Discussion Paper No. 2003/90
30 Pages Posted: 23 Apr 2007
Date Written: December 2003
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.
Keywords: panel data, forecast, nowcast, missing data, clustering, R&D data
JEL Classification: C23, C51, C53
Suggested Citation: Suggested Citation
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