In the construction of a leading indicator model of economic activity, economists must select among a pool of variables which lead output growth. Usually the pool of variables is large, and selection of a subset must be carried out. In this paper we propose an `Automatic Leading Indicator' model. Rather than preselection, we use a dynamic factor model to summarise the information content of a pool of variables. Results show that the forecasting performance of our 'Automatic Leading Indicator' model is significantly better than that of traditional model selection criteria with VAR models. This study is carried out using quaterly data for France, Germany, Italy and the United Kingdom.
Download Info
To download:
If you experience problems downloading a file, check if you have the
proper application to
view it first. Information about this may be contained
in the File-Format links below. In case of further problems read
the IDEAS help
file. Note that these files are not on the IDEAS
site. Please be patient as the files may be large.
Publisher Info
Paper provided by National Institute of Economic and Social Research in its series NIESR Discussion Papers with number
149.
References listed on IDEAS Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.: