Information, data dimension and factor structure

Vol: 
15/2011
Author name: 
Jacobs JPAM
Otter PW
den Reijer AHJ
Year: 
2011
Month: 
June
Abstract: 

This paper employs concepts from information theory to choosing the dimension of a data set. We propose a relative information measure connected to Kullback-Leibler numbers. By ordering the series of the data set according to the measure, we are able to obtain a subset of a data set that is most informative. The method can be used as a first step in the construction of a dynamic factor model or a leading index, as illustrated with a Monte Carlo study and with the U.S. macroeconomic data set of Stock and Watson [22].

Publication file: 

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