Information, data dimension and factor structure

Jan Jacobs, Pieter W. Otter and Ard Reijer ()

CAMA Working Papers from Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University

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].

JEL-codes: C32 C52 C82 (search for similar items in EconPapers)
Pages: 31 pages
Date: 2011-06
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Related works:
Journal Article: Information, data dimension and factor structure (2012)
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Persistent link: https://EconPapers.repec.org/RePEc:een:camaaa:2011-15

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