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Detecting big structural breaks in large factor models

  • Chen, Liang
  • Dolado, Juan Jose
  • Gonzalo, Jesus

Constant factor loadings is a standard assumption in the analysis of large dimensional factor models. Yet, this assumption may be restrictive unless parameter shifts are mild. In this paper we develop a new testing procedure to detect big breaks in factor loadings at either known or unknown dates. It is based upon testing for structural breaks in a regression of the first of the ¯r factors estimated by PC for the whole sample on the remaining r−1 factors, where r is chosen using Bai and Ng´s (2002) information criteria. We argue that this test is more powerful than other tests available in the literature on this issue.

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File URL: http://mpra.ub.uni-muenchen.de/31344/1/MPRA_paper_31344.pdf
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Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 31344.

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Date of creation: 08 Jun 2011
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Handle: RePEc:pra:mprapa:31344
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