Chen, Liang and Dolado, Juan Jose and Gonzalo, Jesus (2011): Detecting big structural breaks in large factor models.
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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.
|Item Type:||MPRA Paper|
|Original Title:||Detecting big structural breaks in large factor models|
|Keywords:||structural break; large factor model|
|Subjects:||C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C12 - Hypothesis Testing: General
C - Mathematical and Quantitative Methods > C3 - Multiple or Simultaneous Equation Models; Multiple Variables > C33 - Models with Panel Data; Longitudinal Data; Spatial Time Series
|Depositing User:||Liang Chen|
|Date Deposited:||08. Jun 2011 12:52|
|Last Modified:||15. Feb 2013 03:47|
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