Detecting big structural breaks in large factor models

Liang Chen, Juan Dolado and Jesus Gonzalo

Journal of Econometrics, 2014, vol. 180, issue 1, 30-48

Abstract: Time invariance of factor loadings is a standard assumption in the analysis of large factor models. Yet, this assumption may be restrictive unless parameter shifts are mild (i.e., local to zero). In this paper we develop a new testing procedure to detect big breaks in these loadings at either known or unknown dates. It relies upon testing for parameter breaks in a regression of one of the factors estimated by Principal Components analysis on the remaining estimated factors, where the number of factors is chosen according to Bai and Ng’s (2002) information criteria. The test fares well in terms of power relative to other recently proposed tests on this issue, and can be easily implemented to avoid forecasting failures in standard factor-augmented (FAR, FAVAR) models where the number of factors is a priori imposed on the basis of theoretical considerations.

Keywords: Structural break; Large factor model; Factor loadings; Principal components (search for similar items in EconPapers)
JEL-codes: C12 C33 (search for similar items in EconPapers)
Date: 2014
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (87)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0304407614000189
Full text for ScienceDirect subscribers only

Related works:
Working Paper: Detecting Big Structural Breaks in Large Factor Models (2013)
Working Paper: Detecting big structural breaks in large factor models (2011)
Working Paper: Detecting big structural breaks in large factor models (2011)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:econom:v:180:y:2014:i:1:p:30-48

DOI: 10.1016/j.jeconom.2014.01.006

Access Statistics for this article

Journal of Econometrics is currently edited by T. Amemiya, A. R. Gallant, J. F. Geweke, C. Hsiao and P. M. Robinson

More articles in Journal of Econometrics from Elsevier
Bibliographic data for series maintained by Catherine Liu ().