Identification theory for high dimensional static and dynamic factor models

Jushan Bai and Peng Wang

Journal of Econometrics, 2014, vol. 178, issue 2, 794-804

Abstract: High dimensional factor models can involve thousands of parameters. The Jacobian matrix for identification is of a large dimension. It can be difficult and numerically inaccurate to evaluate the rank of such a Jacobian matrix. We reduce the identification problem to a small rank problem, which is easy to check. The identification conditions allow both linear and nonlinear restrictions. Under reasonable assumptions for high dimensional factor models, the small rank conditions are shown to be necessary and sufficient for local identification.

Keywords: High dimensional dynamic factor models; Identification; Rank conditions (search for similar items in EconPapers)
JEL-codes: C30 C33 C38 (search for similar items in EconPapers)
Date: 2014
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (27)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:econom:v:178:y:2014:i:2:p:794-804

DOI: 10.1016/j.jeconom.2013.11.001

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