Baltagi, Badi H. and Kao, Chihwa and Wang, Fa (2016): Estimating and testing high dimensional factor models with multiple structural changes.

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Abstract
This paper considers multiple changes in the factor loadings of a high dimensional factor model occurring at dates that are unknown but common to all subjects. Since the factors are unobservable, the problem is converted to estimating and testing structural changes in the second moments of the pseudo factors. We consider both joint and sequential estimation of the change points and show that the distance between the estimated and the true change points is Op(1). We find that the estimation error contained in the estimated pseudo factors has no effect on the asymptotic properties of the estimated change points as the crosssectional dimension N and the time dimension T go to infinity jointly. No NT ratio condition is needed. We also propose (i) tests for the null of no change versus the alternative of l changes (ii) tests for the null of l changes versus the alternative of l + 1 changes, and show that using estimated factors asymptotically has no effect on their limit distributions if √T/N→0. These tests allow us to make inference on the presence and number of structural changes. Simulation results show good performance of the proposed procedure. In an application to US quarterly macroeconomic data we detect two possible breaks.
Item Type:  MPRA Paper 

Original Title:  Estimating and testing high dimensional factor models with multiple structural changes 
English Title:  Estimating and testing high dimensional factor models with multiple structural changes 
Language:  English 
Keywords:  factor model, multiple changes, model selection, panel data 
Subjects:  C  Mathematical and Quantitative Methods > C1  Econometric and Statistical Methods and Methodology: General > C13  Estimation: General C  Mathematical and Quantitative Methods > C3  Multiple or Simultaneous Equation Models ; Multiple Variables > C33  Panel Data Models ; Spatiotemporal Models 
Item ID:  98489 
Depositing User:  Dr Fa Wang 
Date Deposited:  05 Feb 2020 19:59 
Last Modified:  05 Feb 2020 19:59 
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URI:  https://mpra.ub.unimuenchen.de/id/eprint/98489 