Estimation and Inference of Change Points in High Dimensional Factor Models

Bai, Jushan; Han, Xu; Shi, Yutang

doi:10.2139/ssrn.2875193

Cited by 15 publications

(33 citation statements)

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“…We also show that our break date estimator is robust to potential structural changes in the factor loadings, a phenomenon recently considered by Stock and Watson (), Breitung and Eickmeier (), Chen, Dolado, and Gonzalo (), Yamamoto and Tanaka (), Cheng, Liao, and Schorfheide (), Bai, Han, and Shi (), and Ma and Su (), to name a few. Since the CCE approach used in this paper wipes out factors instead of estimating them directly, structural changes in factor loadings do not affect the consistency of our estimators.…”

Section: Introductionsupporting

confidence: 61%

Structural changes in heterogeneous panels with endogenous regressors

Baltagi

Feng

Kao

2019

J of Applied Econometrics

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Summary This paper extends Pesaran's (Econometrica, 2006, 74, 967–1012) common correlated effects (CCE) by allowing for endogenous regressors in large heterogeneous panels with unknown common structural changes in slopes and error factor structure. Since endogenous regressors and structural breaks are often encountered in empirical studies with large panels, this extension makes Pesaran's CCE approach empirically more appealing. In addition to allowing for slope heterogeneity and cross‐sectional dependence, we find that Pesaran's CCE approach is also valid when dealing with unobservable factors in the presence of endogenous regressors and structural changes in slopes and error factor loadings. This is supported by Monte Carlo experiments.

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Section: Introductionsupporting

confidence: 61%

Structural changes in heterogeneous panels with endogenous regressors

Baltagi

Feng

Kao

2019

J of Applied Econometrics

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“…Breitung and Eickmeier (2011), Chen et al (2014), Han and Inoue (2015), Yamamoto and Tanaka (2015) and Barigozzi and Trapani (2017) develop statistical tools to detect breaks. Chen (2015), Cheng, Liao and Schorfheide (2016), Bai, Han and Shi (2017) and Baltagi, Kao and Wang (2017) focus on estimation under the single break assumption. Baltagi, Kao and Wang (2016), Ma and Su (2016) and Barigozzi, Cho and Fryzlewicz (2018) allow for multiple breaks.…”

Section: Introductionmentioning

confidence: 99%

Unstable Diffusion Indexes: With an Application to Bond Risk Premia

Massacci

2019

Oxf Bull Econ Stat

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This paper studies the empirically relevant problem of estimation and inference in diffusion index forecasting models with structural instability. Factor model and factor augmented regression both experience a structural change with different unknown break dates. In the factor model, we estimate factors and loadings by principal components. We consider least squares estimation of the factor augmented regression and propose a break test. The empirical application uncovers instabilities in the linkages between bond risk premia and macroeconomic factors.

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“…Regarding high dimensional time series change point analysis, Jirak (2015) provides a framework to test the mean change using CUSUM statistics. Notably for factor models, there are also many recent articles on estimating loading changes, such as Cheng et al (2016) using shrinkage methods and Bai et al (2016) focusing on establishing the asymptotic distribution of the LS estimator for a structural break.…”

Section: Introductionmentioning

confidence: 99%

Dynamic Semiparametric Factor Model with a Common Break

Chen

Wang

2018

SSRN Journal

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For change-point analysis of high dimensional time series, we consider a semiparametric model with dynamic structural break factors. The observations are described by a few low dimensional factors with time-invariate loading functions of covariates. The unknown structural break in time models the regime switching effects introduced by exogenous shocks. In particular, the factors are assumed to be nonstationary and follow a Vector Autoregression (VAR) process with a structural break. In addition, to account for the known spatial discrepancies, we introduce discrete loading functions. We study the theoretical properties of the estimates of the loading functions and the factors. Moreover, we provide both the consistency and the asymptotic convergence results for making inference on the common breakpoint in time. The estimation precision is evaluated via a simulation study. Finally we present two empirical illustrations on modeling the dynamics of the minimum wage policy in China and analyzing a limit order book dataset.

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Estimation and Inference of Change Points in High Dimensional Factor Models

Cited by 15 publications

References 50 publications

Structural changes in heterogeneous panels with endogenous regressors

Structural changes in heterogeneous panels with endogenous regressors

Unstable Diffusion Indexes: With an Application to Bond Risk Premia

Dynamic Semiparametric Factor Model with a Common Break

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