Common breaks in means and variances for panel data

By Jushan Bai. 2010

291 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/f4c7a2238d898a73831c0f4d92f98677be053928

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In Economics and Econometrics

Citations in the corpus

Inference for single and multiple change‐points in time series (2013, methodology): “Bai (2000, 2010) took advantage of the quasi-likelihood technique so as to estimate change-points not only in the mean vector but also in the variance–covariance matrix of multivariate observations.”
Sieve Estimation of Time-Varying Panel Data Models With Latent Structures (2019, background): “For this reason, numerous studies have been devoted to test for structural changes in panel data models; see Han and Park (1989), Bai and Lluís Carrion-I-Silvestre (2009), Bai (2010), Kim (2011), Chen and Huang (2014), Li, Qian, and Su (2016), and Qian and Su (2016), among others. On the other hand,”
Change‐point detection in panel data (2012, methodology): “Csörg} o and Horváth, 1997; Brodsky and Darkhovskii, 2000) but much less is known on the stability of panel models. Change point detection in panel data can be viewed as a structural stability problem in high dimensional time series. Joseph and Wolfson (1992, 1993) initiated change point models for ”
Testing for Factor Loading Structural Change under Common Breaks (2015, background): “Bai (2010) discusses several examples of common breaks in panel data models.”
Structural Breaks in Interactive Effects Panels and the Stock Market Reaction to COVID-19 (2021, methodology): “Bai (2010) is the only other article that we are aware of that proves consistency under both fixed and large T; however, his model is very simple in that it does not contain any regressors except for a breaking constant.”
Extensions of some classical methods in change point analysis (2014, methodology): “Bai (2010) estimates the time of change with t̂N ,T = T argmaxx N∑ i=1 1 σ 2i Z2T,i (x) T x (T − T x ) and obtains the distribution of the normalized difference between t0 and t̂N ,T assuming that γi = 0 for all 1 ≤ i ≤ N , i.e. the panels are independent.”
Estimation and identification of change points in panel models with nonstationary or stationary regressors and error term (2017, unknown): “As discussed in Bai (2010), “Theoretically, common break is a more restrictive assumption than the random breaks of Joseph and Wolfson (1993).”
Shrinkage estimation of common breaks in panel data models via adaptive group fused Lasso (2016, unknown): “Implicitly, one usually allows to pass to infinity in panel data models.1 Most of the literature falls into two categories depending on whether the parameters of interest are allowed to be heterogenous across individuals or not.”
Selective review of offline change point detection methods (2020, background): “From a theoretical point of view, piecewise linear models are extensively studied in the context of change point detection by a series of important contributions [14, 67–71, 73–77].”
Identification and estimation of a large factor model with structural instability (2017, methodology): “parts (5), (6), (7), (8) and (9) can be proved following the same procedure.”
Estimation of Panel Group Structure Models with Structural Breaks in Group Memberships and Coefficients (2020, unknown): “This condition is often imposed for detecting breaks with time series data, but not with panel data (see, e.g. Bai, 2010; Qian and Su, 2016; Okui and Wang, 2021).”
A review of change point detection methods (2018, methodology): “This formulation encompasses a large number of change point models [1, 14, 32–34, 72, 81, 99, 100, 115, 125].”