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Likelihood ratio test for structural changes in factor models

Jushan Bai, Jiangtao Duan, Xu Han

arXiv 16 Jun 2022 · Econometrics · publishedJournal of Econometrics (2024) · 14 citations (OpenAlex)

arXiv:2206.08052 · PDF · DOI · OpenAlex · Extracted main text

Abstract

A factor model with a break in its factor loadings is observationally equivalent to a model without changes in the loadings but a change in the variance of its factors. This effectively transforms a structural change problem of high dimension into a problem of low dimension. This paper considers the likelihood ratio (LR) test for a variance change in the estimated factors. The LR test implicitly explores a special feature of the estimated factors: the pre-break and post-break variances can be a singular matrix under the alternative hypothesis, making the LR test diverging faster and thus more powerful than Wald-type tests. The better power property of the LR test is also confirmed by simulations. We also consider mean changes and multiple breaks. We apply the procedure to the factor modelling and structural change of the US employment using monthly industry-level-data.

Citation extraction

37
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appendix boundary found by appendix_titled_section at “\textit{Appendix}” · 63% of the source is main text. Read the extracted text to check this.

Most heavily cited references

The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.

ReferenceIntensityMentionsSectionsMain text
1Han, X., Inoue, A (2015) Tests for parameter instability in dynamic factor models self0.64422100%
2Ahn, S. and Horenstein, A (2013) Eigenvalue ratio test for the number of factors0.51121100%
3Bai, J (2010) Common breaks in means and variances for panel data self0.51121100%
4Caner, M. and Han, X (2014) Selecting the Correct Number of Factors in Approximate Factor Models: The Large Panel Case With Group Bridge Estimators self0.51121100%
5Onatski, A (2010) Determining the Number of Factors from Empirical Distribution of Eigenvalues0.51121100%
6Andrews, D.W.K (1993) Tests for parameter instability and structural change with unknown change point0.40511100%
7Bai, J. and Ng, S (2002) Determining the number of factors in approximate factor models self0.40511100%
8Chen, L., Dolado, J.J. and Gonzalo, J (2014) Detecting big structural breaks in large factor models0.40511100%
9Qu, Z. and Perron, P (2007) Estimating and Testing Structural Changes in Multivariate Regressions0.40511100%
Baiunmatched citation key Bai0.000410%

Showing the top 10 of 39 scored citations. 1 of these could not be matched to a bibliography entry, so only the citation key is shown.

Cited by, within the corpus

arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.

Citing paperIntensityMentionsSections
1Disentangling Structural Breaks in Factor Models for Macroeconomic Data0.84333
2Taxonomy and Estimation of Multiple Breakpoints in High-Dimensional Factor Models0.51121
3Structural Analysis of Vector Autoregressive Models0.40511