Jiangtao Duan, Wei Gao, Hao Qu, Hon Keung Tony
arXiv 22 Sep 2019 · Econometrics · publishedCanadian Journal of Statistics (2021)
arXiv:1909.09928 · PDF · DOI · OpenAlex · Extracted main text
In this paper, a statistical model for panel data with unobservable grouped factor structures which are correlated with the regressors and the group membership can be unknown. The factor loadings are assumed to be in different subspaces and the subspace clustering for factor loadings are considered. A method called least squares subspace clustering estimate (LSSC) is proposed to estimate the model parameters by minimizing the least-square criterion and to perform the subspace clustering simultaneously. The consistency of the proposed subspace clustering is proved and the asymptotic properties of the estimation procedure are studied under certain conditions. A Monte Carlo simulation study is used to illustrate the advantages of the proposed method. Further considerations for the situations that the number of subspaces for factors, the dimension of factors and the dimension of subspaces are unknown are also discussed. For illustrative purposes, the proposed method is applied to study the linkage between income and democracy across countries while subspace patterns of unobserved factors and factor loadings are allowed.
appendix boundary found by none_found · 100% of the source is main text. Read the extracted text to check this.
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.
| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | Ando, T. & Bai, J. S (2016) 11em\ Panel data models with grouped factor structure under unknown group membership | 1.000 | 8 | 4 | 100% |
| 2 | Bai, J. S (2009) 11em\ Panel data models with interactive fixed effects | 1.000 | 6 | 5 | 100% |
| 3 | Bonhomme S. & Manresa E (2015) 11em\ Grouped patterns of heterogeneity in panel data | 1.000 | 5 | 4 | 100% |
| 4 | Liu, G., Lin, Z., Yan, S., Sun, J., Yu, Y. & Ma, Y (2013) 11em\ Robust recovery of subspace structures by low-rank representation | 0.644 | 4 | 1 | 100% |
| 5 | Bai, J. S. & Ng, S (2019) 11em\ Rank regularized estimation of approximate factor models | 0.644 | 2 | 2 | 100% |
| 6 | Su, L., Shi, Z. & Phillips, P. C. B (2016) 11em\ Identifying latent structures in panel data | 0.644 | 2 | 2 | 100% |
| Bai \& Ng | unmatched citation key Bai \& Ng | 0.511 | 2 | 1 | 100% |
| 8 | Su, L. & Ju, G. S (2018) 11em\ Identifying latent grouped patterns in panel data models with interactive fixed effects | 0.511 | 2 | 1 | 100% |
| Vidal \& Sastry | unmatched citation key Vidal \& Sastry | 0.511 | 2 | 1 | 100% |
| 10 | Vidal, M. Y. R. & Sastry, S (2005) 11em\ Generalized principal component analysis (gpca) | 0.511 | 2 | 1 | 100% |
Showing the top 10 of 45 scored citations. 2 of these could not be matched to a bibliography entry, so only the citation key is shown.