Junting Duan, Markus Pelger, Ruoxuan Xiong
arXiv 29 Aug 2023 · Econometrics · publishedJournal of Econometrics (2023) · 8 citations (OpenAlex)
arXiv:2308.15627 · PDF · DOI · OpenAlex · Extracted main text
This paper develops a novel method to estimate a latent factor model for a large target panel with missing observations by optimally using the information from auxiliary panel data sets. We refer to our estimator as target-PCA. Transfer learning from auxiliary panel data allows us to deal with a large fraction of missing observations and weak signals in the target panel. We show that our estimator is more efficient and can consistently estimate weak factors, which are not identifiable with conventional methods. We provide the asymptotic inferential theory for target-PCA under very general assumptions on the approximate factor model and missing patterns. In an empirical study of imputing data in a mixed-frequency macroeconomic panel, we demonstrate that target-PCA significantly outperforms all benchmark methods.
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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 | Xiong and Pelger (2023) Large dimensional latent factor modeling with missing observations and applications to causal inference | 0.897 | 18 | 8 | 72% |
| 2 | Bai and Ng (2002) Determining the number of factors in approximate factor models | 0.843 | 3 | 3 | 100% |
| 3 | Bai (2003) Inferential theory for factor models of large dimensions | 0.830 | 7 | 4 | 57% |
| 4 | Bai and Ng (2021) Matrix completion, counterfactuals, and factor analysis of missing data | 0.811 | 4 | 2 | 100% |
| 5 | Cahan, Bai, and Ng (2023) Factor-based imputation of missing values and covariances in panel data of large dimensions | 0.811 | 4 | 2 | 100% |
| 6 | Jin, Miao, and Su (2021) On factor models with random missing: EM estimation, inference, and cross validation | 0.737 | 3 | 2 | 100% |
| 7 | Bai and Ng (2023) Approximate factor models with weaker loadings | 0.644 | 2 | 2 | 100% |
| 8 | Huang, Jiang, Li, Tong, and Zhou (2022) Scaled PCA: A new approach to dimension reduction | 0.644 | 2 | 2 | 100% |
| 9 | McCracken and Ng (2016) FRED-MD: A monthly database for macroeconomic research | 0.511 | 2 | 1 | 100% |
| 10 | Chow and Lin (1971) Best linear unbiased interpolation, distribution, and extrapolation of time series by related series | 0.511 | 2 | 1 | 100% |
Showing the top 10 of 38 scored citations.
arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.
| Citing paper | Intensity | Mentions | Sections | |
|---|---|---|---|---|
| 1 | A Nonlinear Target-Factor Model with Attention Mechanism for Mixed-Frequency Data | 0.985 | 23 | 5 |