Jungjun Choi, Hyukjun Kwon, Yuan Liao
arXiv 31 Jul 2023 · Econometrics · publishedJournal of Econometrics (2024) · 5 citations (OpenAlex)
arXiv:2307.16370 · PDF · DOI · OpenAlex · Extracted main text
This paper studies the inferential theory for estimating low-rank matrices. It also provides an inference method for the average treatment effect as an application. We show that the least square estimation of eigenvectors following the nuclear norm penalization attains the asymptotic normality. The key contribution of our method is that it does not require sample splitting. In addition, this paper allows dependent observation patterns and heterogeneous observation probabilities. Empirically, we apply the proposed procedure to estimating the impact of the presidential vote on allocating the U.S. federal budget to the states.
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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 | Chen, Y., Fan, J., Ma, C., and Yan, Y (2019) Inference and uncertainty quantification for noisy matrix completion | 1.000 | 8 | 3 | 100% |
| 2 | Chernozhukov, V., Hansen, C., Liao, Y., and Zhu, Y (2021) Inference for low-rank models self | 1.000 | 5 | 4 | 100% |
| 3 | Chernozhukov, V., Hansen, C. B., Liao, Y., and Zhu, Y (2019) Inference for heterogeneous effects using low-rank estimations self | 0.928 | 4 | 4 | 100% |
| 4 | Chen, Y., Chi, Y., Fan, J., Ma, C., and Yan, Y (2020) Noisy matrix completion: Understanding statistical guarantees for convex relaxation via nonconvex optimization | 0.811 | 4 | 2 | 100% |
| 5 | Imbens, G. W. and Rubin, D. B (2015) Causal inference in statistics, social, and biomedical sciences | 0.644 | 2 | 2 | 100% |
| 6 | Jin, S., Miao, K., and Su, L (2021) On factor models with random missing: Em estimation, inference, and cross validation | 0.644 | 2 | 2 | 100% |
| 7 | Xia, D. and Yuan, M (2021) Statistical inferences of linear forms for noisy matrix completion | 0.644 | 2 | 2 | 100% |
| 8 | Xiong, R. and Pelger, M (2020) Large dimensional latent factor modeling with missing observations and applications to causal inference. arxiv eprint | 0.644 | 2 | 2 | 100% |
| 9 | Cox, G. W. and McCubbins, M. D (1986) Electoral politics as a redistributive game | 0.585 | 3 | 1 | 100% |
| 10 | Larcinese, V., Rizzo, L., and Testa, C (2006) Allocating the us federal budget to the states: The impact of the president | 0.585 | 3 | 1 | 100% |
Showing the top 10 of 37 scored citations.
arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.
| Citing paper | Intensity | Mentions | Sections | |
|---|---|---|---|---|
| 1 | Inference for Low-rank Models without Estimating the Rank | 0.928 | 4 | 3 |
| 2 | 0.5cmLow-Rank Estimation of Nonlinear Panel Data Models | 0.644 | 2 | 2 |
| 3 | When can weak latent factors be statistically inferred? | 0.405 | 1 | 1 |