Jiti Gao, Fei Liu, Bin Peng, Yayi Yan
arXiv 6 Dec 2020 · Econometrics · publishedJournal of Econometrics (2023) · 13 citations (OpenAlex)
arXiv:2012.03182 · PDF · DOI · OpenAlex · Extracted main text
In this paper, we investigate binary response models for heterogeneous panel data with interactive fixed effects by allowing both the cross-sectional dimension and the temporal dimension to diverge. From a practical point of view, the proposed framework can be applied to predict the probability of corporate failure, conduct credit rating analysis, etc. Theoretically and methodologically, we establish a link between a maximum likelihood estimation and a least squares approach, provide a simple information criterion to detect the number of factors, and achieve the asymptotic distributions accordingly. In addition, we conduct intensive simulations to examine the theoretical findings. In the empirical study, we focus on the sign prediction of stock returns, and then use the results of sign forecast to conduct portfolio analysis.
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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 | Wang (2020) `Maximum likelihood estimation and inference for high dimensional nonlinear factor models with application to factor-augmented r… | 1.000 | 8 | 3 | 100% |
| 2 | Boneva \ Linton (2017) `A discrete-choice model for large heterogeneous panels with interactive fixed effects with an application to the determinants o… | 1.000 | 7 | 4 | 100% |
| 3 | Christoffersen \ Diebold (2006) `Financial asset returns, direction-of-change forecasting, and volatility dynamics', Management Science 52(8), 1273–1287 | 1.000 | 6 | 3 | 100% |
| 4 | Fan, Liao \ Mincheva (2013) `Large covariance estimation by thresholding principal orthogonal complements', Journal of the Royal Statistical Society: Series… | 1.000 | 5 | 3 | 100% |
| 5 | Moon \ Weidner (2015) `Linear regression for panel with unknown number of factors as interactive fixed effects', Econometrica 83(4), 1543–1579 | 0.950 | 7 | 4 | 86% |
| 6 | Bai \ Ng (2013) `Principal components estimation and identification of static factors', Journal of Econometrics 176(1), 18–99 | 0.928 | 4 | 3 | 100% |
| 7 | Bai (2009) `Panel data models with interactive fixed effects', Econometrica 77(4), 1229–1279 | 0.909 | 12 | 4 | 75% |
| 8 | Engle, Ledoit \ Wolf (2019) `Large dynamic covariance matrices', Journal of Business & Economic Statistics 37(2), 363–375 | 0.874 | 9 | 2 | 100% |
| 9 | Pelger \ Xiong (2021) `State-varying factor models of large dimensions', Journal of Business & Economic Statistics p. forthcoming | 0.874 | 6 | 2 | 100% |
| 10 | Bai \ Ng (2002) `Determining the number of factors in approximate factor models', Econometrica 70(1), 191–221 | 0.874 | 5 | 2 | 100% |
Showing the top 10 of 55 scored citations.
arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.
| Citing paper | Intensity | Mentions | Sections | |
|---|---|---|---|---|
| 1 | Bootstrap Inference in Nonlinear Panel Data Models with Interactive Fixed Effects | 1.000 | 7 | 4 |
| 2 | 2507.16462 | 0.843 | 4 | 3 |
| 3 | Common Correlated Effects Estimation of Nonlinear Panel Data Models | 0.811 | 4 | 2 |
| 4 | Threshold Regression in Heterogeneous Panel Data with Interactive Fixed Effects | 0.405 | 1 | 1 |
| 5 | 0.5cmLow-Rank Estimation of Nonlinear Panel Data Models | 0.405 | 1 | 1 |