Chengwang Liao, Ziwei Mei, Zhentao Shi
arXiv 13 Oct 2024 · Econometrics
arXiv:2410.09825 · PDF · DOI · OpenAlex · Extracted main text
In panel predictive regressions with persistent covariates, coexistence of the Nickell bias and the Stambaugh bias imposes challenges for hypothesis testing. This paper introduces a new estimator, the IVX-X-Jackknife (IVXJ), which effectively removes this composite bias and reinstates standard inferential procedures. The IVXJ estimator is inspired by the IVX technique in time series. In panel data where the cross section is of the same order as the time dimension, the bias of the baseline panel IVX estimator can be corrected via an analytical formula by leveraging an innovative X-Jackknife scheme that divides the time dimension into the odd and even indices. IVXJ is the first procedure that achieves unified inference across a wide range of modes of persistence in panel predictive regressions, whereas such unified inference is unattainable for the popular within-group estimator. Extended to accommodate long-horizon predictions with multiple regressions, IVXJ is used to examine the impact of debt levels on financial crises by panel local projection. Our empirics provide comparable results across different categories of debt.
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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 | Han, C., P. C. B. Phillips, and D. Sul (2014) X-differencing and dynamic panel model estimation | 1.000 | 7 | 3 | 100% |
| 2 | Kostakis, A., T. Magdalinos, and M. P. Stamatogiannis (2015) Robust econometric inference for stock return predictability | 0.843 | 4 | 3 | 75% |
| 3 | Mei, Z., L. Sheng, and Z. Shi (2023) Nickell bias in panel local projection: Financial crises are worse than you think self | 0.843 | 3 | 3 | 100% |
| 4 | Dhaene, G. and K. Jochmans (2015) Split-panel jackknife estimation of fixed-effect models | 0.737 | 3 | 2 | 100% |
| 5 | Hahn, J. and W. Newey (2004) Jackknife and analytical bias reduction for nonlinear panel models | 0.737 | 3 | 2 | 100% |
| 6 | Jordà, Ò (2005) Estimation and inference of impulse responses by local projections | 0.737 | 3 | 2 | 100% |
| 7 | Stambaugh, R. F (1999) Predictive regressions | 0.737 | 3 | 2 | 100% |
| 8 | Phillips, P. C. B. and H. R. Moon (1999) Linear regression limit theory for nonstationary panel data | 0.659 | 14 | 5 | 29% |
| 9 | Greenwood, R., S. G. Hanson, A. Shleifer, and J. A. Srensen (2022) Predictable financial crises | 0.644 | 4 | 1 | 100% |
| 10 | Campbell, J. Y. and M. Yogo (2006) Efficient tests of stock return predictability | 0.644 | 2 | 2 | 100% |
Showing the top 10 of 59 scored citations.
arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.
| Citing paper | Intensity | Mentions | Sections | |
|---|---|---|---|---|
| 1 | Nickell Bias in Panel Local Projection: Financial Crises Are Worse Than You Think$^$ | 0.511 | 4 | 2 |