Nickell Meets Stambaugh: A Tale of Two Biases in Panel Predictive Regressions
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| Format: | Preprint |
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2024
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| _version_ | 1866917527287758848 |
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| author | Liao, Chengwang Mei, Ziwei Shi, Zhentao |
| author_facet | Liao, Chengwang Mei, Ziwei Shi, Zhentao |
| contents | In panel predictive regressions with persistent covariates, coexistence of the Nickell bias and the Stambaugh bias imposes challenges for estimation and hypothesis testing. This paper introduces an innovative estimator, the Double IVX (DIVX), inspired by the IVX technique in time series. DIVX effectively removes this composite Nickell-Stambaugh bias and reinstates standard inferential procedures based on the t-statistic. This new procedure achieves unified inference across a wide range of modes of persistence in panel predictive regressions when the cross-sectional dimension and the time dimension are comparably large. Such desirable properties were unattainable by existing methods, including the popular within-group estimator. Extensive Monte Carlo simulations demonstrate the robustness of DIVX under a variety of settings. We apply DIVX to panel data of financial markets in developed economies to examine the predictability of stock returns. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2410_09825 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Nickell Meets Stambaugh: A Tale of Two Biases in Panel Predictive Regressions Liao, Chengwang Mei, Ziwei Shi, Zhentao Econometrics In panel predictive regressions with persistent covariates, coexistence of the Nickell bias and the Stambaugh bias imposes challenges for estimation and hypothesis testing. This paper introduces an innovative estimator, the Double IVX (DIVX), inspired by the IVX technique in time series. DIVX effectively removes this composite Nickell-Stambaugh bias and reinstates standard inferential procedures based on the t-statistic. This new procedure achieves unified inference across a wide range of modes of persistence in panel predictive regressions when the cross-sectional dimension and the time dimension are comparably large. Such desirable properties were unattainable by existing methods, including the popular within-group estimator. Extensive Monte Carlo simulations demonstrate the robustness of DIVX under a variety of settings. We apply DIVX to panel data of financial markets in developed economies to examine the predictability of stock returns. |
| title | Nickell Meets Stambaugh: A Tale of Two Biases in Panel Predictive Regressions |
| topic | Econometrics |
| url | https://arxiv.org/abs/2410.09825 |