Nickell Bias in Panel Local Projection: Financial Crises Are Worse Than You Think
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arXiv
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| Natura: | Preprint |
| Pubblicazione: |
2023
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| _version_ | 1866915713154809856 |
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| author | Mei, Ziwei Sheng, Liugang Shi, Zhentao |
| author_facet | Mei, Ziwei Sheng, Liugang Shi, Zhentao |
| contents | Panel local projection (LP) with fixed-effects (FE) is widely adopted for evaluating the economic consequences of financial crises across countries. This paper highlights a fundamental methodological issue: the presence of the Nickell bias in the panel FE estimator due to inherent dynamic structures of predictive specifications, even if the regressors have no lagged dependent variables. The Nickell bias invalidates the standard inferential procedure based on the $t$-statistic. We propose a split-panel jackknife (SPJ) estimator as a simple, easy-to-implement, and yet effective solution to eliminate the bias and restore valid statistical inference. We revisit four influential empirical studies on the impact of financial crises, and find that the FE method underestimates the economic losses of financial crises relative to the SPJ estimates. Replication files are available at https://metricshilab.github.io/panel-lp-replication/, with links to R and Stata packages. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2302_13455 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Nickell Bias in Panel Local Projection: Financial Crises Are Worse Than You Think Mei, Ziwei Sheng, Liugang Shi, Zhentao Econometrics Panel local projection (LP) with fixed-effects (FE) is widely adopted for evaluating the economic consequences of financial crises across countries. This paper highlights a fundamental methodological issue: the presence of the Nickell bias in the panel FE estimator due to inherent dynamic structures of predictive specifications, even if the regressors have no lagged dependent variables. The Nickell bias invalidates the standard inferential procedure based on the $t$-statistic. We propose a split-panel jackknife (SPJ) estimator as a simple, easy-to-implement, and yet effective solution to eliminate the bias and restore valid statistical inference. We revisit four influential empirical studies on the impact of financial crises, and find that the FE method underestimates the economic losses of financial crises relative to the SPJ estimates. Replication files are available at https://metricshilab.github.io/panel-lp-replication/, with links to R and Stata packages. |
| title | Nickell Bias in Panel Local Projection: Financial Crises Are Worse Than You Think |
| topic | Econometrics |
| url | https://arxiv.org/abs/2302.13455 |