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BIAS REDUCTION FOR DYNAMIC NONLINEAR PANEL MODELS WITH FIXED EFFECTS
Abstract
The fixed effects estimator of panel models can be severely biased because of well-known incidental parameter problems. It is shown that this bias can be reduced in nonlinear dynamic panel models. We consider asymptotics where n and T grow at the same rate as an approximation that facilitates comparison of bias properties. Under these asymptotics, the bias-corrected estimators we propose are centered at the truth, whereas fixed effects estimators are not. We discuss several examples and provide Monte Carlo evidence for the small sample performance of our procedure.
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Citations
Cited by
Split-panel Jackknife Estimation of Fixed-effect Models
Dhaene, G., & Jochmans, K. (2015) · The Review of Economic Studies · doi:10.1093/restud/rdv007 · Cited by 417
(2016) · doi:10.1016/j.jeconom.2015.12.014 · Cited by 319
Identifying Latent Structures in Panel Data
Su, L., Shi, Z., & Phillips, P. C. B. (2016) · Econometrica · doi:10.3982/ecta12560 · Cited by 265
Metadata
- Authors
- Hahn, J., & Kuersteiner, G.
- Venue
- Econometric Theory
- Publisher
- Cambridge University Press (CUP)
- Published
- 2011-05-31
- Volume
- 27
- Issue
- 6
- Pages
- 1152-1191
- ISSN
- 0266-4666 (ISSN-L)
- 1469-4360
- OpenAlex
- W2072134758
- Cited by
- 210
- References
- 0
- FWCI
- 30.59
- Type
- journal article
- Language
- en
- Open access
- closed
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- The paper
- Hahn, J., & Kuersteiner, G. (2011). BIAS REDUCTION FOR DYNAMIC NONLINEAR PANEL MODELS WITH FIXED EFFECTS. Econometric Theory. https://doi.org/10.1017/s0266466611000028
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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