Fixed effects estimation of large-T panel data models
Files
Accepted manuscript
Date
2018-01-01
Authors
Fernandez-Val, Ivan
Weidner, Martin
Version
OA Version
Accepted manuscript
Citation
Ivan Fernandez-Val, Martin Weidner. 2018. "Fixed Effects Estimation of Large-T Panel Data Models." ANNUAL REVIEW OF ECONOMICS, VOL 10, Volume 10, pp. 109 - 138 (30). https://doi.org/10.1146/annurev-economics-080217-053542
Abstract
This article reviews recent advances in fixed effect estimation of panel data models for
long panels, where the number of time periods is relatively large. We focus on semiparametric
models with unobserved individual and time effects, where the distribution of the outcome
variable conditional on covariates and unobserved effects is specified parametrically, while
the distribution of the unobserved effects is left unrestricted. Compared to existing reviews
on long panels (Arellano & Hahn, 2007; a section in Arellano & Bonhomme, 2011) we discuss
models with both individual and time effects, split-panel Jackknife bias corrections, unbalanced
panels, distribution and quantile effects, and other extensions. Understanding and
correcting the incidental parameter bias caused by the estimation of many fixed effects is
our main focus, and the unifying theme is that the order of this bias is given by the simple
formula p/n for all models discussed, with p the number of estimated parameters and n the
total sample size.