Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/189725 
Year of Publication: 
2018
Series/Report no.: 
cemmap working paper No. CWP22/18
Publisher: 
Centre for Microdata Methods and Practice (cemmap), London
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.
Subjects: 
panel data
fixed effects
incidental parameter problem
bias correction
unobserved heterogeneity
nonlinear models
jackknife
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

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