Publication Type
Journal Article
Version
acceptedVersion
Publication Date
2-2014
Abstract
This paper introduces a new estimation method for dynamic panel models with fixed effects and AR(p) idiosyncratic errors. The proposed estimator uses a novel form of systematic differencing, called X-differencing, that eliminates fixed effects and retains information and signal strength in cases where there is a root at or near unity. The resulting "panel fully aggregated" estimator (PFAE) is obtained by pooled least squares on the system of X-differenced equations. The method is simple to implement, consistent for all parameter values, including unit root cases, and has strong asymptotic and finite sample performance characteristics that dominate other procedures, such as bias corrected least squares, generalized method of moments (GMM), and system GMM methods. The asymptotic theory holds as long as the cross section (n) or time series (T) sample size is large, regardless of the n/T ratio, which makes the approach appealing for practical work. In the time series AR(1) case (n = 1), the FAE estimator has a limit distribution with smaller bias and variance than the maximum likelihood estimator (MLE) when the autoregressive coefficient is at or near unity and the same limit distribution as the MLE in the stationary case, so the advantages of the approach continue to hold for fixed and even small n. Some simulation results are reported, giving comparisons with other dynamic panel estimation methods.
Keywords
Maximum Likelihood Estimation, Unit Root, Time Series, Limit Theory, Matrix Estimator, Error Components, Inference, Covariance, Regression, Autoregression
Discipline
Econometrics
Research Areas
Econometrics
Publication
Econometric Theory
Volume
30
First Page
201
Last Page
251
ISSN
0266-4666
Identifier
10.1017/S0266466613000170
Publisher
Cambridge University Press
Embargo Period
7-17-2017
Citation
HAN, Chirok; PHILLIPS, Peter C. B.; and SUL, Donggyu.
X-differencing and dynamic panel model estimation. (2014). Econometric Theory. 30, 201-251.
Available at: https://ink.library.smu.edu.sg/soe_research/1971
Copyright Owner and License
Authors
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1017/S0266466613000170