Publication Type

Working Paper

Version

publishedVersion

Publication Date

9-2014

Abstract

It is well known that (quasi) MLE of dynamic panel data (DPD) models with short panels depends on the assumptions on the initial values; ignoring them or a wrong treatment of them will result in inconsistency or serious bias. This paper introduces a initial-condition free method for estimating the fixed-effects DPD models, through as simple modification of the quasi-score. An outer-product-of-gradients (OPG) method is also proposed for robust inference. The MLE of Hsiao, Pesaran and Tahmiscioglu (2002, Journal of Econometrics), where the initial observations are modeled, is extended to quasi MLE and an OPG method is proposed for robust inference. Consistency and asymptotic normality for both estimation strategies are established, and the two methods are compared through Monte Carlo simulations. The proposed method performs well in general, whether the panel is short or not. The quasi MLE performs comparably, except when model does not contain time-varying regressor, or the panel is not short and the dynamic parameter is small. The proposed method is much simpler and easier to apply.

Keywords

Bias reduction, Consistency, Asymptotic normality, Dynamic panel, Fixed effects, Modified quasi-score, Robust standard error, Short panel

Discipline

Econometrics

Research Areas

Econometrics

First Page

1

Last Page

34

Publisher

SMU Economics and Statistics Working Paper Series, No. 16-2014

City or Country

Singapore

Copyright Owner and License

Authors

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