It is well known that quasi maximum likelihood (QML) estimation of dynamic panel data (DPD) models with short panels depends on the assumptions on the initial values, and a wrong treatment of them will result in inconsistency and serious bias. The same issues apply to spatial DPD (SDPD) models with short panels. In this paper, a unified Mestimation method is proposed for estimating the fixed-effects SDPD models containing three major types of spatial effects, namely spatial lag, spatial error and space-time lag. The method is free from the specification of the distribution of the initial observations and robust against nonnormality of the errors. Consistency and asymptotic normality of the proposed M-estimator are established. A martingale difference representation of the underlying estimating functions is developed, which leads to an initial condition free estimate of the variance of the M-estimators. Monte Carlo results show that the proposed methods have excellent finite sample performance.
Adjusted quasi score, Dynamic panels, Fixed effects, Initial-condition free estimation, Martingale difference, Spatial effects, Short panels
Unified M-Estimation of Fixed-Effects Spatial Dynamic Models with Short Panels. (2015). Research Collection School Of Economics.
Available at: http://ink.library.smu.edu.sg/soe_research/1783
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