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Efficient GMM estimation of spatial dynamic panel data models with fixed effects

Lung-Fei Lee and Jihai Yu (jihai.yu@gmail.com)

Journal of Econometrics, 2014, vol. 180, issue 2, 174-197

Abstract: In this paper we derive the asymptotic properties of GMM estimators for the spatial dynamic panel data model with fixed effects when n is large, and T can be large, but small relative to n. The GMM estimation methods are designed with the fixed individual and time effects eliminated from the model, and are computationally tractable even under circumstances where the ML approach would be either infeasible or computationally complicated. The ML approach would be infeasible if the spatial weights matrix is not row-normalized while the time effects are eliminated, and would be computationally intractable if there are multiple spatial weights matrices in the model; also, consistency of the MLE would require T to be large and not small relative to n if the fixed effects are jointly estimated with other parameters of interest. The GMM approach can overcome all these difficulties. We use exogenous and predetermined variables as instruments for linear moments, along with several levels of their neighboring variables and additional quadratic moments. We stack up the data and construct the best linear and quadratic moment conditions. An alternative approach is to use separate moment conditions for each period, which gives rise to many moments estimation. We show that these GMM estimators are nT consistent, asymptotically normal, and can be relatively efficient. We compare these approaches on their finite sample performance by Monte Carlo.

Keywords: Spatial autoregression; Dynamic panels; Fixed effects; Generalized method of moment; Many moments (search for similar items in EconPapers)
JEL-codes: C13 C23 R15 (search for similar items in EconPapers)
Date: 2014
References: Add references at CitEc
Citations: View citations in EconPapers (85)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:econom:v:180:y:2014:i:2:p:174-197

DOI: 10.1016/j.jeconom.2014.03.003

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Journal of Econometrics is currently edited by T. Amemiya, A. R. Gallant, J. F. Geweke, C. Hsiao and P. M. Robinson

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