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QML estimation of spatial dynamic panel data models with endogenous time varying spatial weights matrices

Xi Qu, Lung-Fei Lee () and Jihai Yu ()

Journal of Econometrics, 2017, vol. 197, issue 2, 173-201

Abstract: In spatial panel data models, when a spatial weights matrix is constructed from economic or social distance, spatial weights could be endogenous and also time varying. This paper presents model specification and proposes QMLE estimation of spatial dynamic panel data models with endogenous time varying spatial weights matrices. Asymptotic properties of the proposed QMLE are rigorously established. We extend the notion of spatial near-epoch dependence to allow time dependence. By using spatial-time LLN for near-epoch dependence process and CLT for martingale difference sequence, we establish the consistency and asymptotic normality of QMLE. Monte Carlo experiments show that the proposed estimators have satisfactory finite sample performance.

Keywords: Spatial autoregression; Dynamic panels; Fixed effects; Endogenous spatial weights matrix; QMLE (search for similar items in EconPapers)
JEL-codes: C13 C23 R15 (search for similar items in EconPapers)
Date: 2017
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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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Handle: RePEc:eee:econom:v:197:y:2017:i:2:p:173-201