首页|Instrumental variable estimation of a spatial dynamic panel model with endogenous spatial weights when T is small
Instrumental variable estimation of a spatial dynamic panel model with endogenous spatial weights when T is small
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NETL
NSTL
Oxford Univ Press
The spatial dynamic panel data (SDPD) model is a standard tool for analysing data with both spatial correlation and dynamic dependences among economic units. Conventional estimation methods rely on the key assumption that the spatial weight matrix is exogenous, which would likely be violated in some empirical applications where spatial weights are determined by economic factors. In this paper, we propose an SDPD model with individual fixed effects in a short time dimension, where the spatial weights can be endogenous and time-varying. We establish the consistency and asymptotic normality of the two-stage instrumental variable (2SIV) estimator and we investigate its finite sample properties using a Monte Carlo simulation. When applying this model to study government expenditures in China, we find strong evidence of spatial correlation and time dependence in making spending decisions among China's provincial governments.
Endogenous spatial weightsFixed effectsPublic ExpenditureSpatial correlationSpatial dynamic panel data model
Qu, Xi、Wang, Xiaoliang、Lee, Lung-fei
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Shanghai Jiao Tong Univ, Antai Coll Econ & Management, 1954 Huashan Rd, Shanghai 200030, Peoples R China
Ohio State Univ, Dept Econ, 410 Arps Hall,1945 N High St, Columbus, OH 43210 USA
NETL
NSTL
Oxford Univ Press
