Estimation of Spatial Panel Data Models Using a Minimum Distance Estimator: Application
نویسنده
چکیده
This paper is concerned with modelling and estimating panel data autoregressive spatial processes in the framework of minimum distance methods. A contiguity matrix based on distance between points relates observations spatially. The model is estimated in two stages. First, the cross-section parameters are consistently estimated by maximum likelihood, and a consistent asymptotic covariance matrix is computed for the second stage. Minimum distance estimators are derived under xed slopes and all identical parameters restrictions. We used this speci cation to examine empirically spatial patterns of residential water demand for the French department of "Moselle", including electricity price e ects.
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