Nonparametric Estimation of the Spatial Connectivity Matrix Using Spatial Panel Data

We use moments from the covariance matrix for spatial panel data to estimate the param-eters of the spatial autoregression model, including the spatial connectivity matrix W. In the unrestricted spatial autoregression model, the parameters are underidentified by one when W is symmetric. We show that a special case exists in which W is asymmetric and its parameters are exactly identified. If the panel data are stationary and ergodic, spatially and temporally, the estimates of W and the spatial autoregression coefficients are consistent. Spatial panel data for house prices in Israel are used to illustrate this methodology. When observations are available over time as well as across space, these constraints (on W) can be relaxed. In the particular case where the time dimension is larger than the spatial dimension, a spatial weight matrix is no longer necessary... (Anselin 1988, p. 176