Abstract
The single spatial parameter in the spatial autoregressive model affects both the estimation of spillovers and the estimation of spatial disturbances. Consequently, the spatial autoregressive model has the undesirable property that if the degree of spatial dependence in the disturbances differs from that in the spillovers, neither may be estimated correctly. We show theoretically that the dependence structure for the spillovers and disturbances can differ and conduct a Monte Carlo experiment that verifies these findings. In contrast, estimates from a simple separable model show little bias in all the scenarios. We also show differences between the spatial autoregressive model and the separable model on five empirical examples.
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Notes
To maintain simplicity, we keep s as permanent and do not explore letting s be independent over time and space as that would create more scenarios to examine. However, this could certainly be done.
We used Louisiana because it is one of the first states with data releases in the 2010 Census and because more effort than normal was spent in data collection due to concerns about population loss after Katrina.
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Pace, R.K., Zhu, S. Separable spatial modeling of spillovers and disturbances. J Geogr Syst 14, 75–90 (2012). https://doi.org/10.1007/s10109-011-0155-7
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DOI: https://doi.org/10.1007/s10109-011-0155-7