Though standard spatial econometric models may be useful for specification testing, they rely heavily on a parametric structure that is highly sensitive to model misspecification. The commonly used spatial AR model is a form of spatial smoothing with a structure that closely resembles a semiparametric model. Nonparametric and semiparametric models are generally a preferable approach for more descriptive spatial analysis. Estimated population density functions illustrate the differences between the spatial AR model and nonparametric approaches to data smoothing. A series of Monte Carlo experiments demonstrates that nonparametric predicted values and marginal effect estimates are much more accurate then spatial AR models when the contiguity matrix is misspecified.
ASJC Scopus subject areas
- Environmental Science (miscellaneous)