Spatial Autoregressive Nonlinear Models in R with an Empirical Application in Labour Economics

This chapter covers the extension of the non-linear models that are commonly used in empirical microeconomics to allow for cross-sectional dependence that can be captured via a proximity or spatial weighting matrix. It starts with brief overview of the spatial econometric methods and challenges in the empirical work with spatial data. Next, it proceeds to the detailed analysis of spatial autoregressive nonlinear probit models, including the calculation of marginal effects, with an example of an empirical application in labour economics using available packages in R.