The course starts with an introduction into spatial data analysis including basic tools to capture the spatial structure and to generate descriptive statistics. Given that backgound we focus on spatial regression models, in particular, on models with residual spatial autocorrelation and with spatial autoregressive or interaction effects. Various estimation tools are explained and discussed, including Maximum Likelihood estimation, Instrumental Variable and Generalized Methods of Moments Estimation, we will also deal with spatial effects in panel data. Moreover, the course reviews software options and gives hints in programming resources. Finally, the course illustrates the methods in a pratical exercise, which deals with spatial interaction vs. residual spatial autocorrelation in local taxation.
Economists, Regional Scientists and Geographers, Ph.D Students in Economics and Geography with interest in empirical research