ECON4545 Spatial Econometrics
We will begin at the beginning of spatial analysis, around mid-18th century. The introduction will be at a general level of epidemiology. Then we will slowly move to spatial statistics, spatial econometrics and finally to, spatial urban economics. We will touch on the contrast between time-series and spatial dependence, and the need for moving from linear to non-linear models; from fixed to space varying coefficient models. More specifically, in the context of urban econometrics, we will study the price of housing; we will argue that not only the spatial dependence of house prices, but also the dependence in the variability (risk) of prices need to be considered, leading to non-linear spatial autoregressive conditional heteroskedastic (SARCH) model. The major highlight of the course will be how to test various spatial models, particularly, in the context of possible misspecification.
The theories covered in the course will be illustrated in the computer lab by substantial applications using data from several countries, including Colombia. The aim of the computer lab is to introduce to students the problems related with handling spatial data an2d the properties of the basic econometric models. With hands-on experience, students will have a broad overview of the most recent developments and refinements of the basic models used in spatial econometrics. At the end of the course, students will have acquired the necessary skills to build, estimate and test these models in the R environment.
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