Some Important Spatial Definitions

The major difference between standard econometrics and spatial econometrics lies in the fact that, in order to treat spatial data, we need two different sets of information. The first is related to the observed values of the economic variables, whereas the second relates to the particular locations where those variables are observed and to the links of proximity between them. This chapter is devoted to a presentation of the basic tools that are necessary to conduct a spatial econometric analysis. First of all, we introduce the spatial weight matrix, a tool that incorporates the information about the links of proximity between the spatial observations; we then use such a definition to introduce the notion of the “spatial lag”, which constitutes an extension of the popular definition of time lag. Based on thee definitions, we then present a test of the spatial autocorrelation among the regression residuals. The chapter ends with the computer codes needed to implement the procedure discussed in the computer  language R, STATA and Python.