On the other hand, in statistical or econometrics analysis based on
data geographically referenced there are two types of spatial effects
that are of particular interest as they have a considerable influence:
spatial dependence and spatial heterogeneity. Spatial dependence is
usually described by spatial autocorrelation using statistics such as
Moran's index. Spatial heterogeneity relates with spatial differentiation,
which follows the intrinsic uniqueness of each location, and it can occur
in the form of different distributions in different subsets, i.e., data nonstationary
(Anselin, 1998). Exploratory Spatial Data Analysis (ESDA)
focuses explicitly on these spatial effects