EXPLORATORY SPATIAL ANALYSIS OF HOUSING PRICES OBTAINED FROM WEB SCRAPING TECHNIQUE

Abstract

The exploratory spatial analysis allows to describe patterns of spatial distribution, to identify clusters and outliers through specific techniques of spatial association and data model. The objective of the study is to verify the spatial autocorrelation between the mean prices of the housing obtained from web scraping technique in online platforms in the city of Salvador, on the coast of northeast Brazil. For this purpose, the Global Moran’s Index (which provides a general measure of association) and the Local Index of Spatial Association (LISA) were calculated. The results of Global Moran’s Index indicate positive autocorrelation between the mean prices of housing prices in the 163 districts of the municipally that are statistically significant, such as identification of clusters through LISA. Thus, the analysis allows to conclude the existence of a heterogeneous pattern in the distribution of these mean prices in the urban space of Salvador.