The impact of the weight matrix on the local indicators of spatial association: an application to per-capita value added in Italy

Making use of the local Moran index and taking as a case study the value added per capita in 103 Italian provinces in 2005, this work investigates how local measures of spatial association are affected by the use of different algorithms to calculate the weights of spatial matrices. We find that three methods we applied (adjacency, K-nn and MaxMin) provide very similar results at the global spatial level. Instead, considering the local spatial analysis, we note some differences in spatial outliers identification.