The dataset I'm using contains income data per area. The values are not normally distributed as shown in the following diagram. Global Moran's I indicates significant spatial patterns and Local Moran's I finds significant hot and cold spots (according to the p-value). When I check the z-score, it turns out that the cold spots don't reach significant levels. Could this be due to the distribution of income values? Is there anything I should do differently? Maybe use the log income?
Or can I simply ignore the z-score as long as th p-values are fine (= significant, < 0.05)?
(Using PySAL to compute both Global and Local Moran's I.)
Here's the histogram of log incomes:
I've recently aquired another income data set from a different country in which income values are normally distributed. Local Moran's I computations for this dataset result in significant hot and cold spots according to both p-value and z-score: