S-maup: Statistic test to measure the sensitivity to the Modifiable Areal Unit Problem

TL;DR

This paper introduces S-maup, a novel nonparametric statistical test designed to measure how sensitive spatial variables are to the Modifiable Areal Unit Problem (MAUP), which affects spatial data analysis.

Contribution

It presents the first statistic of its kind to assess the impact of MAUP on spatial variables, including its design, critical values, and empirical validation.

Findings

Power increases with larger sample sizes

Size decreases as the number of areas increases

Empirical application demonstrates practical utility

Abstract

This work presents a nonparametric statistical test, $S$-maup, to measure the sensitivity of a spatially intensive variable to the effects of the Modifiable Areal Unit Problem (MAUP). $S$-maup is the first statistic of its type and focuses on determining how much the distribution of the variable, at its highest level of spatial disaggregation, will change when it is spatially aggregated. Through a computational experiment, we obtain the basis for the design of the statistical test under the null hypothesis of non-sensitivity to MAUP. We performed a simulation study for approaching the empirical distribution of the statistical test, obtaining its critical values, and computing its power and size. The results indicate that the power of the statistic is good if the sample (number of areas) grows, and in general, the size decreases with increasing sample number. Finally, an empirical application is made using the Mincer equation in South Africa.