MULTIFRACTAL CHARACTERIZATION OF SPATIAL INCOME CURDLING: THEORY AND APPLICATIONS

A spatial curdling index $(\mathcal{C})$ is presented for studying income concentration in two-dimensional fields originated by a cascade process, resembling resource allocation maps. Computational simulations of spatial distributions show that the relation between $\mathcal{C}$ and measures of income inequality such as the Gini coefficient $(\mathcal{G})$ forms a concave area. Acknowledgment of this fact brings additional information for formulating geopolitical strategies for income inequality reduction, and for comparison purposes in a set of countries or across time within a country. With the aim of showing the importance of index $\mathcal{C}$, a prototype of the empirical application is shown based on the Peruvian and Swedish income maps.