These codes were used to analyse the interplay of subnational Gini coefficient and GNI per capita at the global scale. It is part of the following publication. Please do cite this paper when using the codes.
Chrisendo D, Niva V, Hoffman R, Sayyar SM, Rocha J, Sandström V, Solt F, Kummu M. 2024. Income inequality has increased for over two-thirds of the global population. Preprint. doi: https://doi.org/10.21203/rs.3.rs-5548291/v1
To run the code, you first need to run the following codes:
Gini coefficient data creation: https://github.com/mattikummu/subnatGini
GNI per capita data creation: https://github.com/mattikummu/subnatGNI
The code is numbered with the order it should be run. Below each code is briefly explained. We used R (version 4.3.2) to develop the code.
0_install_packages.R: install the needed packages
1_gini_gni_bins.R: creates the Gini - GNI bins
2_gini_gni_groups: creates and plots the Gini - GNI combination groups
3_plot_gini_gni_bins.R: plots the bins
4_fuzzy_clustering.R: performs the fuzzy clustering
5_urban_gini_analysis.R: code for the urban gini analysis
functions: the functions used in the scripts above are in this folder
For more information, please contact Matti Kummu (matti.kummu@aalto.fi)