Code and processed data for: Can Energy Sufficiency Corridors Be Reconciled with Carbon and Material Limits? A Scenario Analysis of Social-Ecological Position in the Global North and South

This record contains the Python code and processed data used in the article "Can Energy Sufficiency Corridors Be Reconciled with Carbon and Material Limits? A Scenario Analysis of Social-Ecological Position in the Global North and South" (submitted to Energy Reports). The code estimates a primary-energy sufficiency corridor (Z_L, Z_U) from social-outcome curves for 214 countries in seven regions over 2000–2022, constructs the Social-Ecological Position Index (SEPI), projects the trend-continuation and sufficiency pathways to 2060 under a 1.5 °C carbon budget and a material-footprint ceiling, and runs the Monte Carlo, cluster-bootstrap, sensitivity and Shapley decomposition analyses reported in the article. Contents:- SEIP_Zenodo.ipynb / SEIP.py: analysis code (Jupyter notebook and Python script versions).- Input and processed data files used by the code (see README.txt for the list and sources).- README.txt: file descriptions, sources and instructions. To reproduce the results, place all files in one folder and run the notebook from top to bottom. Notes: One-off extraction cells that read the full AR6 Scenarios Database (R10 regions, v1.1; Byers et al., 2022) have been removed, because that database is not redistributed here owing to its size; the extracted files (ar6_r10_*.csv) are provided. Retired cells not used in the article (AR6 category C3 and the transition-speed parameter theta) have also been removed.