Resolved-EXIOBASE (REX) – A highly resolved MRIO database for analyzing supply-chain impacts (A. Code and data from 2006–2015)

This repository provides the code and the R-MRIO database for the years 2006–2015 of the study "A highly resolved MRIO database for analyzing environmental footprints and Green Economy Progress":

https://doi.org/10.1016/j.scitotenv.2020.142587

The R-MRIO database for the years 1995–2005 is stored under the repository http://doi.org/10.5281/zenodo.3994795

The folder "R-MRIO_CODE" provides the code to resolve the spatial resolution of EXIOBASE3 from 44 countries and 5 Rest of the World (RoW) regions into 189 individual countries while keeping the high sectoral resolution (163 sectors) by the integration of data from Eora26, FAOSTAT and previous studies. It implements the environmental impact categories climate change impacts, particulate-matter related health impacts, water stress and land-use related biodiversity loss into EXIOBASE3, Eora26 and the resolved MRIO database.
The folder includes:
Exiobase_resolved.m: MATLAB code to resolve the EXIOBASE3 database according to the procedure described in Section 2.3–2.6 of the manuscript.
Folder ‘Files’: Includes all files required to run ‘Exiobase_resolved.m’, except for the MRIO tables from EXIOBASE3 and Eora26, which need to be downloaded from the EXIOBASE3 and Eora26 homepage and stored in the provided folder “Files/Exiobase/” and “Files/Eora/bp/”, respectively. These data can be downloaded from:
https://www.exiobase.eu/index.php/data-download/exiobase3mon
https://worldmrio.com/eora26/

The folders "Year_RMRIO" provide the R-MRIO database for each year from 2006–2015. Each folder contains the following files (*.mat-files):
A_RMRIO: the coefficient matrix
Y_RMRIO: the final demand matrix
Ext_RMRIO and Ext_hh_RMRIO: the satellite matrix of the economy and the final demand
TotalOut_RMRIO: the total output vector
The labels of the matrices are provided by the separate folder "Labels_RMRIO "

A script for importing and indexing the RMRIO database files in Python as Pandas DataFrames can be found here:

https://github.com/jbnsn/RMRIO-database-py-import