Eora Documentation

MRIO structure


This workbook shows:

How to cite

To cite Eora work please refer to these papers:

Lenzen M, Kanemoto K; Moran D, and Geschke A (2012) Mapping the structure of the world economy. Environmental Science & Technology 46(15) pp 8374–8381. DOI: 10.1021/es300171x. Supplementary Information

Lenzen, M., Moran, D., Kanemoto, K., Geschke, A. (2013) Building Eora: A Global Multi-regional Input-Output Database at High Country and Sector Resolution. Economic Systems Research, 25:1, 20-49, DOI:10.1080/09535314.2013.769938

How Eora is Built

There are two main academic papers presenting how Eora was constructed. The Supplementary Information for the "Mapping the Structure" paper contains a considerable amount of detail, including which data source(s) were used for building which IO tables.

Lenzen M, Kanemoto K; Moran D, and Geschke A (2012) Mapping the structure of the world economy. Environmental Science & Technology 46(15) pp 8374–8381. DOI: 10.1021/es300171x. Supplementary Information

Lenzen, M., Moran, D., Kanemoto, K., Geschke, A. (2013) Building Eora: A Global Multi-regional Input-Output Database at High Country and Sector Resolution. Economic Systems Research, 25:1, 20-49, DOI:10.1080/09535314.2013.769938

To build Eora we must merge and reconcile multiple, often conflicting, data sources into a single balanced MRIO. This means that the values in Eora should be understood as the mean value with an associated confidence interval. Standard deviations are provided for all Eora values. How confident may we be that the values published in Eora are correct? We provide a white paper on Eora Confidence.

MRIO model intercomparison

Several MRIO models exist. There is variation in the CBA results across models, but this variation is generally considered acceptable. For more on intercomparison see:

D. Moran, Wood, R. (2014) Convergence between the Eora, WIOD, EXIOBASE, and OpenEU's consumption-based carbon accounts. Economic Systems Research. DOI:10.1080/09535314.2014.935298

Or visit our intercomparison results page

Another intercomparison website is the Environmental Footprints Explorer .

Learning MRIO

Below is a list of resources (papers, reports, and video) that can help in learning basic IO analysis.

The MRIO lecture video series by Prof. Lenzen is highly recommended if you are new to IO.

Two commonly used textbooks on IO are Input-Output Analysis: Foundations and Extensions [amazon.com] by Miller and Blair and Handbook of Input-Output Analysis by Thijs ten Raa.

Programming Notes

Reading .mat files in Python

We suggest the pymatreader package for this.

Reading .mat files in R

Normally all .mat files from Eora are saved as HDF5 (Matlab version "7.3") files. Each file contains a single variable which is named "M". Here's an example of how to read HDF5 files in in R and get the variable M:


install.packages("BiocManager")
BiocManager::install("rhdf5")
library(rhdf5)
h5f = H5Fopen("datafile.mat")
myData = h5f$M # Load the data from variable "M"
H5Fclose(h5f)

In case the variable "M" doesn't have the data you can see the list of other items in the file like this:


fileContentListing = h5ls("datafile.mat")
variableName = fileContentListing[1,2] # First variable name

In some (rare) cases our .mat files are saved using the older original .mat format rather than the HDF5 / "v7.3" style. Here's how to read those original .mat files in R:


install.packages("R.matlab")
library(R.matlab)
matContents=readMat("test.mat", drop=c("singletonLists"), sparseMatrixClass="matrix")
myData = matContents[1]

Additional papers

Most of the main papers presenting Eora and Eora-based results are provided above and in the individual applications sections (e.g. for carbon, water, and biodiversity footprints). We have also contributed to a number of additional papers related to the construction or use of MRIOs: