Open Risk Academy Course: Input-Output Models with Python

A DeepDive Course into using Python to work with Input-Output Models

Page content

What are Input-Output Models?

Environmentally Extended Multi-Regional Input-Output (EE MRIO) tables describe economic relationships of economic actors (e.g. industrial sectors) operating within and between regions and their environmental repercussions.

IO System

An EE MRIO augments the more basic and historically first proposed Input-Output Models (IO) with additional datasets and/or modeling assumptions in order to provide insights into the environmental foorprint of economic activity. Presently, the emphasis on negative externalities of economic activity (e.g., climate change, biodiversity loss) turns EE MRIO models into a useful conceptual and analytic tool. Yet a good grounding on the underlying IO models is a prerequisite and this is the focus of this new course that is now available at the Open Risk Academy.

Course Content:

This course is a DeepDive with nine segments, exploring Input-Output models using Python and the pymrio library.

Who Is This Course For:

The course is at a core technical level.

  • It requires working familiarity with python
  • Basic linear algebra and
  • Elements of economic systems.

How Does The Course Help:

Step by step we explore how one can define and perform useful operations in Input-Output Analysis. Mastering the course content provides background knowledge towards the following activities:

  • Improved understanding of Input-Output Models and in particular computational aspects in the Python ecosystem
  • Laying the groundwork for working with Environmental Extended Input-Output models

What Will You Get From The Course:

  • get exposed to the concept and structure of Input-Output Models
  • create a variety of stylized IO models in Python
  • perform basic IO related workflows as those are facilitated by the pymrio package

Course Level and Difficulty Level:

This course is part of the new Sustainable Finance family.

The course requires some prior knowledge of python (and indeed prior programming knowledge in some language is required), basic linear algebra (linear systems, matrices) and (very) basic economics.

If you have not taken an Open Risk Academy course before, the CrashCourse Academy Demo provides a quick overview of the Academy.

Course Material:

The course material comprises the following:

  • Nine interactive readings (Lessons) with exercises dispersed throughout
  • Accompanying code that is available in the course github repo

Time Requirements and Important Dates

  • The course is self-paced and can be undertaken at any point. Depending on your background knowledge it requires a commitment of a few days to work out through the examples and suggested exercises.

Where To Get Help:

If you get stuck on any issue with the course or the Academy:

  • If the issue is related to the course topics / material, check in the first instance the Course Forum (Chat)
  • If the issue is related the operation of the Open Risk Academy check first the Academy FAQ.
  • If the issue persists contact us at

Check out other Academy Courses