Updated Open Risk Academy Course: Input-Output Models with Python

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

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The SFI32064 course is a DeepDive with nine segments, exploring Input-Output models using Python and the Pymrio library. The following is an updated overview of it contents.

  • Define Input-Output models, introduce the Pymrio Python package and setup so as to be able to do the programming exercises
  • Construct the simplest possible IO system, execute the core workflow of standard IO analysis and interpret the results.
  • Construct a slightly more realistic example that will involve two industrial sectors. While still far from adequate for real economies, this case already requires the full matrix machinery for analysis. Examine the complication that emerges when production of goods and services is interconnected via supply chains.
  • Understand better the economic interpretation of the interconnectedness of sectors. Review the mathematics of power series approximations and discuss aspects of mixing Pymrio functionality with the underlying numpy and pandas python packages.
  • Discuss the mechanism for adding Extensions to IO Models. Workout some particular extension examples
  • Look at the economic concepts of Open versus Closed IO Models. In particular discuss the Mathematical Consequences of Closed Models.
  • Introduce the concept of Hybrid IO Models. Discuss some of complications introduced by such generalizations.
  • Introduce and work with a more realistic IO model. Discuss the concept of output multipliers. Learn to save processed IO data in the file system (disk drive).
  • Learn how to import IO data from production EEIO databases like EXIOBASE and OECD-ICIO

Who Is This Course For

The course is at a core technical level.

  • It requires working familiarity with Python (and Pandas).
  • Knowledge of basic linear algebra is useful for understanding the concepts and operations at a deeper level.
  • Familiarity with basic notions around measuring economic systems and the role of official statistics.

How Does The Course Help

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

  • Improved understanding of Input-Output Models and in particular computational aspects within 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 the basic IO related workflows that are facilitated by the Pymrio package

Course Level and Difficulty Level

This course is part of the Sustainable Finance family of courses.

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) within the Academy
  • If the issue is related the operation of the Open Risk Academy check first the Academy FAQ.
  • If the issue persists contact us at info@openrisk.eu

IO System

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