Introduction

G-Cubed is a family of models that share a common set of characteristics. G-Cubed models are used to analyze a wide range of economic and environmental issues. The models are written in SYM. The software that produces economic projections for a given model is implemented in Python.

This preview documents the current build 199 model workflow. Model configuration, design, setup and chartpack files use the documented YAML formats.

The examples in this documentation are based on the public version of G-Cubed, with 2 regions and 2 sectors. However, the documentation also applies to larger G-Cubed models, with many regions and many sectors.

To learn how to run simulation experiments with a G-Cubed model, follow the steps set out below. You should be running experiments and viewing the results within 10 minutes if you use Github Codespaces.

1. Set up your G-Cubed environment.

2. Run a simulation experiment.

3. Plot the experiment results, referring to the chart guide for detailed instructions.

To better understand what you have just done:

1. Review the model configuration.

2. Become familiar with the data files.

3. Understand the model definition.

4. Learn how to design simulation experiments.

5. Use the YAML recipe book when creating or changing configuration, design, setup or chartpack files.