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.

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.