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Global convergence of incomes in a climate-constrained world

Repository Overview

This repository stores all code related to the paper Oswald, 2024, Global convergence of incomes in a climate-constrained world (in preparation/review).

All relevant output figures for this paper are produced in Jupyter notebooks. These notebooks employ the classes that represent the actual model, which are Python files.

Model Python Files

  1. country_class.py - Defines the country-specific attributes and behaviors.
  2. scenario_class.py - Handles the different scenarios for income convergence modeling.

Supporting Modeling Files for Plots

  1. scenariosweeper_class.py - Necessary for 2-D trade-offs plots.
  2. plots_class.py - Contains methods for generating various plots.

Notebooks for Figure Outputs

  1. first_data_explorations.ipynb - Initial data checks and analysis, includes FIGURE 1.
  2. run_figure2.ipynb - Generates FIGURE 2.
  3. run_figure3.ipynb - Generates FIGURE 3.
  4. run_figure4.ipynb - Generates FIGURE 4.
  5. run_figure5.ipynb - Generates FIGURE 5.
  6. run_country_specifics Figures not included in paper or supplementary material but of relevance for country-specific analysis.

Pre-Modelling Data Processing Notebooks

  1. clean_extend_pip_data.ipynb - Processes and extends initial data for modeling.

Data files

All necessary data files that are processed by the notebooks and model are in the folder data. There is only freely available data from the World Bank, the UN and processed data from IIASA SSP explorer. Please get in touch in case of issues loading the data or conflict of storing the data here.

The original references are

1. https://pip.worldbank.org/ (originally downloaded dataset included)
2. https://tntcat.iiasa.ac.at/SspDb/dsd?Action=htmlpage&page=welcome (originally downloaded dataset NOT included)
3. https://population.un.org/wpp/ (originally downloaded dataset included)

Getting Started

To get started with the code, ensure you have the necessary dependencies installed. You can set up your environment using the provided requirements.txt file.

pip install -r requirements.txt

Usage

Each Jupyter notebook is designed to be run independently. Ensure you have the model Python files in the same directory as the notebooks to avoid import errors. As well as the required data files.

  1. Clone the repository:

    git clone https://github.com/yannickoswald/global-convergence-incomes.git

  2. Navigate to the repository:

    cd global-convergence-incomes

  3. Run the notebooks:

    Open any of the Jupyter notebooks using Jupyter Lab or Jupyter Notebook interface.

    jupyter lab

    or

    jupyter notebook

Reporting Issues

If you encounter any issues or have suggestions for improvements, please raise an issue on GitHub. To do so, follow these steps:

  1. Go to the repository's Issues page.
  2. Click on the "New Issue" button.
  3. Provide a descriptive title and detailed information about the issue.
  4. Click "Submit new issue" to create the issue.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Contact

[email protected]