Abstract
The rise of computational power makes agent-based modelling a viable option for models capturing the complex nature of an economy. However, the coding implementation can be tedious. Because of this, we introduce ABCE, the Agent-Based Computational Economics library. ABCE is an agent-based modeling library for Python that is specifically tailored for economic phenomena. With ABCE the modeler specifies the decision logic of the agents, the order of actions, the goods and their physical transformation (the production and the consumption functions). Then, ABCE automatically handles the actions, such as production and consumption, trade and agent interaction. The result is a program where the source code consists of only economically meaningful commands (e.g. decisions, buy, sell, produce, consume, contract, etc.). ABCE scales on multi-core computers, without the intervention of the modeler. The model can be packaged into a nice web application or run in a Jupyter notebook.
D. Taghawi-Nejad—This author gratefully acknowledge the financial support from MS AMLIN plc, London.
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Notes
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Meaning that goods and money are not created “out of thin air”. ABCE is stock flow consistent, if the stock-flow consistency is not explicitly broken.
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Taghawi-Nejad, D. et al. (2017). ABCE: A Python Library for Economic Agent-Based Modeling. In: Ciampaglia, G., Mashhadi, A., Yasseri, T. (eds) Social Informatics. SocInfo 2017. Lecture Notes in Computer Science(), vol 10539. Springer, Cham. https://doi.org/10.1007/978-3-319-67217-5_2
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