Computational Reasoning with Stock and Flow Macroeconomic Models

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Description of Research Project

Stock-and-flow consistent (SFC) macro-economic models provide a quantitative framework for representing economies as dynamic systems evolving over time. In these models, stocks represent accumulated quantities such as deposits, cash, inventories or tangible capital, while flows capture the rates at which these stocks change, including consumption, investment, and wages. By setting up systems of equations that show how stocks are affected by flows with the passage of time, it is possible to construct computational models of economies that allow simulation and analysis of their behavior given different parameterizations and external disturbances. Such analyses may, in turn, allow comprehension and appreciation of the complex causal structures that drive the evolution of an economy.

In this project, the student will develop implementations of a specific set of SFC models put forth by Godley and Lavoie. Using Python and appropriate mathematical libraries they will start by coding and solving the systems of equations proposed by said authors. They will then refactor the mathematical models so that they reflect a plausible causal interpretation of how economic variables affect each other. They will use Causal Loop or Stock and Flow Diagrams to visually represent and reason about such causal structures. From there, depending on their specific interests, the student will focus either on producing increasingly detailed and realistic models aimed at thoroughly understanding and appreciating the Godley and Lavoie framework, or on exploring novel computational techniques based on classical or modern Artificial Intelligence (AI) (e.g., action theoretic calculi, qualitative reasoners, or possibly LLMs) to perform automated reasoning about the dynamics of the modeled systems.

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Undergraduate Student Responsibilities

- Thoroughly and critically study the SFC framework proposed by Godley and Lavoie.
- Using Python and related tools and libraries, implement the proposed models, experiment with them and visualize the output data in various ways.
- Potentially: study one or more additional AI formal specification approaches and appropriately formalize the models using such approaches. Use corresponding computational tools to perform different kinds of simulation of and automated reasoning with the dynamics of the modelled system.
- In weekly meetings offer presentations and demonstrations of the learned framework, targeted to an audience of computer scientists who may have limited familiarity with macroeconomic concepts.

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Qualifications Required

Major/Minor in Economics.
- Students from other departments who can demonstrate strong interest and skill, due to e.g., extra-curricular study, are welcome to apply.
- Exceptional academic performance and strong interest in the subject and in high-quality scholarship.
- Technical skills. All students must have a strong interest in computer programming and computer-based simulation. In addition, they should offer the following:
- Strong understanding of macro-economics and monetary economics as evident in strong performance in courses such as: ECON2450, ECON4020, ECON3430, ECON3440. ECON3580, or similar MOOCs
- Basic linear algebra skills (ability to manipulate and solve systems of equations).
- Basic programming skills in Python are highly desired but not mandatory.