Global Economy Super-Simulator Proposed by Complexity Science Expert

Efforts to improve economic forecasting have led Prof J. Doyne Farmer to propose a detailed simulator of the global economy using advanced computational methods. The initiative aims to address limitations in current economic models, especially in the context of climate and financial risks.

Prof. Farmer, who leads the Complexity Economics programme at Oxford University, has outlined plans for a “super-simulator” that would model individual companies worldwide. The approach relies on complexity science and machine learning to better reflect the behavior of economic agents and interactions across sectors.

The simulator is expected to require an investment of around US$100 million. Farmer and his team have previously developed complexity-based models to analyze events such as the US real-estate collapse and the economic effects of the COVID-19 pandemic in the UK. These retrospective studies have demonstrated the potential for more nuanced modeling compared to traditional methods.

Current work by Farmer’s group includes a global energy sector model, which incorporates data from about 30,000 companies and 160,000 assets collected over 25 years. This project is part of a broader effort to capture the complexity of real-world economic systems, moving beyond the assumptions of rational agents and static equilibrium found in standard economic theory.

What the numbers show

• The proposed simulator would cost approximately US$100 million
• A 2022 study found rapid clean energy transition could save trillions of dollars
• Climate shocks between 2070 and 2090 could result in up to 50% global GDP loss, according to a 2025 assessment

Complexity economics, as described by Farmer and other researchers, treats the economy as a system with diverse decision-makers and interconnected components. This contrasts with mainstream models, which have faced criticism for failing to anticipate events like the 2008 subprime mortgage crisis and the economic impact of the COVID-19 pandemic.

Farmer has stated that the envisioned simulator could be developed within a decade, and possibly within five years. He has compared its potential use to that of navigation tools like Google Maps, providing dynamic answers to economic questions based on real-time data and adaptive modeling.

Recent studies have highlighted the limitations of existing economic models in assessing climate risks. Some mainstream approaches estimate a 10% global GDP loss at 3–4 °C warming, while other scientific assessments suggest more severe impacts, including the possibility of societal disruption. Experts have stated that ignoring extreme events and tipping points in economic modeling could result in underestimating the potential for catastrophic outcomes.

Farmer’s recent book, “Making Sense of Chaos: A Better Economics for a Better World,” was first published in 2024. The publication explores the principles of complexity economics and the need for improved tools to address global challenges.

* This article is based on publicly available information at the time of writing.