A better economics for a better world
Macrocosm is modeling the future – navigating the nexus of climate, economics & finance
Our Approach
At Macrocosm we are scientists with a strong background in economic and financial modeling. We use advanced computational techniques to simulate economic systems from the bottom up.
Why it matters
Traditional economic models often oversimplify the world we live in. Our approach, called complexity economics, acknowledges that the global economy consists of:
Numerous diverse agents
Various types of interactions
Intricate supply chains
Continuously evolving technologies
We aim to capture these complexities in our models.
What we do
Data-Driven Models
Our systems are designed to handle and analyze complex datasets, providing precise, actionable insights.
Advanced Computational Techniques
We leverage AI and machine learning to enhance our economic modeling capabilities, producing robust and adaptable code.
Transparent Research
We believe in open and accessible research. Our work is shared publicly through scientific publications, ensuring accountability & fostering collaboration.
Innovative Solutions
We offer novel approaches to complex economic challenges, bridging the gap between theoretical models and real-world applications.
Our Expertise
Macrocosm develops models to address complex economic challenges. Our interdisciplinary approach combines economic insight with advanced computational techniques. We provide robust, flexible, data-driven analyses for complex economic and technological challenges.
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We think of the economy as a complex system where governments, firms, banks, and households interact. Our models are faithful to this heterogeneity of agents, roles, and scopes. We create artificial economies that provide comprehensive economic forecasts. With this approach, our researchers successfully predicted the impact of lockdowns on the UK economy during the COVID19 pandemic.
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We believe that data and statistics can tell us a lot about the future of technology. We develop time-series models to predict how the cost of technologies will evolve and how rapidly they will be adopted. Our researchers made a prediction on the cost of solar energy - and they were right.
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Our expertise in energy systems modeling is crucial for understanding the dynamics of the green transition. Our agent-based models of the energy markets allow us to simulate scenarios and analyze the impact of policy decisions on the energy sector's evolution.
Our Insights
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Decarbonising the energy system by 2050 could save trillions
Transitioning to a decarbonised energy system by around 2050 is expected to save the world at least $12 trillion, compared to continuing our current levels of fossil fuel use, according to a peer-reviewed study by Oxford University researchers, published in the journal Joule.
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Quant fund pioneer plans to build an economic super-simulator on a global scale
Counting the number of angels dancing on the head of a pin is not the sort of scholarly endeavour that would distract Doyne Farmer. But identifying a similarly granular level of detail will be a major part of his next big venture – and its scope is immense.
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Learning curves will lead to extremely cheap clean energy
As we stand on the brink of a renewable energy revolution, Doyne Farmer explains in this podcast how historical patterns of cost reductions in technologies like solar photovoltaics, wind power, and batteries are not just predictions but a continuation of an established trend.
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In conversation with BCG Henderson Institute
Our funder Doyne Farmer discusses complexity economics with BCG’s Dave Young.
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In conversation with Martin Reeves
Together with Martin Reeves, Chairman of the BCG Henderson Institute, Doyne Farmer discusses the limitations of standard models of economics as well as the consequences of such limitations.
