Simulated Economy Tutorial

Agent-based modeling offers a more realistic approach to economic systems than traditional equilibrium models. New approachs including generative agents (ABM+LLMs) are promising. J. Doyne Farmer's recent book "Making Sense of Chaos: A Better Economics for a Better World" is a great reading for those interested in this field.

https://www.amazon.com/Making-Sense-Chaos-author/dp/02412019...

Neat, now I'm curious. Can you explain why?

stands to reason .. if we assume the actual economy is full of autonomous agents [ people, companies, governments ] acting largely in self interest.

Agent-based models capture the messy reality of economic systems by simulating heterogeneous actors making local decisions with imperfect information, allowing for emergent phenomena, non-linear dynamics, and adaptation over time, precisely the features that equilibrium models abstract away through unrealistic assumptions of perfect rationality, homogeneity, and static optimization that fail to predict or explain crises, bubbles, and technological disruptions that define actual economic evolution. To be honest, ABMs aren't perfect either. They face challenges with calibration, validation against empirical data, computational limitations, etc.

Demis Hassabis seems to describe a process whereby an AI can accelerate the results of billions of simulations by efficiently encoding that predictive behavior.. making something that is computationally expensive to simulate perhaps several orders of magnitude more tractable.

This has proven out in the acceleration of actual weather prediction using AI which means it can be feasibly run on a single desktop machine.

I think its not a stretch to imagine that a) there is a way to simulate the whole economy at the same level of quality as a weather or climate simulation b) AI can accelerate the computations to the point they can run on accessible hardware.

We need this whole economy simulation ... to answer practical questions such as - if we dole out UBI to everyone to cover basic living costs, will that simply result in the cost of rent going up to absorb the whole amount ?

Thanks for the link. If anyone has additional links, including scholarly references, this is an area of huge interest to me but I wouldn't know where to turn to for the latest research and models.

No. There is no macroeconomist who wouldn’t adopt these approaches if they were “better”.

Agent based models have been around since the 1980’s at least. No one uses them in central banks, no one uses them in industry, and you can be very confident that they’ve tried.

Sure, they've tried but it does not mean it hasn't evolved

https://www.centralbanking.com/central-banks/economics/macro...

https://www.bankofengland.co.uk/working-paper/2025/agent-bas...

> if we dole out UBI to everyone to cover basic living costs, will that simply result in the cost of rent going up to absorb the whole amount?

For that to be true, rent-seeking would have to literally capture all surplus. In which case UBI wouldn’t be an option in the first place.

The marginal increase in the purchasing power of someone who went from having $0 to $n would always be greater than the increase in purchasing power for someone who went from $1 billion to $1 billion + n - even with inflation.

> We need this whole economy simulation ... to answer practical questions such as - if we dole out UBI to everyone to cover basic living costs, will that

"How will humans (in aggregate) behave under novel conditions?"

Models tend to behave poorly when asked about things outside their training distribution.

Sure, just don't necessarily sell them as "more realistic" if they're not performing as well in real situations

Neural network based computer vision models also existed for decades. They weren't very good and weren't really used, till early 2010s when people figured out how to make them work. Now they are vastly superior to all the other ways.

This is quite common across the sciences. Some technique doesn't seem to work because of missing crucial insights or technology. Then somebody fills the gaps, and the technique works.

These types of models in economics might or might not become viable at some point.

"The models might become viable at some point" is very different from the original claim at the top level of this comment chain, though, which made a positive assertion that agent-based models are better. The parent comment to yours was right to call out that claim, and it offered a reasonable basis for that counterargument at the same time.

You're taking this from the perspective of people who are stuck in a specific mental framework who want to prove that their mental framework is the right one, no matter how impossible it is in practice.

What if you don't care about tuning against a real macro-economy? What if the economy being fictional was the entire point?

Let's suppose you wanted to make a game that simulates a realistic economy as a gameplay element no different from say a physics engine. Why wouldn't you do it using agent based modeling? What you're saying sounds purely dogmatic now. It's more about thought termination than actually accomplishing something. After all, central banks and businesses don't give a damn that agent X did action Y at time Z for all agents, actions and times. Meanwhile in a game? It's actually essential, because the model is the reality inside that fictional world. The model is "perfect".

Not to mention non-ergodicity, path dependency and hysteresis.

"realistic" is an interesting word, because it can have different connotations.

We can write a very accurate quantum mechanical model for the oxygen atom. But you can't actually simulate it without a galaxy sized classical computer. But it is very realistic=accurate model.

Or you can write and easily simulate a non-realistic semiclassical model. This one is a realistic=efficiently simulatable model.

Obviously a fully agent made model is more realistic in the "accurate" sense, because it correctly models the underlying reality. But if you make realistic agents, you have something inefficient (non realistic in the "simulatable" sense).

Right, Agent-based models are only useful as “exploration” tool, you cannot really use them for forecast because there's an impractically high number of parameter to tune.

Micro-founded macro economics models (say DSGE) are much easier to tune based on available historical data so they are much preferred, and nobody seams to care that they have the same predicting power as astrology.

Its not like the classical models are any good in terms for performance in real situations, as they have proven to be unable to predict anything over the past 40 years better than a basic linear extrapolation from the trend would have.

Current macro-economics models are arguably not much better than a broken clock in terms of predicting power.

There are plenty of people working on the application of ML in economics, including NN methods, and including in macro.

That’s a totally different class of model to this agent based approach. People in the (small) agent based modeling community have been pushing their stuff for decades to no effect.

Sure it’s possible that there’s some amazing advance I can’t see coming in the future but as of now I would not recommend anyone pursue ABM.