If I were to look at physics, I can model simple systems in classical physics quite easily using a computer. In biology I can model population dynamics. Doing so helps me learn, and I find it gives me a deeping understanding as it forces me to be clear about exactly what is going into a model.
I'm aware that economics is a much softer science, but other than Peter Novig's example I can't find much in the way of modelling as a learning tool (rather than a research tool).
Does that approach exist anywhere?
Analogously in economics you'd want to define the agents, the inventory of what they have, what they want, and the medium (market) through which they will trade to become as happy as they can. When nobody sees any point trading anymore you have a “Pareto optimal” end-state and you're basically in equilibrium.
Back when I used program simulations I used Mathematica, and I am still deeply tied to that specific platform, but there's several introductions to doing much the same with less exotic (and expensive) tools such as Python: https://www.researchgate.net/profile/Michael_North/publicati...
I'd be interested in an attempt to take these simple ideas: credit, debt, etc and created a simple model that shows how credit leads to cycles, where I can play with parameters and see exactly what affacts what.
For example, why cycles? Why should credit across multiple people synchronize into cycles? why not just average out? Exactly what assumptions go into this?
But your example - why business cycles occur - is really more of a debate than a generally understood phenomenon. That's part of the reason why they occur. (part of the explanation is straightforward: people are less likely to borrow if they think that problems in the economy might make repayment difficult, and optimism/pessimism about the future tends to be shared by large proportions of the population. But the dynamics aren't universally agreed upon.)