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Mathematical economist/game theorist here (applying daily in the role of CEO of family firm founded three generations ago).

Firstly... and I do not mean this to sound like hurt pride, but... a discipline would need to be quite trivial to be ‘understood’ by cursorily surveying a few online texts. There's a corpus of several centuries of findings, derivations, and unresolved controversies precisely _because_ it is nontrivial. (Side note: the existence of controversies that divide different schools of thought does not mean that everything is in question and that absolutely anything goes because, hey, we can always argue with words by distancing ourselves from observable reality — that makes for religion not science, albeit even the dismal kind.)

Second: the general idea is that there exists a dynamic, complex system constituted of agents (people, sometimes aggregated into firms and/or nations, being almost always simultaneously consumers of something in need of everything except that which they are suppliers of, be it labour, materials, knowledge, time in the form of lending money, whatever) each doing their best to maximise the enjoyment (utility) of what they have by interacting in a series of ‘markets’, which for the sake of analysis we generally are forced to assume are in ‘equilibrium’ (i.e. We're at the “end of history“ where no external bumps or surprises are leaking into the market and nudging it in any direction) but in truth we know to be in perpetual disequilibrium as information percolates in, surprises happen, and generally guesstimates of everybody involved are shown to right at best on average. An equilibrium price comes to exist where supply and demand cross and we spend many a happy hour calculating that and then trying to figure out how a ‘shocked’ system returns to equilibrium if we jolt it.

Thirdly: money is (surprisingly enough, for the public which seems to conflate economics and accounting) not necessarily the domain of economics. As a whole the discipline deals with incentives (most usefully and generically regarded as differences in subjective utility) and responses thereto (utility maximising strategies). Money is at best something that serves as a denominator to give everything a common unit and, at worst, an irksome distortion. This is one of those “school of thought” controversies I mentioned above: there are monetarists within the domain of economics and there is the separate domain of finance, somewhere between accounting and economics, and to which ‘risk’ (uncertain future outcomes) is an essential ingredient — and governmental fiscal policy (taxation and public spending)... that's yet another thing.

For the sake of reading I suggest (no offence intended) Managerial Economics For Dummies, The Origin Of Wealth (Eric Beinhocker), and The Social Atom (Mark Buchanan).

P.S. On mobile so I've had to edit this a few times... sorry if you caught me in flux but it's great to have a chance to mention stuff that amuses me once in a while.

Maybe I was too broad when I said "understand" - I had no intention of trivializing economics. I'm interested in it because it's both complex and relevant. I just want to know more than I know now.

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?

In computational physics you model situations by creating some particles, placing them in some initial configuration, and defining the manner in which position and proximity of other particles creates forces acting upon each particle, and then you calculate acceleration, and thus eventually the position of those particles after a single temporal step. When all the giggling stops you've hit your system's final configuration given the initial conditions and subject to the forces defined (up to the numerical precision afforded by whatever affects your simulation's precision).

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...

Oh well, so much for that.

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