[JumpCrisscross]

> You record supply, demand and price over time period and then you can predict price by matching it to supply and demand

That's what the damn curves are! Even calling them curves is misleading. Freshman economics looks at linear systems. You take data, draw a regression and then predict a price.

Supply and demand isn't voodoo. Early economics courses are inaccurate because they start with linear models a general population of freshmen without strong mathematics training can grasp.

[js8]

> That's what the damn curves are!

No, they are not. The curves are drawn at a given point in time, what you're doing here is recording supply/demand over time. You would have to assume in addition that the curves didn't change over the time period so you could say this data are the demand/supply curves.

[JumpCrisscross]

> The curves are drawn at a given point in time, what you're doing here is recording supply/demand over time

Supply tables show producer activity at a point in time. Linear models don't model elasticity or endogeneity. Taking activity across a period in time is perfectly fine for this kind of a model.

By the way, we discovered and characterized elasticity and endogeneity by measuring deviations from said linear model. In some cases, the deviations were predictable. That expanded the box of situations in which the model was broadly useful.

Of course the introductory model isn't useful in most cases. But it (a) can be empirically validated in a predictable set of markets and (b) naturally extends itself to cover more ground, e.g. non-linear, endogenous and failure effects.

> You would have to assume in addition that the curves didn't change over the time period so you could say this data are the demand/supply curves

This is a fine assumption for a bare-bones model. If someone wants to shrink the box of uncertainty around their predictions they can learn more finance and economics.

TL; DR these models work well enough that people who understand them, and their limitations, will be able to make better predictions than those who don't.