"I'm not sure what you disagree with." I disagree with the usual notion that the problem of planning is somehow (algorithmically) difficult, once you know the

"I'm not sure what you disagree with." I disagree with the usual notion that the problem of planning is somehow (algorithmically) difficult, once you know the objective function. Instead, I argue there is a tradeoff in the objective function, which is hard to estimate in theory without experimentation. This experimentation goes against the goal of efficiency (you need redundancy). So even if you knew all the demands of all the consumers, and could calculate what to produce (which e.g. von Mises argues is impossible), I argue you would still have a problem with central planning, because the resulting optimal plan would not be robust enough to execute. I also don't think the former is a big issue with computers, to be honest. There are examples of top-down logistical planning operations in the world which are comparable to an economy of a small country. "Do you have any evidence that this is a universal statement?" Well, in optimization problems, usually as you get closer to the possible optimum, the number of acceptable solutions decreases. So the closer the solution to the optimum, the less leeway there is to adapt the solution to some unforeseen circumstances. Addendum: I think many economists try to paint free market as being efficient, and that's why they argue the optimization problem is impossible to solve. However, I don't think free markets actually are efficient, but rather, make a different trade-off, which works better in practice (it also has downsides).