Capital Equipment

How should a quantum economist deal with it. Let Nick start a debate about Hanson's machines as heard on Russ's Econotalk, then read the comments on Brad's blog, and get this note:

Piero Sraffa was someone that Paul Samuelson thought highly of in the likely case that students today have never heard of him. Models of total automated economies go back to Dmintriev. Ian Steedman developed one in his Marx After Sraffa. Spencer Pack has one such model in his highly stimulating recent book on Aristotle, Smith and Marx

From hartal. He punched all my buttons in the tango. So I look this guy up, find out how he is connected to the Cambridge debates, and have to take a shot at capital definition in the quantum sense.

Capital is a tightly bound function about some power. It is reliably doing something needed, in near world, and doing it fast and accurate against a stable Gibbs separation. This polynomial is occupying prime space of the low orders and generating inventories out to the fourth or fifth order, we rely on its rate keeper. The next power up is high, the gain from specialization high.
In the real economy, a Kragen's manager can rely on the delivery of headlamps, they have high precision capital equipment behind them. So he reduces some of his own variability in favor of the reliable specialized equipment, adapting his store.

Tightly bound?
Like a car frame, all  transportation quants, down the chain,  obey the car frame.

Does capital equipment have Elliot waves?
Sure, the car industry does a sudden unwind after an oil shock. What we thought was a blob of car dealers, became a spiral of sparse inventory flow.

Good capital equipment has a path through the Fib tree in large jumps down the center.  The inverse Fib is going to be volatile and noisy.  When we get a basic change from the manufacturer, we get an inventory bulge pushing down the tree, adding phase shift to the polynomials that had become multiples of the more powerful.  This appears to the quantum economists as a spiral, he will look geographically for changes in business property values, shipment types, Ceridian index, commuter miles, all of this over geography, the local polynomials, short in variation are partitioned out as the economist looks for residual polynomials that cover lower rates and higher sizes.

How is the problem solved?
We get better at making high powered polynomials with few terms. We make new capital equipment when we see spirals.