For the economists, it is often matching the moments between savings and loans, in particular it means finding the N such that mean, variance and skew of a relationship pair match.
The typical cases are all 1,y,z on the tree. That chain lists all the N for which the moments of savings and loans match, they are at the same resolution.
This is about coloring the ball with deviations from moment match, keeping those deviations minimal. This is where the Lucas criteria is met, we have to match N, the number of agents we need to meet some policy equilibrium. And the Markov tree tells us the resolution of that match.
If the economists does not understand this then they inevitable stop at one or two moments, become flat earthers, like Pau Krugman. The resoluiont part is where the Huffman encoder comes in play, a Huffman encoder can 'rescale' the model to adapt to some N, and the Markov tree, after some trials, will tell us what the N is, what the Huffaml resolution is when thingds match.
Operating off the 1,y,z path still works, and you need this for central banking. Some x,y,z includes the x for government borrowings, more like a seigniorage tax needed to keep government in balance. In this case we are finding the N we need to keep government from exceeding its bound error (ie going off the rails). The moment matching test tells is in the model and in reality how concentrated the wealth becomes when N is reasonably fixed. This is the Lucas critique, this is what the hidden Markov solves. It can tell us how rich Bezos needs to be so that government dos no fall out of balance.
The super wealthy solve a problem, they can hold out as long as the government needs seigniorage taxes. Keynes was clueless, most of this moment matching only goes back top 1990 at the earliest. But this is economics today, if it is not done right the the economists is considered a fraud, sorry to day. The flat earthers are concentrating wealth, they need to stop.
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