N(m)=∑ini=∑imai=∑ie−ailog1/m
has the form of a partition function
Z(β)=∑ie−βEi
Where β=1/kT corresponds to log1/m and the energy of the states Ei corresponds to the ai, which corresponds to the maximum entropy probability distribution. If we take that analogy at face value, the expected value of the random ai with maximum entropy would be
⟨a⟩=−∂logZ(β)∂β=∑iaimai∑imai
Since N∼m⟨a⟩, we now have an exponent that varies with m -- exactly we have observed with the exponent κ(N,M)! (see here or here). The resulting function N∼m⟨a⟩ now overestimates the result of adding the markets together. Here are the results for uniformly distributed ai where ai∈[0,1], [0,2] and [0,4] (the plot of ⟨a⟩ appears alongside the corresponding graph of N∼m⟨a⟩):
One thing is that in statistical mechanics, higher temperature means that more of the higher energy states are occupied, it appears as though the observation in economics is that higher m (money supply) means that more of the lower ai states are occupied in order to produce this figure. I'll have to look into this a little more to fully understand how this works. However this may be a pretty important result, at least for information transfer economics. Stay tuned!
No comments:
Post a Comment
Comments are welcome. Please see the Moderation and comment policy.
Also, try to avoid the use of dollar signs as they interfere with my setup of mathjax. I left it set up that way because I think this is funny for an economics blog. You can use € or £ instead.
Note: Only a member of this blog may post a comment.