In SV (south of SF - coddled lot with starry eyes), we see a growing emphasis on causation. Why? At the same time, one hears a lot of the usefulness of econometrics. That esteemed field is quite careful about using the "cause" word. What gives?
Not only do we hear of causation, as if infinite correlative associations are observed, we see a great emphasis on modeling. But, then, SV is about computers albeit one would hope that some wisdom would arise there.
For instance, what about being a little sensitive to issues related to causation? One example would be the triad of qualification, frame, and ramification that came out of advanced logic. That is, pre-conditions, event, post-conditions are still a gnarly group of things despite the seemingly magical nature related to our displays of prowess.
The Fed has its head in the STEM-sand. So, the analysis would have to pair our predilection to think that silicone reigns.
Now, to the interest rate. The Fed and its ilk need to agree on some floor for interest. It is not zero. Japan's penetration of that (following talks in Europe of the same thing) is wrong for several reasons.
One thing that we could do then, with such a floor, is study liquidity issues. I mean in the sense associated with the analysis of Keynes and others. Elsewhere(What-is-negative-interest-rate-adopted-by-bank-of-Japan), I suggested that we need to identify two groups: gamers and savers. The former are running things (into the ground). The latter are really interested in long-term issues of which a big factor is investment.
Somehow, some (Nash, et al) have caused (there I go - causation is a multi-faceted affair of which we never remove the residue - except via chimeric means) a descent toward perdition, as measured by turbulence.
How this all works out (Janet's unwinding from Ben's positions) will be something to watch. But, the underlying models and methods are worthy of attention from a different angle. This work is imperatively important.
Disclosure: My degrees in Economics had a focus on Econometrics and the underlying discplines of Mathematics and Statistics. However, I spent my career working real problems in the areas supported by Engineering Computing. Now, I am getting back to the dismal-ness of Economics.
Remarks: Modified: 02/04/2016