One web site of choice is "Bank
Underground" from the Bank of England. Essentially it is about how it
works and tries to explain what it is up to or not up to as the case may be. It
is neither fun nor easy.
Certainly, it needs a site like this because
it is all too evident that most or nearly all of the main media, political
parties, traders, dealers, retail bankers, experts of one sort or another and
far too many economists are not really up there with the economic game.
To be fair, the game is not the old
fashioned single entity where the rules are more or less the same from year to year,
and there is a fair chance that predictions may be right or work. In effect,
the rules change almost by the day as well as the pitch, the players and the
purpose.
This
article in titled "New Machines For The Old
Lady" is about the advances made at the Bank of England in applying high
and new technology to its function as a central bank. There has been, it says,
an explosion in the amount and variety of digitally available data.
All you need are machines that will
analyse it and allow you to suggest the policy options it alleges are required.
If you are in a hurry with all those berserker politicians crying for answers,
it seems a good idea.
I prefer the Bank articles to be brief and
not to challenge the wiring between the ears. This one needs time because of
the subject matter and having to explain what is what. But if you want to know
what your central bank is up to, why and how, it is part of the answer.
Unluckily, in this world however good the
mathematics, science, data gathering, artificial intelligence, analytic systems
and coffee machines, there are no certainties and not much comfort. After all
the explanation, it ends:
Quote:
However, care is needed when interpreting
the outputs from ML models. For example, they do not necessary identify
economic causation.
The fact that a correlation between two variables
has been observed in the past does not mean it will hold in the future, as we
have seen in the case of the artificial neural network when it is faced with a
situation not previously seen in the data, resulting in forecasts wide of the
mark.
Unquote.
Told you so.
Told you so.
If we pay people to forecast something which is unpredictable we'll still get forecasts. That's a strong correlation where causation is quite clear.
ReplyDeleteIf we can get new Brian artificial prediction is feasible causation us being unpredictable
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