On Thu, 9 Sep 2010, John C Frain wrote:
There is a considerable debate about using x12-arima adjusted data
in
econometric models. Some times it is all that you can do. Often it
is better to include a specific seasonal model in your econometrics.
John, thanks for your contribution to the discussion. It's really nice to
have debates of this caliber here on the user list.
I just want to add that, in my very very humble opinion, the mindless
usage of preprocessed data is one of the reasons of the present comatose
state of macroeconometrics. In practice, you take a time series like gdp
(which is itself a rough estimate of something that is defined rather
vaguely), you take seasonality away via x12 or tramo/seats, then you take
the trend away via HP or whatever (oh, and if you use HP you adopt the
usual, ridiculously conformist choice as to the value of lambda) and you
end up with something you pompously call the "output gap", which is in
fact little more than an educated drawing from a random number generator.
Then you ramble on for weeks and months across working papers and journals
about a 0.1% variation, trying to prove whatever the latest theoretical
fad is; while of course, all you really care about is the impact factor of
the journal you're submitting to.
Riccardo (Jack) Lucchetti
Dipartimento di Economia
Università Politecnica delle Marche
r.lucchetti(a)univpm.it
http://www.econ.univpm.it/lucchetti