9:04 p.m.
Henrique,
My initial encounter with seasonal adjustment was as a statistician in
the Central Statistics Office in Dublin. In the mid 1970's we started
to use the x11 (previous version of the X12-Arima) program. For each
series we asked a variety of questions (e.g. Additive/multiplicative
adjustment, Easter adjustment? Trading day adjustment, Treatment of
outliers). Initial answers to these problems were suggested by an
examination of the x11 output with default settings. This output is
still produced by X12-ARIMA. If the initial automatic run was not
satisfactory one generally revised the initial parameters until the
output was satisfactory. The process was continued until a
satisfactory result (specification) was obtained. This specification
would then be used in a form of revised automatic seasonal adjustment
for that series for a long period afterwards. One did, or should,
monitor the x11 quality statistics in later periods. These are real
life problems that anyone working in detail on seasonal adjustment
might find. Ignoring them will likely lead to later problems. If you
feel that you would like to learn more about the X11 output can I
recommend Ladiray, D. and Benoit Quenneville (2001), Seasonal
Adjustment with the X-11 Method, Springer. My experience is that
seasonal adjustment is more difficult than simply pressing a few
buttons in a computer program. Seasonal adjustment is much more
complex than drawing a graph and often needs manual intervention.
Thus the difference.
I do use the Gretl X12-ARIMA facilities. It is a very convenient way
to access the X12-ARIMA or TRAMO/SEATS program. In particular, I like
the facility to import a large amount of data into Gretl and pass the
results to X12-ARIMA. I do look at the X12-ARIMA or TRAMO/SEATS
output. If the automatic adjustment is not satisfactory I will use
the one of the seasonal adjustment programs either directly or through
another interface. I have already stated that the opinion of various
persons, working on this topic in statistical offices or central
banks, who were accustomed to evaluating seasonal adjustments is that
the automatic process works well in about 70% of cases. I can not
quote any specific study - just an approximation. (It is worth noting
that the x12-arima output produced by gretl includes a copy of the
material that can be used as a direct input to the x12-arima program)
In a real life interior missing values and the treatment of outliers
is a problem. The treatment of these in X12-ARIMA is unique. The
Gretl interface has problems with interior missing values. If Gretl
crashes in such circumstances it might be helpful if the user was
referred to the x12-arima manual where he would find details of the
process necessary to do seasonal adjustment. If it is considered more
convenient for the gretl interface to delete missing values at the
start and end of the data then I have no objection. My problem was
that I considered the interior missing values to be more important and
was hoping to cover both cases in one.
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.
Best regards
John
I'm not blaming Gretl or X-12-Arima because of this.
I have a real life problem: I have two series, X and Y, inside a Gretl data
file (.gdt). The variable X goes up to 2008 and variable Y goes up to 2009.
My model says that:
X = B0 + B1*Y(t-1)
With this I can predict the values of the X variable up to 2009.
I don't think it would be nice adjust my sample everytime I need to make an
X-12-Arima analysis. I don't adjust it when I need to use logs. I don't need
to adjust it when I plot a graph. Why treat X-12-Arima differently?
Best regards,
Henrique
2010/9/9 John C Frain <frainj(a)gmail.com>
>
> X12-ARIMA has its own way of dealing with missing values either at the
> end of the series or in the middle. Even if the missing values are in
> the middle of the series X12-Arima in Gretl will fail with a similar
> message. Perhaps it would be better if Gretl just checked for
> missing values and if it found them issued a message that X!2-ARIMA
> does not work if there are missing values in the span of the data.
>
> While the X12-ARIMA manual states that missing values are not allowed
> there are ways around this. If the missing value is replaced by
> -99999 then -99999 may be replaced by a value that is regarded as an
> outlier and then this may be replace by the appropriate Reg-ARIMA
> fitted value for the purpose of estimation seasonal factors etc. This
> may require specific X12ARIMA options to be in effect and running
> X12-ARIMA outside of Gretl.
>
> I would strongly recommend that users of X12-ARIMA become familiar
> with X12-ARIMA output and check initial runs of the program to ensure
> that what they are doing is correct. While X12-ARIMA does produce
> sensible results in the majority of cases there are times when it may
> not. In such cases you may need to refine the options used. Don't
> blame the program if you use the wrong options
>
> On 9 September 2010 05:01, Henrique Andrade <henrique.coelho(a)gmail.com>
> wrote:
> > Thanks a lot Allin!
> >
> > 2010/9/9 Allin Cottrell <cottrell(a)wfu.edu>
> >>
> >> On Wed, 8 Sep 2010, Henrique Andrade wrote:
> >>
> >> > I'm trying to perform a X-12-Arima analysis in a series but
I'm
> >> > getting
> >> > this
> >> > error message:
> >> >
> >> > ERROR: Multiplicative or log additive seasonal adjustment cannot
> >> > be performed when preadjustment factors are derived from a
> >> > regARIMA model for data which have not been log transformed.
> >>
> >> Because the current sample range contains missing values. OK,
> >> we'll pre-adjust the sample.
> >>
> >> Allin
> >> _______________________________________________
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> >
> >
> >
> > --
> > Henrique C. de Andrade
> > Doutorando em Economia Aplicada
> > Universidade Federal do Rio Grande do Sul
> > www.ufrgs.br/ppge
> >
> > _______________________________________________
> > Gretl-users mailing list
> > Gretl-users(a)lists.wfu.edu
> > http://lists.wfu.edu/mailman/listinfo/gretl-users
> >
>
>
>
> --
> John C Frain
> Economics Department
> Trinity College Dublin
> Dublin 2
> Ireland
> www.tcd.ie/Economics/staff/frainj/home.html
> mailto:frainj@tcd.ie
> mailto:frainj@gmail.com
> _______________________________________________
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--
Henrique C. de Andrade
Doutorando em Economia Aplicada
Universidade Federal do Rio Grande do Sul
www.ufrgs.br/ppge
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John C Frain
Economics Department
Trinity College Dublin
Dublin 2
Ireland
www.tcd.ie/Economics/staff/frainj/home.html
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mailto:frainj@gmail.com