Dear 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,

2010/9/9 John C Frain <>
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 <> wrote:
> Thanks a lot Allin!
> 2010/9/9 Allin Cottrell <>
>> 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
>> _______________________________________________
>> Gretl-users mailing list
> --
> Henrique C. de Andrade
> Doutorando em Economia Aplicada
> Universidade Federal do Rio Grande do Sul
> _______________________________________________
> Gretl-users mailing list

John C Frain
Economics Department
Trinity College Dublin
Dublin 2
Gretl-users mailing list

Henrique C. de Andrade
Doutorando em Economia Aplicada
Universidade Federal do Rio Grande do Sul