to anyone who was mistakenly looking for the armax beer paper using Bierens
as the author. I made a mistake and apologize because the author was
franses and the paper is at the link below:

http://repub.eur.nl/res/pub/2112/eur_franses_MR1.pdf


On Thu, Feb 21, 2013 at 11:23 AM, Paul Bernal <paulberna...@gmail.com>wrote:

> Thank you very much my friend.
> El 21/02/2013 11:21, "Mark Leeds" <marklee...@gmail.com> escribió:
>
>> let me look. I have hardcopy so hopefully I have computer copy. get back
>> in a few minutes.
>>
>>
>> On Thu, Feb 21, 2013 at 11:06 AM, Paul Bernal <paulberna...@gmail.com>wrote:
>>
>>> Could you please provide me with a copy of that text?
>>>
>>> Best regards,
>>>
>>> Paul
>>> El 21/02/2013 10:59, "Mark Leeds" <marklee...@gmail.com> escribió:
>>>
>>>>  Hi: bierens has a paper on modelling beer sales in the netherland ( I'm
>>>> pretty sure it's on the net.
>>>> if not, I have a copy somewhere I think )  using an ARIMAX. why don't
>>>> you
>>>> take his paper and his data and see if you get the same estimates using
>>>> R.
>>>> That's one way if you'll know if you're doing the steps correctly. I
>>>> don't
>>>> have cryer and chan and I've never used the TSA package so I can't say
>>>> anything else.
>>>>
>>>>
>>>>
>>>>
>>>>
>>>>
>>>> On Thu, Feb 21, 2013 at 5:26 AM, Jose Iparraguirre <
>>>> jose.iparragui...@ageuk.org.uk> wrote:
>>>>
>>>> > Hi
>>>> >
>>>> > I'm trying to measure the effect of a policy intervention (Box and
>>>> Tiao,
>>>> > 1975).
>>>> > This query has to do with the coding of the model rather than with the
>>>> > particulars of my dataset, so I'm not providing the actual dataset
>>>> (or a
>>>> > simulated one) in this case, apart from some general description.
>>>> >
>>>> > The time series are of length n=34 (annual observations between 1977
>>>> and
>>>> > 2010). The policy measure was introduced in 2000 and it has been
>>>> > implemented once a year ever since.
>>>> >
>>>> > The variable of interest (VI) is continuous, and I have four
>>>> continuous
>>>> > covariates (CO1-CO4), plus the dummy intervention variable (DUM)
>>>> which is
>>>> > equal to 0 between 1977 and 1999 and equal to 1 since 2000.
>>>> >
>>>> > I thought of using an ARIMAX model, with the arimax() function in the
>>>> TSA
>>>> > package to fit the transfer function. I'm interested in modelling the
>>>> > intervention effect as a step function.
>>>> >
>>>> > I specified the model thus:
>>>> >
>>>> >
>>>> > a.       I've checked the ARIMA properties of each series using the
>>>> > auto.arima() function (from the 'forecast' package) -the VI was found
>>>> to
>>>> > best fit an ARIMA(0,1,1) model and the first covariate an
>>>> ARIMA(1,0,0),
>>>> > whereas the other covariates were white noise.
>>>> >
>>>> >
>>>> >
>>>> > b.      To facilitate the specification of the various models  (the
>>>> > different model specifications dropped variables or added additional
>>>> > covariates, etc, without changing the general structure of the syntax
>>>> > below), I defined the following design matrix:
>>>> >
>>>> >
>>>> >
>>>> > > xreg.1 <-  model.matrix(~CO1+ CO2+ CO3+ CO4)[,2:5]
>>>> >
>>>> >
>>>> >
>>>> > c.       Following Cryer and Chan (2008, ch. 11, p. 255), I wrote
>>>> models
>>>> > such as this:
>>>> >
>>>> >
>>>> >
>>>> > > arimax.1 <- arimax(VI, order=c(0,1,1),
>>>> >
>>>> > + xtransf=data.frame(xreg.1,dummy1=DUM),
>>>> >
>>>> > + transfer=list(c(1,0),c(0,0),c(0,0),c(0,0),c(0,0)))
>>>> >
>>>> >
>>>> > d.      So, I get estimates for the following coefficients:
>>>> >
>>>> >
>>>> > ma1;  CO1-AR1;  CO1-MA0;  CO2-MA0;  CO3-MA0;  CO4-MA0;  DUM-MA0
>>>> >
>>>> > Can you spot any problems with the general modelling approach or in
>>>> this
>>>> > specification?
>>>> >
>>>> > Many thanks in advance,
>>>> >
>>>> > José
>>>> >
>>>> >
>>>> >
>>>> > José Iparraguirre
>>>> > Chief Economist
>>>> > Age UK
>>>> >
>>>> > T 020 303 31482
>>>> > E jose.iparragui...@ageuk.org.uk<mailto:
>>>> jose.iparragui...@ageuk.org.uk>
>>>> > Twitter @jose.iparraguirre@ageuk
>>>> >
>>>> >
>>>> > Tavis House, 1- 6 Tavistock Square
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>>>> > http://ageukblog.org.uk/> | @ageuk<http://twitter.com/ageukpa
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>>>> >
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>>>> >
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>>>> >
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>>>>
>>>>
>>>>
>>>> ______________________________________________
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