Re: [Gretl-users] Gretl-users Digest, Vol 44, Issue 25
I figured out what was causing the discrepancy. I was incorrectly
assuming that the ARIMA feature was seasonally differencing both the
dependent and independent variables. I was able to reconcile when I
manually seasonally differenced the dependent variables outside of the
ARIMA feature.
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Today's Topics:
1. Re: ARIMA v. OLS seasonal difference (Allin Cottrell)
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Message: 1
Date: Fri, 17 Sep 2010 16:38:28 -0400 (EDT)
From: Allin Cottrell <cottrell(a)wfu.edu>
Subject: Re: [Gretl-users] ARIMA v. OLS seasonal difference
To: Gretl list <gretl-users(a)lists.wfu.edu>
Message-ID: <Pine.A41.4.58.1009171627150.573836(a)f1n11.sp2net.wfu.edu>
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On Wed, 15 Sep 2010, Allin Cottrell wrote:
On Wed, 15 Sep 2010, Mike Pfeiff wrote:
> Is there any obvious reason why using the ARIMA feature (without any
AR
> or MA terms) with a seasonal difference=1 would yield different
> coefficients that using OLS and manually seasonally differencing the
> independent and dependent variables?
No. Can you post an example script that shows differences in
results? We have some test cases on file where we get identical
results via the two methods, but maybe we're overlooking
something...
Sorry, what I said there was not correct. The test cases I had in
mind, where we got identical results, were in fact comparisons of
(a) ARIMA estimation and (b) plain ARMA estimation, with the data
manually differenced first.
As for "ARIMA" with no AR or MA terms versus OLS on differenced
data, you would expect the results to be close but not necessarily
identical, because the calculation method is quite different
(using the Kalman filter and BFGS for ARIMA). Or I should say "was
quite different", because I've now changed this in CVS: if we
detect that an ARIMA model has no ARMA content (and no missing
values) we now just apply OLS (= MLE), there being no point in
using heavy artillery when a pea-shooter will do the job.
Allin Cottrell
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