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Re: st: Why does Stata estimate different partial autocorrelations?

From   Gewei Wang <>
Subject   Re: st: Why does Stata estimate different partial autocorrelations?
Date   Sat, 19 Feb 2005 02:26:13 -0500

Thank you very much for your informative comment. I just hope that an
option for Yule-Walker estimation will eventually be added to -corrgram-
and -pac- since sometimes we are likely to compare results from Stata
with those from SAS, Eviews, Minitab, Limdep etc. I was surprised when I
saw that my result was different with that on the textbook and my
teacher's (he used Minitab).


----- Original Message ------
At 09:41 AM, 02-16-2005, you wrote:
>On Tue, 15 Feb 2005, Gewei Wang wrote:
>> Hi, all,
>> I just found the Stata's command -- corrgram -- gives different results
>> of partial autocorrelations from other statistical softwares such as SAS
>> and Eviews. Of course, the -- pac -- creates different plots. In
>> particular, Stata's one period lag partial autocorrelation is different
>> with one period lag autocorrelation. However, other softwares report
>> same values. Who can tell me the reason? Thanks a lot.
>> Gewei
>There are several different ways that the partial autocorrelation
>funtion can be calculated.  Stata's -pac- and -corrgram- commands use
>a linear regression-based technique; see the Methods and Formulas in
>[TS] corrgram for details.
>Another way of computing the PAC's is to use the Yule-Walker equations,
>and the other software packages you mentioned may be doing that. The
>Yule-Walker equations are discussed in many time-series books, including
>Box, Jenkins, and Reinsel's "Time Series Analysis: Forecasting and
>The Yule-Walker method will result in the first PAC being equal to the
>first AC (as is true in the population), but the linear regression method
>Stata uses will not.  On the other hand, the Yule-Walker method does not
>work very well when the series is close to being nonstationary.
>McCullough (1998, Journal of Economic and Social Measurement) discussed
>several different methods, including least squares methods and a method
>based on the Yule-Walker equations.  His results suggest that least
>squares works better than the Yule-Walker-based method.
>Hope this helps.
>   -- Brian Poi
>   -- StataCorp LP
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