Dear George,
I believe that the SAS error parameterization is different from
that of Stata. SAS has y(t) = X'B + v(t)
where v(t)=e(t) - phi1v(t-1)- phi2v(t-2) - ... - phi(m) v(t-m).
Meanwhile, Stata uses
y(t) = X'B + v(t)
with v(t)= phi1v(t-1)+phi2v(t-2) + ... + phi(m) v(t-m)
I hope this helps,
Bob Yaffee
Robert A. Yaffee, Ph.D.
Research Professor
Silver School of Social Work
New York University
Biosketch: http://homepages.nyu.edu/~ray1/Biosketch2008.pdf
CV: http://homepages.nyu.edu/~ray1/vita.pdf
----- Original Message -----
From: "George Kikuchi 菊池 城治" <[email protected]>
Date: Wednesday, February 4, 2009 12:16 pm
Subject: st: SAS proc autoreg and Stata arima
To: [email protected]
> Hello List,
>
> My question may be a too simple question to be asked on the list, but
> I hope some of you may be kind enough to help me out.
>
> I am trying to replicate somebody else's time series analysis that was
> conducted in SAS (proc autoreg, in particular). Below is the SAS code
> that I am trying to replicate, followed by Stata code that I believe
> is doing the same analysis.
>
> Although the regression coefficient estimates by these codes are
> virtually the same, the direction of autoregressive error coefficients
> are in the opposite.
>
> Am I doing something wrong? Do I need to specify certain options to
> get the same results?
>
> **** SAS code ***
> proc autoreg data=test.japan09 all method=ml;
> model murdr = welf gini unemp drate fl urbanper mpr20_29 clr1/ nlag=(1
> 2) dw=6 dwprob;
> run;
>
> *** Stata code ***
> arima murdr welf gini unemp drate fl urbanper mpr20_29 clr1, ar(1/2)
>
>
> *** SAS output ****
> Standard Approx
> Variable DF Estimate Error t Value Pr > |t|
> Variable Label
>
> Intercept 1 -0.2291 1.3726 -0.17 0.8683
> WELF 1 0.0901 0.0139 6.50 <.0001
> GINI 1 2.5837 1.0148 2.55 0.0150
> UNEMP 1 0.0807 0.0464 1.74 0.0901
>
> DRATE 1 -0.1187 0.1509 -0.79 0.4363
>
> FL 1 -0.009282 0.008776 -1.06 0.2967
> URBANPER 1 -0.0159 0.007080 -2.25 0.0302
>
> MPR20_29 1 0.1578 0.0270 5.84 <.0001
> CLR1 1 0.003780 0.003500 1.08 0.2867
> AR1 1 -0.4149 0.1392 -2.98 0.0049
> AR2 1 0.5435 0.1374 3.96 0.0003
>
>
>
>
> *** Stata output***
> ARIMA regression
>
> Sample: 1951 - 2000 Number of obs =
> 50
> Wald chi2(10) =
> 7883.00
> Log likelihood = 61.32109 Prob > chi2 =
> 0.0000
>
> ------------------------------------------------------------------------------
> | OPG
> murdr | Coef. Std. Err. z P>|z| [95% Conf. Interval]
> -------------+----------------------------------------------------------------
> murdr |
> welf | .0900617 .0143372 6.28 0.000 .0619613
> .118162
> gini | 2.583805 .8179648 3.16 0.002 .9806232
> 4.186986
> unemp | .0807053 .0521775 1.55 0.122 -.0215608
> .1829714
> drate | -.1186688 .1867984 -0.64 0.525 -.4847869
> .2474493
> fl | -.009291 .0096179 -0.97 0.334 -.0281418
> .0095598
> urbanper | -.0159288 .0061898 -2.57 0.010 -.0280606 -.0037971
> mpr20_29 | .1577909 .0355243 4.44 0.000 .0881645
> .2274172
> clr1 | .003777 .0050106 0.75 0.451 -.0060437
> .0135977
> _cons | -.2280505 1.405894 -0.16 0.871 -2.983553
> 2.527452
> -------------+----------------------------------------------------------------
> ARMA |
> ar |
> L1. | .4148975 .1494673 2.78 0.006 .121947
> .707848
> L2. | -.5435063 .1329498 -4.09 0.000 -.8040832 -.2829295
> -------------+----------------------------------------------------------------
> /sigma | .0704317 .0093342 7.55 0.000 .0521371
> .0887263
> ------------------------------------------------------------------------------
>
>
> Thank you,
>
> George
>
>
> ***************************************
> George Kikuchi, Ph.D.
>
> National Research Institute of Police Science
> Department of Criminology and Behavioral Sciences
> Crime Prevention Section
>
> 6-3-1 Kashiwanoha
> Kashiwa-shi, Chiba 277-0882
> Japan
>
> TEL: +81-4-7135-8001 ext.2641
> FAX: +81-4-7133-9184
> e-mail: [email protected]
> ***************************************
> *
> * For searches and help try:
> * http://www.stata.com/help.cgi?search
> * http://www.stata.com/support/statalist/faq
> * http://www.ats.ucla.edu/stat/stata/
*
* For searches and help try:
* http://www.stata.com/help.cgi?search
* http://www.stata.com/support/statalist/faq
* http://www.ats.ucla.edu/stat/stata/
