Stata The Stata listserver
[Date Prev][Date Next][Thread Prev][Thread Next][Date index][Thread index]

st: Re: Seemingly unrelated regression or similar estimation


From   "Scott Merryman" <smerryman@kc.rr.com>
To   <statalist@hsphsun2.harvard.edu>
Subject   st: Re: Seemingly unrelated regression or similar estimation
Date   Tue, 23 Sep 2003 21:17:46 -0500

----- Original Message ----- 
From: "Ed Levitas" <levitas@uwm.edu>
To: <statalist@hsphsun2.harvard.edu>
Sent: Tuesday, September 23, 2003 9:25 AM
Subject: st: Seemingly unrelated regression or similar estimation


> Statalisters,
> 
> I have two equations:
> 
> F = B(0) + B(1)var1 + B(2)var2 + U(1)
> G = Y(0) + Y(1)var1 + Y(2)var2 + U(2)
> 
> F is continuous and G is a positive integer.  Are there ways I can perform
> joint tests of coefficients across the two equations (e.g. B(1) = Y(1) = 0).
> This seems like a Seemingly Unrelated Regression.  But given the difference
> in error distributions, I would think some major modifications are in order.
> Can anyone suggest recommendations (e.g. ado files), citations, etc.
> 
> Thanks in advance for your time and consideration.
> 
> -Ed
> 

How about Seeming Unrelated Estimation -suest-

Example:

. use "C:\Stata8\auto.dta", clear
(1978 Automobile Data)

. qui poisson rep mpg weight for, score(A)

. est store poisson

. qui reg price mpg weight for, score(B)

. est store OLS

. suest poisson OLS

Simultaneous results for poisson, OLS
                                                            Obs      =      74

------------------------------------------------------------------------------
             |               Robust
             |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
poisson_r~78 |
         mpg |   .0143303    .005316     2.70   0.007     .0039112    .0247494
      weight |   .0000841   .0000604     1.39   0.164    -.0000343    .0002025
     foreign |   .3581404    .095116     3.77   0.000     .1717164    .5445644
       _cons |   .5416934   .2650292     2.04   0.041     .0222457    1.061141
-------------+----------------------------------------------------------------
OLS_mean     |
         mpg |    21.8536   79.07015     0.28   0.782    -133.1211    176.8283
      weight |   3.464706   .7614705     4.55   0.000     1.972251    4.957161
     foreign |    3673.06   651.1297     5.64   0.000      2396.87    4949.251
       _cons |  -5853.696    3793.29    -1.54   0.123    -13288.41    1581.017
-------------+----------------------------------------------------------------
OLS_lnvar    |
       _cons |   15.32848   .2000052    76.64   0.000     14.93647    15.72048
------------------------------------------------------------------------------

. test [poisson_rep78]mpg =0

 ( 1)  [poisson_rep78]mpg = 0

           chi2(  1) =    7.27
         Prob > chi2 =    0.0070

. test [OLS_mean]mpg =0, accum

 ( 1)  [poisson_rep78]mpg = 0
 ( 2)  [OLS_mean]mpg = 0

           chi2(  2) =    7.35
         Prob > chi2 =    0.0253


Hope this helps,
Scott



*
*   For searches and help try:
*   http://www.stata.com/support/faqs/res/findit.html
*   http://www.stata.com/support/statalist/faq
*   http://www.ats.ucla.edu/stat/stata/



© Copyright 1996–2021 StataCorp LLC   |   Terms of use   |   Privacy   |   Contact us   |   What's new   |   Site index