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From |
SamL <saml@demog.berkeley.edu> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
RE: st: What is seemingly unrelated regression? |

Date |
Wed, 11 Jul 2007 10:26:31 -0700 (PDT) |

I don't think so. I think you need to use 2sls or 3sls for such situations, or perhaps some other models. HTH Sam On Wed, 11 Jul 2007, Mak, Timothy wrote: > Thanks Sam. > > If you don't mind, one more question: When using SUR, can we have > variables being both independent and dependent, ie dependent in one > equation and independent in another? Ie, can we use it to fit some > simple structural equation models? > > Tim > > > -----Original Message----- > From: owner-statalist@hsphsun2.harvard.edu > [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of SamL > Sent: 10 July 2007 17:01 > To: Stata Listserve > Cc: SamL@demog.berkeley.edu > Subject: RE: st: What is seemingly unrelated regression? > > Responses below: > > On Tue, 10 Jul 2007, Mak, Timothy wrote: > > > Dear Sam, > > > > I'm not sure I understand your notation. Supposedly X is an > > independent variable that is shared between the equations, whereas Z > > and Q are variables that are not shared. > > Correct. > > > So do you imply that SUR is only useful when at least one independent > > variable is shared across equations? > > > > No. As I said, the efficiency increase only occurs if at least one of > the variables differs across equations. However, the ability to test > coefficients across equations remains. > > Second, none of the variables need to be shared across equations. But, > because the usual researcher finds themselves placing some of the > independent variables in two different equations, I included X in both > to indicate that was allowed. > > > > In any case, the question why using SUR produces markedly biased > > estimates in my simple illustration still begs an answer. > > > > I tried to clarify that SUR is not for a situation where there is only > one Y. If I understand, your simulation produces only one Y. Thus, the > simulation is not appropriate. > > HTH > Sam > > > Thanks for your help. > > > > Tim > > > > > > > > -----Original Message----- > > From: owner-statalist@hsphsun2.harvard.edu > > [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of SamL > > Sent: 10 July 2007 15:29 > > To: statalist@hsphsun2.harvard.edu > > Cc: SamL@demog.berkeley.edu > > Subject: Re: st: What is seemingly unrelated regression? > > > > This is my favorite model. SUR is a multi-equation model. If you > > have more than one y y's (y1 and y2, say), you could run multiple > > regressions: > > > > y1=f(X+Z)+e_1 > > y2=g(X+Q)+e_2 > > > > If Z and Q differ, it is asymptotically more efficient to estimate the > > > equations jointly. If Z and Q do not differ, it is not more efficient > > > to estimate the equations jointly, but it can still be advantageous to > > > do so because joint estimation allows an appropriate test of > > coefficients across equations. > > > > I do not have my econometrics textbooks here (I am traveling) but I > > believe this model is discussed in the usual suspect textbooks (e.g., > > Maddala, Goldberger, Judge et. al.) The Zellner citation is: > > > > Zellner, A. 1962. "An Efficient Method of Estimating Seemingly > > Unrelated Regressions and Tests for Aggregation Bias." Journal of the > > > American Statistical Association. 57: 348-368 > > > > HTH > > Sam > > > > On Tue, 10 Jul 2007, Mak, Timothy wrote: > > > > > Hi Statalist, > > > > > > Forgive me for more of a statistical question than a Stata question, > > > > but I only recently found out about seemingly unrelated regression > > > (SUR). I dug up the Zellner (1962) paper, and it says that: > > > > > > Under conditions generally encountered in practice, it is found > > that > > > the regression coefficient estimators so obtained are at least > > > asymptotically more efficient than those obtained by an > > > equation-by-equation application of least squares. > > > > > > Interesting claim - does it imply that whenever we're doing more > > > than one regression on the same dataset, we should be using SUR? > > > > > > Anyway, I ran a small test. First I created a 5-dimensional > > > multivariate normal sample of size 10000. Correlations between the 5 > > > > variables are all 0.3. I generated y = 0.1 * (x1+ x2 + x3 + x4 + x5) > > > > + > > > > > u, where x1-x5 are the variables just created, and u is an error > > > term generated separately by -uniform-. And I regressed y on x1, x2, > > > > x3, etc, separately using -reg-, and together using -sureg-. As > > > expected the > > > -reg- estimates were around 0.22 (=0.1 + 4 * 0.3 * 0.1 + ...). But > > > the > > > -sureg- estimates were around 0.02. If these were estimates of the > > > relationship between y and x1, x2, etc, then these are clearly > biased. > > > > > I suppose then that these estimates are not estimating the same > > > things > > > > > as > > > -reg- estimates. But then what are these estimating? > > > > > > Sorry if this is really elementary. I haven't studied econometrics > > > but > > > > > would like to learn a bit more about statistics. > > > > > > Thanks, > > > > > > Tim > > > > > > * > > > * 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/ > > > > > * > > * 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/ > > > > * > > * 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/ > > > * > * 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/ > > * > * 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/ > * * 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/

**References**:**st: What is seemingly unrelated regression?***From:*"Mak, Timothy" <Timothy.Mak@iop.kcl.ac.uk>

**Re: st: What is seemingly unrelated regression?***From:*SamL <saml@demog.berkeley.edu>

**RE: st: What is seemingly unrelated regression?***From:*"Mak, Timothy" <Timothy.Mak@iop.kcl.ac.uk>

**RE: st: What is seemingly unrelated regression?***From:*SamL <saml@demog.berkeley.edu>

**RE: st: What is seemingly unrelated regression?***From:*"Mak, Timothy" <Timothy.Mak@iop.kcl.ac.uk>

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