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From |
"Kit Baum, Faculty Micro Resource Center" <fmrc@bc.edu> |

To |
StataList <statalist@hsphsun2.harvard.edu> |

Subject |
st: re: std error covariances between equations |

Date |
Fri, 13 Sep 2002 21:03:49 -0500 |

I believe that Alan's problem, in a two-equation context, could be viewed as

looking for the covariance term

cov [x1 0] V [0 x2'] = x1 V12 x2'

using V12 to refer to the NE block of the

covariance matrix. Alternatively, we could be looking for

cov [0 x2] V [x1' 0] = x2 V21 x1'

where V21 is the SW block of the covariance

matrix. Since x1 and x2 may have different numbers of columns, these off-diagonal blocks are not symmetric.

The predict option stddp calculates the standard error of the difference in

linear predictions. Using the same algebra, and the formula given in [r] predict,

this is x1 V11 x1' - x2 V21 x1' - x1 V12 x2' + x2 V22 x2'

where the first and last terms are related to the variances of the two individual equations. It would seem like they could be calculated (via stdp for each equation) and added, and the result negated. Without working it out in detail, I am not sure how - [- x2 V21 x1' - x1 V12 x2' ] relates to what Alan seeks, but it seems like you ought to be able to get it out of this.

Since Stata will calculate this stddp for any pair of equations, it would

be quite straightforward to have an ado do all the necessary predicts (for

both the stdp and stddp) and crank out the desired quantities, even for >2 eqns,

if they can be derived from the stddp magnitudes.

Kit

--------------------------------------------------------------------

Kit Baum, Faculty Micro Resource Center fmrc@bc.edu

Academic Technology Services, Boston College http://www.bc.edu/ats

http://fmwww.bc.edu/FMRC/ http://fmwww.bc.edu/GStat/

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