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st: Re: what's wrong witt bootstrap in seemingly unrelated regression
From |
"Martin Weiss" <[email protected]> |
To |
<[email protected]> |
Subject |
st: Re: what's wrong witt bootstrap in seemingly unrelated regression |
Date |
Sat, 7 Mar 2009 20:17:59 +0100 |
<>
Since the bootstrap is concerned with the estimation of standard errors, it
is natural that your coefs are unaffected. Still, you do have a point in
that a boostrap of -sureg- does indeed end up in error 301
************
sysuse auto, clear
constraint 1 [price]foreign = [mpg]foreign
bootstrap _b, reps(2): sureg (price foreign weight length) (mpg foreign
weight) (displ foreign weight), isure const(1)
************
HTH
Martin
_______________________
----- Original Message -----
From: <[email protected]>
To: <[email protected]>
Sent: Saturday, March 07, 2009 8:05 PM
Subject: st: what's wrong witt bootstrap in seemingly unrelated regression
Dear all,
I am doing seemingly unrelated regression, using "sureg()()(),
const()isure". Since the number of my observations is very small, I am
tring to do it again with bootsrap method. Now I have two questions:
1. The first command I used was " bootstrap _b, reps(500): sureg()()(),
const()isure". But it took such a long time, so I changed reps(500) to
reps(2) to have a try. At the end there is an error: r(301), last
estimations not found.
Then I dropped "isure", so the command becomes " bootstrap _b,
reps(500): sureg()()(), const()". This time the results came out quickly.
Does that mean "bootsrtap" can't be used with "isure"? Why? Then how can
I get the bootsrap results base on my origianl sureg with "isure"? Since
the coef. based on sureg with and without "isure" are totally different.
2. I find the coef. after bootstraping are exactly the same as the
original regression. I am wondering if the only thing I should care about
is p value. If bootsrap p value is similar to the original one, it means
the original regression results based on small number of observations is
correct. Is it right?
Thank you very much!
Jingjing Li
U of T
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