Dear Bart, dear all,
Please read this e-mail even if you are not interested in my response to
Bart's question as you might be in the position to answer my follow-up
question. ;-]
There seems to be no ado-file like IVoprobit or IVmprobit. However, you
should be able to do something like that "by hand". I'm certainly not expert
on this field, but here is an example of how such a "self made" code could
look like:
clear
sysuse auto
xtile y2 = mpg, nq(3)
quietly tab y2, gen(y2_)
rename price y1
rename trunk z
rename weight x
* First-stage ordered probit:
oprobit y2 z x
predict p1 p2 p3, p
* Second-stage OLS:
regress y1 p2 p3 x
* Correction of standard errors:
drop p2 p3
rename y2_2 p2
rename y2_3 p3
predict residuals, resid
replace residuals = residuals^2
quietly sum residuals
scalar realmse = r(mean)*r(N)/e(df_r)
matrix bmatrix = e(b)
matrix Vmatrix = e(V)
matrix Vmatrix = e(V) * realmse / e(rmse)^2
ereturn post bmatrix Vmatrix, noclear
ereturn display
clear
Now, here is/are my follow-up question(s):
a) What would the above code have to look like if I wanted Stata to return
ROBUST corrected standard errors, i.e. if I wanted to use the
Huber/White/sandwich estimator of variance?
b) What would it have to look like to use clustering, let's say, using the
variable "foreign" to specify to which group each observation belongs?
Thank's for helping me out!
Best regards,
Tobias
On 3/13/06, Bart Vanneste <[email protected]> wrote:
Dear,
Is it possible to use an instrumental variable approach with ordered or
multinomial probit (or logit for that matter)? ivprobit / ivlogit seem to
deal only with binary dependent variables.
In recent months several other posts have asked the same question, but to my
knowledge a satisfactory solution has not been given.
Your response is greatly appreciated.
Best,
Bart
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