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Re: st: Krinsky and Robb procedure

From   Martin Weiss <>
Subject   Re: st: Krinsky and Robb procedure
Date   Sat, 23 Aug 2008 18:45:29 +0200

Let me try an answer: if you look at the code of wtpcikr.ado, it calls -simulate- in line 57, saving into a -tempfile- with the option -saving(`simdat')-. I was able to turn this -tempfile- into a permanent one by appending the following after line 134 (and saving wtpcikr.ado under a different name (wtpcikr2.ado)):

u `simdat', clear
save mysimdat

This will allow you to access the meanwtp and the medianwtp from each simulation run afterwards.


Quoting German Muchnik Izon <>:

Hi all,

I have a new question. I am estimating 95% confidence
intervals for willingness to pay (WTP) for a good using a
command called wtpcikr that implements the Krinsky and
Robb procedure, recently developed by P. Wilner Jeanty for
stata. Based on a power point presentation given by Jeanty
at the 6th North American Stata Users Group Meeting 2007,
the steps of this procedure is as follows:

1.Estimate the WTP model of interest
2.Obtain the vector of parameter estimates     and the
variance-covariance (VCV) matrix
3.Calculate the Cholesky decomposition, C, of the VCV
matrix such that
4.Randomly draw from standard normal distribution a vector
x with k independent elements
5.Calculate a new parameter vector Z such that
6.Use the new parameter vector Z to calculate the WTP
measures of interest
7.Repeat steps 4, 5, and 6 N(>=5000) times to obtain an
empirical distribution of WTP
8.Sort the N values of the WTP function in ascending order
9.Obtain a 95% confidence interval around mean/median by
dropping the top and bottom 2.5% of the observations

The example given in this presentation is:

drop _all
. set memory 8m
. use south
. gen lbid=ln(bid)
. probit ypay lbid unlimwat govtpur environ waterbill
. wtpcikr lbid unlimwat govtpur environ waterbill urban,
reps(50000) meanl expo

Is there a way in stata to obtain a vector of the mean
WTP's that are estimated in step 6 after each replication.

Thank you!!


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