st: Comparing bootstrapped estimates across two models

[Matthew Wibbenmeyer <mwibbenmeyer@gmail.com>]

Hi all,

I'm engaged in a choice modeling study in which wildfire managers were
asked to select their **preferred** management strategy and their
**expected** strategy  given current political and social constraints.
I want to compare willingness-to-pay values derived from two models
with different dependent variables: choice_expected and
choice_preferred. WTP values are ratios between coefficients so they
have no distribution and a distribution must be estimated using
bootstrapping (or parametric bootstrapping).

My question has two parts:
1) What formal test can I use to test the significance of the
difference between bootstrapped WTP estimates from two models with
different dependent variables?
2) How can I implement this following my bootstrap commands, which
look like this:

bootstrap wtp1 = ((-1)*(_b[homes]/_b[cost])), reps(100) seed(12345)
cluster(obsid) dots: ///
clogit choice_exp homes watershed aviationhours grounddays duration cost ///
, group(obsid)

bootstrap wtp2 = ((-1)*(_b[homes]/_b[cost])), reps(100) seed(12345)
cluster(obsid) dots: ///
clogit choice_pref homes watershed aviationhours grounddays duration cost ///
, group(obsid)

Thanks in advance for any help anyone can offer!

Matt Wibbenmeyer
USDA Forest Service
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