[Limdep Nlogit List] bivariate probit

[William Greene]

I agree with Fred.  The .99+ almost surely indicates some kind of model
misspecification.  The bivariate probit with selection is using a pretty
accurate quadrature method for the bivariate normal (a routine written
by Jerry Hausman), but you can't adjust the number of quadrature points.
I would look at the variables in the two equations. There is a problem 
variable in there somewhere.
/Bill Greene

----- Original Message -----
From: "Fred Feinberg" <feinf at umich.edu>
To: "Limdep and Nlogit Mailing List" <limdep at limdep.itls.usyd.edu.au>
Sent: Sunday, November 4, 2007 11:38:20 AM (GMT-0500) America/Bogota
Subject: Re: [Limdep Nlogit List] bivariate probit

You *could* report the results, but probably shouldn't. Rho up near 0.99 almost
certainly indicated one of three things: (1) an important omitted variable; (2)
a model misspecification; (3) a flat-out error.

It is very unlikely that the fit at 0.99 is a true maximum. It may be a holdover
from the estimation's approximation method, which I believe is either some form
of quadrature or quasi-Monte-Carlo. Those methods work well IF enough estimation
points are used. Have you tried using a larger value? You may discover that your
0.99 value changes. [See the documentation for how to do this.]

A telltale sign is that the *substantive* results -- particularly the size of
Rho -- change radically when any variables are subtracted. It's actually more
common to have Rho go up when you leave out a variable, because that variable is
now unavailable to 'remove' its effects from the model's two equations, whose
error would then be more correlated. Of course, taking out a variable can
increase the overall error in the model, so Rho can go down, too; but this is
less common.

I'm curiour what Prof. Greene might say, but my own experience with Heckman-type
models indicates that this particular solution probably isn't an accurate
representation of what's going on in your data.

Fred

=====

Fred Feinberg
Hallman Fellow and Professor of Management
Stephen M. Ross School of Business
University of Michigan
feinf at umich.edu

"Dr. Anat Tchetchik" wrote:

> We are running via  NLOGIT a bivariate probit with selection (which  uses
> the atanh(rho) during estimation) and keep receiving very high and
> significant Rho (0.99 but never 1), The model results, other than that, are
> reasonable and fit our expectations.  when we omit variables from the model,
> rho decreases substantially and become insignificant.  Can we report our
> results with such rho?
> Thanks,
> Anat Tchetchik, Ph.D.
> The Department of Agricultural Economics
> The Hebrew University of Jerusalem
> Tel: 08-9489231
> cell: 054-4928740
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-- 
Professor William Greene
Department of Economics
Stern School of Business
New York University
44 West 4th St., Rm. 7-78
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