Re: st: Predicted probabilities after oprobit w/robust standard errors

[Nick Winter <nw53@cornell.edu>]

Beating a horse that I am 95% confident is already dead:

To put it another way, the variance of the underlying distribution (that 
puts you with certain probabilities in each response category) is 
normalized to one in ordered probit.  This is analogous to the standard 
error of the regression (Root MSE).  When we estimate an OLS regression 
with robust standard errors, our estimate of Root MSE does not change -- 
that is, our estimate of the variance of the residuals does not 
change.  What changes is our estimate of the variance of the parameters 
(across hypothetical repeated samples).

--NIck



At 06:14 PM 6/2/2006, you wrote:

> At 02:40 PM 6/2/2006, Nick Winter wrote:
> No.
>
> You are confusing the (sampling) variance of the various estimates, with 
> the variance of the underlying distribution.  The latter is normalized to 
> one regardless of the technique used to estimate the sampling variances.
>
> --NW
--------------------------------------------------------
Nicholas Winter                           607.255.8819 t
Assistant Professor                       607.255.4530 f
Department of Government              nw53@cornell.edu e
308 White Hall            falcon.arts.cornell.edu/nw53 w
Cornell University
Ithaca, NY 14853-4601


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