st: Mfx in tobit: same significance across mfx?

[Ryan Edwards <REdwards@gc.cuny.edu>]

I'm using Stata 10's "svy: tobit" routine, but I'd like to look at  
different marginal effects than the default, which are the beta  
coefficients in the latent variable model.

The standard solution would be to run "mfx" afterward.  The problem is  
that running mfx after svy: tobit (still) takes an extremely long time  
to report the standard errors.  mfx, nose is much quicker, of course.   
So my question is whether I have to pretend I'm a grad student in the  
1970s and run my large number of models overnight, or if there's a  
convenient shortcut.

Interestingly, in the old "dtobit" routine from STB56, for each  
independent variable the ratios of coefficients to their standard  
errors across all the various marginal effects are exactly the same.

http://stata-press.com/journals/stbcontents/stb56.pdf

Presumably the various scaling factors, which I think are things like  
the cdf, pdf, and sigma, were treated as constants in that code, so  
the ratio of coefficient to standard error is always the same  
regardless of the particular marginal effect of interest.  If true,  
this would be a nice shortcut to getting transformed standard errors  
indeed.

But I don't see quite the same thing when actually running svy: tobit  
and then mfx afterward (once it finally cranks everything out).  As I  
think is typical, the primary svy: tobit returns a t-stat while mfx  
returns a z-stat, but more importantly, the ratios of coefficients to  
standard errors are decidedly different between the default tobit  
output and the mfx output.

Could this be due to the svy augmentation?  Or is it erroneous?  Or  
does it reveal a problem in the original dtobit code?

Ryan Edwards
Assistant Professor of Economics
Queens College and the Graduate Center
City University of New York
redwards@qc.cuny.edu
tel: 718-997-5189
fax: 718-997-5466
http://qcpages.qc.cuny.edu/~redwards/

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