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Re: st: Marginal effects for bivariate probit


From   Joseph Capuno <[email protected]>
To   [email protected]
Subject   Re: st: Marginal effects for bivariate probit
Date   Mon, 17 Nov 2003 16:18:42 -0800 (PST)

Stephen,

Thanks a lot

Joseph J. Capuno
--- "Stephen P. Jenkins" <[email protected]> wrote:
> On Fri, 14 Nov 2003 16:13:16 -0800 (PST) Joseph
> Capuno 
> <[email protected]> wrote:
> 
> > Hi! I've been running a bivariate probit
> regression
> > and try to obtain the marginal effects using the
> 'mfx
> > compute" option. However, I fail to obtain the
> > marginal effects in most of the runs, and in those
> > cases when I do Stata does not compute the
> standard
> > errors. 
> > I would appreciate it somebody could help me out
> with
> > the following questions:
> > (1) Is there a way for me to compute the standard
> > errors myself? 
> 
> You can program the analytical formulae, but it is
> complicated.
> Formulae are given in 
> Christofides LN, Stengos T, Swidinsksy R (1997)
> "On the calculation of marginal effects in the
> bivariate probit model"
> Economics Letters 54, 203-208
> with an important Corrigendum by Christofides LN,
> Hardin JW and Stengos 
> T (2000) Economics Letters 68, 339, which indicated
> tersely that many 
> of the original formulae were wrong. I am not sure
> that the Corrigendum 
> resolved everything either (it is very terse).  
> 
> The help file to Tomas Bartus's program -margin-
> states that it 
> calculates marginal effects for -biprobit-, but I
> have not checked that 
> it uses the analytical formulae cited above.
> 
> 
> > (2) And, how do I interpret Stata's estimates of
> the
> > marginal effects with no standard errors? How much
> > confidence can I attach to these estimates?
> > (3) Sometimes Stata reports "." when a standard
> error,
> > z-stat, P>|z|, Wald statistic or a chi-squared
> > statistic is expected? What does "." mean in this
> > context? No estimate? 
> 
> I suspect both symptoms are related, and connected
> to an inability to 
> invert the relevant Hessian matrix (as it is close
> to singular) -- 
> required to calculate the s.e.s. Also check whether
> your original model 
> is well-conditioned (e.g. no very large
> coefficients)
> 
> 
> Stephen
> ----------------------
> Professor Stephen P. Jenkins <[email protected]>
> Institute for Social and Economic Research (ISER)
> University of Essex, Colchester, CO4 3SQ, UK
> Tel: +44 (0)1206 873374. Fax: +44 (0)1206 873151.
> http://www.iser.essex.ac.uk
> 
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