st: Fwd: -cmp- not concave

["Z. Liu" <zl290@cam.ac.uk>]

Dear all,

I've been trying to fit a bivariate tobit model using the user-written 
command -cmp-. The model looks like this:

cmp (equation1: y1 = X1) (equation2: y2 = y1 + X2), indicators(2 2) 
robust

This model doesn't work out. Stata keeps showing 'log pseudolikelihood = 
0 (not concave)'. I tried to start with minimum regressors (1-2 
explanatory variables) in each equation, but the problem remains. I also 
tried alternative ml options such as - tech(dfp)- and -difficult- but 
still can't fix it. However, the two tobit equations can be estimated 
separately, although the Pseudo R2 is quite small (around 5%). As well, 
the system model
can be estimated if I change the two tobit equations into linear 
equations. Some descriptive statistics of the two dependent variables 
are as follows:

y1: Percentiles: 1% (0), 25% (0), 50% (23.57), 99% (6127.14); mean 
(365.00); SD (1186.90); Skewness (7.14); Kurtosis (71.23)

y2: Percentiles: 1% (0), 50% (0), 75% (0), 90% (78.10), 99% (1128.53); 
mean (61.29); SD (401.82); Skewness (13.27); Kurtosis (217.49)

Anybody out there knows what might be the problem? Any advice or 
suggestions
would be appreciated. Thanks a lot in advance.


Best Regards,


Leo


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