[Limdep Nlogit List] Problems when Estimating Multivariate Probit Model

Peter Tarmo Savolainen bb2725 at wayne.edu
Wed Oct 13 05:09:24 EST 2010

Hello all,

I am trying to estimate a multivariate probit model for six interrelated binary outcomes.  My model has been structured as follows:

LHS = Y1,Y2,Y3,Y4,Y5,Y6;
EQ1 = X1,Y2,Y3,Y4,Y5,Y6;
EQ2 = X2,Y4;
EQ3 = X3,Y6;
EQ4 = X4,Y2;
EQ5 = X5,Y3,Y6;
EQ6 = X6,Y3;
PTS = 50$

X1 through X6 correspond to vectors of independent variables (the specific variables included in X differ among the six models).  When running the model in NLOGIT, I receive the following error messages:

"Error   130: Models - Regression; insufficient degrees of freedom.
Line search does not improve fn. Exit iterations. Status=3
Check derivatives (with ;OUTPUT=3). This may be a solution
if several iterations have been computed, not if only one.
Error   806: (The log likelihood is flat at the current estimates.)"

I am particularly concerned with Error 130, which is reported five times in a row.  From the structure presented above, does it appear that I have over-specified my model?  Is there something else that leads to this particular error message?  I did not run into any issues previously when dealing with a smaller number of outcomes and fewer simulations points.  My dataset includes 4,962 observations and the less-frequent of the 6 outcomes occur slightly over 100 times.  Any insight would be very much appreciated.


Peter T. Savolainen, Ph.D., P.E.
Assistant Professor
Department of Civil and Environmental Engineering
Wayne State University-Transportation Research Group
5050 Anthony Wayne Drive, EDC 0504.01
Detroit, MI 48202
Phone: (313) 577-9950
Fax: (313) 577-8126

More information about the Limdep mailing list