[Limdep Nlogit List] Nested Logit Model

[Sabir, M. (Muhammad)]

Dear all,

 

 I am trying to estimate the nested logit model with follwing details; 

 

 

NLogit

;Lhs= choice, cset, altij

;Choices = C, B, T, O, N

;crosstabs

; tree = Yes(C,B,T, O),  No(N)

;start=logit

;ivset:(No)=[1.0]

;Model:

 U(C) = bc + b11*X1+b12*X2 /

 U(B) = bB + b21*X1+b22*X2 /

 U(T) = bT + b31*X1+b32*X2 /

 U(O) = bO + b41*X1+b42*X2  /

 U(N) =      b51*X1+b52*X2   

  ; utility = u1 $

 

Where X1 and X2 are individual specific and do not varies across the
choices. 

 

when I run the above model I get the following errors;

 

+---------------------------------------------+

| Discrete choice and multinomial logit models|

+---------------------------------------------+

Hessian is not positive definite at start values.

  Error   803: Hessian is not positive definite at start values.

B0 is too far from solution for Newton method.

Switching to BFGS as a better solution method.

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.)

 

 

After these error messages, it provides the output for MNL however there
are many coefficients missing (Coefficients are there but their standard
deviation are not provided. Only written fixed parameters). 

 

And then the following error messages comes too. 

 

Initial iterations cannot improve function.Status=3

  Error   805: Initial iterations cannot improve function.Status=3

Function=  .46408498810D+05, at entry,  .46408498810D+05 at exit

  Error  1025: Failed to fit model. See earlier diagnostic.

 

I have no idea/guess what is going wrong ? 

 

Can anyone suggest that what could be the possible reason for collapse
of the model ? and any possible direction to correct for that ?

 

Thanks in advance. 

 

 

Kind regards,

Muhammad