[Limdep Nlogit List] Problems in Nested Multinomial Logit Model

William Greene wgreene at stern.nyu.edu
Wed Sep 10 22:01:38 EST 2008


Dear Ester Ramos Pérez: The line search error indicates that it is
not possitle to fit your model with the weights. The log likelihood
has changed only slightly from entry to exit. This is an indicator 
of a problem in your specification of the model - here it because 
of the weights. Without the data in hand, I cannot be any more specific
than that. For the second question you raised, your model is not 
identified. I would guess that the problem is the constant term in 
the utility function for Public. If you remove BP from the equation, I
suspect that the rest of the model will be estimated OK. When a model is
overspecified, it will predict the outcomes as well as one that is
not - that is why you are finding that the unidentified model is
"very good."
/B. Greene

----- Original Message -----
From: To: limdep at limdep.itls.usyd.edu.au
Cc: Sent: Wednesday, September 10, 2008 7:50:12 AM GMT -05:00 US/Canada Eastern
Subject: [Limdep Nlogit List] Problems in Nested Multinomial Logit Model

 

We're fitting a nested multinomial logit model. As a response variable we have three alternatives (public transport, car and motorcycle). The syntax of the model, which we use, is:
 
NLOGIT;Lhs=MODE,N_ALT,ALT; Wts=ELEV;
Choices=Public,Cotxe,Moto;
Tree=Travel[TP(Public),VP(Cotxe,Moto)];
Model:
U(Cotxe)=BC+BCC*CGCO+BCA*DIA+BCR*RISC/
U(Moto)=BMC*CGMO/
U(Public)=BP+BPC*CGTP+BPI*INT1;
PrintVC;Crosstab;
Describe;List;ShowTree;Effects:;Pwt;Means$
 
 
When we obtain the results after the execution of the model, we can see these two errors.
 
Line search does not improve fn. Exit iterations. Status=3
  Error   806: Line search does not improve fn. Exit iterations. Status=3
Function=  .11853876438D+06, at entry,  .11812641048D+06 at exit
  Error  1025: Failed to fit model. See earlier diagnostic.
 
 
Our first question is what's the meaning of these errors, and how can we solve them? 
 
 
According to the above, We're fitting the same model without weight. The syntax of the model, which we use, is (without weight):
 
NLOGIT;Lhs=MODE,N_ALT,ALT;
Choices=Public,Cotxe,Moto;
Tree=Travel[TP(Public),VP(Cotxe,Moto)];
Model:
U(Cotxe)=BC+BCC*CGCO+BCA*DIA+BCR*RISC/
U(Moto)=BMC*CGMO/
U(Public)=BP+BPC*CGTP+BPI*INT1;
PrintVC;Crosstab;
Describe;List;ShowTree;Effects:;Pwt;Means$
 
 

Now, the results in all parameters of Public transport are not significant.

 

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

|Variable | Coefficient  | Standard Error |b/St.Er.|P[|Z|>z] |

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

          Attributes in the Utility Functions (beta)

 BC             .66774715      .08919300     7.487   .0000

 BCC           -.07808303      .01075774    -7.258   .0000

 BCA          -2.51885645      .15944988   -15.797   .0000

 BCR           -.06917638      .00737276    -9.383   .0000

 BMC           -.13290383      .02072193    -6.414   .0000

 BP            -.76015104     158.734729     -.005   .9962

 BPC           -.03802969     7.94136259     -.005   .9962

 BPI           -.38789100     80.9993955     -.005   .9962

          IV parameters, tau(j|i,l),sigma(i|l),phi(l)

 TP            2.10762224     440.113628      .005   .9962

 VP            2.35485967      .12374261    19.030   .0000

 
 

We don't understand why, because if we apply the model the degree of success is very good

 
Could you help us?
 

 

 

Ester Ramos Pérez

 

Gabinet d'Estudis

Transports Metropolitans de Barcelona

Tf. 93 298 75 57

Fax: 93 298 71 21

E-mail: eramosp at tmb.net <mailto:eramosp at tmb.net> 

 

 



 
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