Dear Statalist members,
I am estimating a mixed logit model in WTP-space with the user-written command mixlogitwtp by Arne Risa Hole. The sign of the price variable was changed as the model assumes the coefficient to be log-normally distributed.
With about 50,000 rows of data from a choice experiment and 15 random coefficients to estimate, the model has now been running for a good week. The number of replications was set to 500, with 45 burnt. The “difficult” option was also specified. I have already dropped the alternative-specific constant from the model because of the output “numerical derivatives are approximate. flat or discontinuous region encountered”.
The software is now performing its 84th iteration. The log-likelihood rose from the initial value of - 19508.876 to the current one of -19367.784, with improvements in the first 5 digits not taking place since iteration #36. No “(not concave)” message was seen for the past 37 iterations.
Given this background and my lack of previous experience in estimating models in WTP-space, I was wondering:
Best regards,
Veronica
I am estimating a mixed logit model in WTP-space with the user-written command mixlogitwtp by Arne Risa Hole. The sign of the price variable was changed as the model assumes the coefficient to be log-normally distributed.
With about 50,000 rows of data from a choice experiment and 15 random coefficients to estimate, the model has now been running for a good week. The number of replications was set to 500, with 45 burnt. The “difficult” option was also specified. I have already dropped the alternative-specific constant from the model because of the output “numerical derivatives are approximate. flat or discontinuous region encountered”.
The software is now performing its 84th iteration. The log-likelihood rose from the initial value of - 19508.876 to the current one of -19367.784, with improvements in the first 5 digits not taking place since iteration #36. No “(not concave)” message was seen for the past 37 iterations.
Given this background and my lack of previous experience in estimating models in WTP-space, I was wondering:
- Whether there is any hope for me to see the log-likelihood function converge with the current settings;
- Should this not be the case, and if you do not believe that the problem lies in the model being empirically unidentified, it would be nice if someone could indicate any possible trick to facilitate convergence. For instance, would specifying a matrix of initial WTP values obtained through estimation of the model in preference space speed up the process? And can some variables, whose coefficients in preference space were not significant, be dropped from the model in WTP space?
Best regards,
Veronica
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