Hello, everybody,
I am currently evaluating two choice experiments and have read a lot of information about different estimation models. During my research I came across the possibility to estimate e.g. Mixed Logit or G-MNL models directly in WTP space instead of doing the estimates in the preference space. Now I asked myself if this is also possible for HB models? And if so, how?
My second question refers to the beta drawings in HB estimation process. The individual beta parameters are the average values of the drawings after the burn-in phase, e.g. averaging the last 2000 drawings. Now I wonder if it makes sense to use the distribution of these drawings instead of the mean value in the WTP calculations. So I could again make a drawing from the 2000 drawings, and I could do this for both the price coefficient and an attribute coefficient. The ratio of the price coefficient to the attribute coefficient would result in the WTP estimate for this one drawing. The whole thing could be done many times, for example 20,000 times. As a result, I would not have one WTP value per individual, but a distribution of the individual willingness to pay. In this way, the uncertainties from the drawings would be included in the WTP estimates.
What do you think?
Many greetings
Nico