No-choice dummy WTP interpretation

[tomschuette]

Greetings,

I ran multiple discrete choice experiments in which I included a no-choice/status quo option. In the analysis, I included a dummy variable for the no-choice option. My question now is how to interpret a no-choice dummy in terms of WTP. Say my model is an unlabeled choice experiment where one chooses between different types of cars. Can I then interpret the (negative) WTP value for the no-choice dummy (either from preference space or a WTP space model) as the mean WTP for any car, independent of the attributes? I cannot think of any other way to interpret it, but I am unsure if I can do that at all.

Another thing that made me wonder about the interpretability of the WTP value of the no-choice dummy is that the WTP value from both preference and WTP space models is much higher than the levels of the cost attributes we included, meaning that the respondents were not even able to express that WTP value through their choices...

In the end, what I want is to say what the average WTP for choosing an option (buying) in an unlabelled DCE is, regardless of the attributes.

I am using Stata 17 with the mixlogit command for my models.

I am grateful for any help and tips regarding this.

[Michiel Bliemer]

The opt-out alternative either has a utility of zero or a constant. It is easiest to interpret if it is set to zero.

U(A) = b0 + b1*X1 + ... + bc*Cost
U(B) = b0 + b1*X1 + ... + bc*Cost
U(optout) = 0

Perhaps you are referring to the alternative-specific constant because an opt-out alternative cannot have a dummy variable because it has no attributes.

b0 represents the preference of purchasing a car, versus not purchasing a car, ALL ELSE BEING EQUAL (so X1=0, X2=0, Cost=0). I am not sure whether it is meaningful to use b0 as a WTP to purchase a car because it assumes that the car costs nothing. WTP is usually only computed for attributes, not for constants, I would not use constants to interpret WTP.

In simple experiments one sometimes checks the so-called boundary WTP values to ensure that the ranges and trade-offs in the choice experiment allow a wide range of WTP in the population, i.e. ensuring that cost levels are wide enough. For example, in transport they sometimes look at Boundary Value of Travel Time (BVTT), see for example https://link.springer.com/article/10.1007/s11116-020-10139-3.

Michiel