Discrete choice models , willingness to pay , credible sets
Abstract:
Previous literature on the distribution of willingness to pay has focused
on its heterogeneity distribution without addressing exact interval estimation.
In this paper we derive and analyze Bayesian confidence sets for quantifying
uncertainty in the determination of willingness to pay for carbon
dioxide abatement. We use two empirical case studies: household decisions
of energy-efficient heating versus insulation, and purchase decisions of ultralow-
emission vehicles. We first show that deriving credible sets using the
posterior distribution of the willingness to pay is straightforward in the case
of deterministic consumer heterogeneity. However, when using individual
estimates, which is the case for the random parameters of the mixed logit
model, it is complex to define the distribution of interest for the interval
estimation problem. This latter problem is actually more involved than determining
the moments of the heterogeneity distribution of the willingness
to pay using frequentist econometrics. A solution that we propose is to derive
and then summarize the distribution of point estimates of the individual
willingness to pay under different loss functions.
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