Choice analysts increasingly use a mix of revealed preference and stated choice data paradigms to identify preferences of samples of individuals that are used to infer behavioural response and willingness to pay for specific attributes. These data are in a sense artificial constructs that are developed to approximate real choice settings of the way that individuals process relevant information in making choices. As such, all data designs formalized through a survey instrument seek information through questions that become descriptions of events and as such the probabilities of choice that are of interest are strictly probabilities attached to event descriptions and not choice probabilities of events per se. The recognition of this distinction, initially noted by Kahneman et al. [Kahneman, D., Slovic, P., Tversky, A., 1982. Judgement under uncertainty: Heuristics and biases. Cambridge University Press, New York], can be captured, at least in part, through the idea of process heterogeneity, as a way of recognizing and accounting for the many ways in which individuals process information, and in part is influenced by the way the analyst describes the context in which preference data is sought. Building on previous contributions on attribute processing, this paper draws on recent empirical evidence to further reinforce the importance of joint modelling of process and outcome in choice analysis. This study adds to the evidence of a trend emerging on the upward bias of mean estimates of marginal willingness to pay when ignoring process heterogeneity.
Download Info
To download:
If you experience problems downloading a file, check if you have the
proper application to
view it first. Information about this may be contained
in the File-Format links below. In case of further problems read
the IDEAS help
page. Note that these files are not on the IDEAS
site. Please be patient as the files may be large.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
Volume (Year): 43 (2009) Issue (Month): 2 (February) Pages: 117-126 Download reference. The following formats are available: HTML
(with abstract),
plain text
(with abstract),
BibTeX,
RIS (EndNote, RefMan, ProCite),
ReDIF