Thinking and Deciding

THE MEASUREMENT OF UTILITY 337
benefit. The findings suggest that contingent valuation methods may be improved by
eliminating information from which costs could be inferred, so that respondents can
focus more easily on benefits alone.
WTA (willingness to accept) is larger than WTP
A general result in CV is that willingness to accept (WTA) is larger than WTP
(Mitchell and Carson, 1989). For example, the minimum WTA for a change in the
pollution level from ten to twenty units is about twice the WTP for a reduction from
twenty to ten. This is an example of the status-quo bias (Chapter 12).
Several studies have succeeded in manipulating the effect. Irwin (1994) found
that this kind of effect was greater for environmental goods than for market items,
and she presented evidence that the difference was the result of respondents’ moral
concerns about making the environment worse. Marshall, Knetsch, and Sinden
(1986) found that WTA versus WTP effects do not occur for advisers (as opposed to
decision makers). A possible explanation of this result is that the norm prohibiting
accepting money in return for losses (even personal losses) might be “agent relative,”
that is, dependent on the role of the decision maker rather than the outcome alone
(Chapter 16).
In sum, CV responses are affected by several factors that should not affect the
utility of the good being evaluated — cost and WTA versus WTP — and they are not
affected enough by factors that should affect the utility of the good, particularly its
quantity.
Disagreement among measures
Methods of utility measurement disagree with each other. In health judgments, for
example, the standard-gamble and time-tradeoff methods tend to yield higher utilities
than other methods (closer to normal, farther from death) for intermediate health
states (see Baron, 1997a). The standard gamble is usually highest of all. When asked
how much risk of death they will take for the sake of avoiding various conditions,
people tend to give small probabilities, which imply high utilities for the conditions.
What should we conclude from these disagreements? Scholars have proposed
many answers to this question. One general answer seems initially promising but
runs into problems when we examine it. This is the idea that different methods
measure different kinds of utility. Scholars often say that standard gambles (SGs)
measure “von Neuman-Morgenstern utility,” which differs from utility measured in
other ways. This provides a simple explanation of the fact that utilities measured by
SGs differ from those measured in others. (They are higher for good outcomes that
occur with probability 1, relative to uncertain outcomes, for example.)
Similarly, we might imagine PTO utilities that differ from utilities estimated in
other ways. In all these cases, the idea is to use different utilities depending on
the kind of decision at issue. If the decision involved risk, we use utilities elicited