the immediate region, it was clear that respondents were valuing broader commodities such as
health effects of air quality degradation.
In the first case, it is possible that a survey instrument could be designed which would
allow a high enough “ceiling” to stabilize the BID coefficient. In the latter two cases, the model
is not the problem; in fact, there is no “problem.” Most respondents (80 percent) are simply not
willing to part with a good which they “own”, visibility/air quality. This position can be justified
on theoretical grounds. The fact that the size of BID does influence WTP estimates is not at all
contradictory in this case. Since property rights have been reassigned in the WTP scenario,
respondents are left with no choice but to buy back the good. This also may partly explain that
while bid offers were comparable across the two groups, the percentage of yes respondents in
the WTP survey was substantially higher than that in the WTA survey (33 vs. 20 percent). It is
entirely possible that the difference between WTA and WTP, rather than being an anomaly or an
artifact of hypothetical bias, is consistent with theoretical models of consumer behavior, and
certainly merits further examination. In the final analysis, trying to “deflate” WTA estimates to
make them more “reasonable” may actually turn out to be data manipulation which contradicts
theoretical expectations!
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