In Chapter 14 we presented a general model of consumer preferences in the presence of a quasi-fixed good. We saw that it is relatively straightforward to define welfare measures for changes in exogenous variables faced by consumers – be they price or quasi-fixed good changes. We also saw how observation of behavior in private good markets reveals sufficient information on preferences to construct exact (compensating and equivalent variation) or approximate (consumer surplus) welfare measures for private good price changes. Welfare measurement for changes in exogenously given quantities, however, turned out to be considerably more complicated. The fundamental challenge of welfare measurement for changes in quasi-fixed quantities is based on the fact that, by definition, no markets exist for quasi-fixed goods such as environmental quality. Thus there is no observable behavior from which to construct a demand curve, and hence no direct window through which preferences can be observed. We concluded from this that extra-market information is needed to estimate the welfare effects of changes in quasi-fixed goods. In this chapter we focus on one potential source of extra information: assumptions on how the demand for a private good interacts with the quasi-fixed good. These assumptions give rise to the so-called revealed preference models for non-market valuation.

Revealed preference methods are based on the premise that, though there are no direct markets for environmental goods, people interact with the environment in a variety of observable ways. For example, there is no market that determines the population of orcas in Washington's Puget Sound, but visitors to the area purchase whale-watching tours to see them. If there are fewer animals available we are likely to observe fewer people booking tours. Air quality in many urban areas is highly variable due to geography and wind patterns. Though there is no market for air quality, people are often observed choosing their place of residence based in part on where air quality is higher. Likewise, people who are sensitive to episodic changes in ground-level ozone may alter their schedules so as to spend less time outdoors during pollution spikes. Other examples abound: fishermen go where the fish are, beach visitors favor areas with clean water, homebuyers like to locate near protected open space, and pregnant women avoid eating fish with mercury contaminants.