Using Known Relationships Between Ordinary Goods and Environmental Goods

    In a sense, the preceding "sum-of-specific damages" approach could have been classified as going here--a damaged person visits the hospital (the ordinary good) when the pollution levels go up.  But, a rather different, more indirect, approach is envisioned under this category.  There are three primary sub-approaches to discuss:

Property-Value Differential Hedonic Valuations

    The notion underlying property-value studies is that the value of a home (sales price or rent) will be related to the traits that that home possesses.  Consider the typical real estate listing: it will contain information about the structural traits of the home (stone or wood, # baths, # bedrooms, age, type of heat, square footage, family room, garage, special features, etc.) and about the traits of the neighborhood in which the home is located (schools, quiet, access to the city, access to ocean or mountains, crime, etc.).  Those traits will, collectively, determine the value of the home--this is what people have in mind when they say "putting in another bathroom will pay for itself" (That is, the value of the home will rise by the cost of adding the bathroom).  But, one of the traits that people care about is environmental quality--a home in a polluted area will rent or sell for a smaller amount than will a home in a cleaner area.   If we can determine how much people are willing to pay for the same home in a clean location versus a dirty location, we will have a measure of exactly what we want, the marginal dollar willingness-to-pay for environmental quality, which can then be compared to the dollar marginal cost of environmental quality.  The process:
    1) Obtain as much information as possible about the determinants of the property value of each house in a sample (structural, neighborhood, and environmental quality) along with its property value--ideally an actual sales price.
    2) Statistically relate the property value (as the dependent variable) to its determinants (the independent variables already discussed).  Note that this examination involves many possible functional forms--non-linearities, synergisms, etc. may be important.  That there is little theoretical guidance on the functional form which presents problems and sometimes enables advocates to publish very different conclusions from identical data!
    3) The coefficients on the environmental quality variables depict how much impact a given change in EQ will have on property value.  That is, the trade-off between environmental quality and other goods can be directly measured.
    Problems: If some other amenities are correlated with the environmental measure--and omitted from the equation--the value of the environment is likely to be overstated.  For example, suppose that the more polluted parts of a city are also less desirable for several other reasons (more crime, worse schools, more graffiti, worse streets, poor lighting, fewer parks, etc.) and these other "bads" are not included in the equation.  By not including the other bads that are correlated with pollution, the impact of pollution will seem to be larger than it is, effectively attributing to pollution the effects of the other non-included variables.  [Technically, the bias on the pollution coefficient will be the coefficient on the omitted variable times the correlation of that variable with the included pollution variable].
    But, on the other hand, suppose that people don't fully perceive either the impact of pollution on their health and well-being or how the pollution levels vary across locations.  This is plausible--even the "experts" have widely varying opinions about the amount of damage stemming from pollution (see discussion of sum-of-specific damages).  And, since many pollutants are odorless, colorless, and tasteless in ambient concentrations commonly encountered, it might be difficult for the average person to even know whether a particular house is in a high-pollution or low-pollution location.  If  buyers don't properly perceive all of the damages from pollution or if they can't tell which locations are dirtier, the benefits estimated by this approach will be understated.
      What is the net effect?  Nobody knows with any certainty.  There are, however, many studies showing strong relationships between property values and pollution.  This approach is particularly useful for valuing spatially concentrated environmental damages--e.g. the impact of toxic waste dumps (Superfund sites) on surrounding land values.  As we shall see, however, the situation is quite a bit more complicated than it seems to this point.
 

Wage Differential Hedonic Valuation

    A quite similar technique goes about the hedonic valuation of environmental quality by looking at labor markets, rather than land markets.  The idea is that some labor market regions are more polluted than others, and that people will have to be compensated for the pollution they experience to be willing to work in dirtier cities.  That is, if City A (one of two otherwise identical cities) has higher pollution levels than City B, residents would move from A to B reducing the labor supply in A (raising wages) while increasing the labor supply in B (lowering wages).  The movements would continue to occur until the wage differential just compensated people for the higher pollution in City A.  Again, if this approach seems plausible, it has the desirable feature of getting exactly what we want, the marginal willingness-to-pay in dollar terms, which can then be compared to the marginal costs of policies yielding that amount of cleanness.  The process:
    1) Obtain as much data as possible on the determinants of wages for people at various locations (education, experience, age, occupation, etc.) and their wages along with measures of pollution levels in those locations.
    2) Statistically relate the wage (as the dependent variable) to its determinants (the independent variables already discussed).  As noted for property values, there is little guidance on functional form (linearity, interactions among variables, etc.), offering the possibility that advocates will distort the information by their choices.
    3) The coefficients on the environmental quality variable will indicate how much impact a given change in environmental quality will have on wages.  Again, the trade-off between environmental goods and other goods can be directly measured.
    As with property value studies, values generated in this way can either overstate (omitted other "bads" that are correlated with pollution) or understate (the pollution differences are not perceived or people don't know how pollution affects them) the true benefits of cleaning up.  As with property values, however, a large number of wage studies indicate that the environment does matter to people--they give up wages to live in cleaner locations.
 

Wage and Property Value Differentials Are Not Alternatives

    Until fairly recently, the preceding hedonic approaches to valuing environmental improvements were viewed as alternative approaches.  That is, one could find out what clean air was worth either by examining property value variation in land markets or by examining wage variation in labor markets...but not both.  It turns out that this is incorrect under plausible assumptions about peoples' behavior when evaluating locations.  Indeed, for this view to be valid, it must be the case that people follow a two-stage procedure in picking a location.  First, only look at wages (and average pollution levels), they decide among alternative labor markets; only then, having settled on a labor market, do they select a location based on housing price (and pollution) variation within that area.  Yet, clearly one would do much better in general to look at the combination of wages, rents, and amenities available prior to selecting their location.  Another way to think about this is that, between two otherwise identical locations, the one that is more polluted will be less attractive--so, people will move from the more-polluted to the less-polluted location until they are equally well off in both locations.  But, as they move into the less-polluted location they both increase the supply of labor (driving down wages) and increase the demand for land (driving up rents).  Hence, the "true" value of the less-polluted locations is the sum of what is being paid for reduced pollution in both markets!  Thus, the "Quality-of-Life" as ranked by publications such as Rand-McNally can be compared (unfavorably!) to the QofL as viewed by economists (willingness-to-pay for "niceness" in both land and labor markets).  We will develop these arguments more carefully in class with a series of progressively more complicated models.  The process:
    1) Start with "flat, featureless plain," where all locations are literally identical (initial situation--like S&D--GRAPH)
    2) Introduce a nicer location and consider the new equilibrium (wages lower and rents higher as people move in).
    3) Introduce variations in desirability from firm perspective (nicer locations will have higher wages and rents).
    4) Discuss various combinations of consumer and firm amenities, graphing the permutations (many GRAPHS).
    5) Introduce people and firm differences, noting what difference heterogeneity makes.
    NOTE: The implication is that efforts to value environmental (and other) amenities in land markets or labor markets separately  are flawed and lead, generally, to understatement of the values we place on environmental goods (and other amenities that we consume).

Travel Cost Methods

    Travel cost methods of valuing environmental goods depend on the following presumption: the value of the things we visit must be at least as great as the full cost of getting there.  Imagine, for example, a world comprised of zones around some natural wonder (e.g. the Grand Canyon).  Those nearer would be expected to have higher visitation rates than those farther away, since they have lower costs of visiting the site.  One can calculate the cost of visiting the site for people in any zone, using explicit out-of-pocket costs, implicit time costs (big--Discuss how determined), any entrance fees, etc. and relate that to visitation rates--lower rates will be observed and, in this way, a demand curve can be generated.  The "value" of the natural, then, is the area under the demand curve.  Problems: multiple visit trips, lower-bound nature of numbers--benefits must be "at least" that amount, but might be substantially higher.