By Daniel K. Benjamin
The Environmental Protection Agency has been regulating air pollution in the United States for more than thirty years. Thus far, we know remarkably little about what benefits we are getting for the $30-plus billion the nation spends each year on this endeavor. Recent research by Kenneth Chay and Michael Greenstone (2005) has made an important advance in accurately quantifying these benefits.
In their study of total suspended particulates (TSPs), the tiny particles emitted by sources such as internal combustion engines, Chay and Greenstone have found that reductions in air pollution are associated with clear increases in housing prices. Indeed, their estimates imply that during the 1970s alone, mandated reductions in TSPs led to a $45 billion rise in home prices in counties where pollution was reduced due to federal regulations.
Housing markets are an excellent place to study people’s willingness to pay for environmental amenities. A large body of economic evidence from real estate markets already indicates that people will pay more for homes that have identifiable attributes they want (such as larger lot size or additional bathrooms). In principle, if people value clean air for aesthetic or health reasons, they are likely to pay extra for homes in locales with cleaner air. We thus should be able to identify the value they place on this amenity by observing differences in house prices across areas with differing air quality. But this has proven difficult to do in practice, because of confounding factors that affect both air quality and house prices.
For example, if people move to southern California to take advantage of the mild climate or the excellent surfing, air pollution will rise, but so too will house prices. Thus, even if people dislike dirty air, we may observe people paying more for houses where the air is dirtier.
The great advance made by Chay and Greenstone is that they focus on the very uneven application of the Clean Air Act Amendments of 1970.1 Under this legislation, if pollution concentrations in a county exceed the federally determined ceiling, then the Environmental Protection Agency (EPA) designates the county as “nonattainment.” Polluters in nonattainment counties face more stringent pollution regulations than do those in attainment counties.
During the 1970s this differential regulatory treatment of counties under the Clean Air Act forced down TSP levels in nonattainment counties relative to attainment counties, and did so independently of other potentially relevant factors. Moreover, because the regulations impinged very unevenly across the nation, TSP concentrations also changed unevenly across the nation. These features of the Clean Air Act provide Chay and Greenstone with something very much like a controlled experiment; hence their ability to isolate the effects of TSPs on housing prices.
The authors find that, even after controlling for other factors likely to affect housing prices, such as income, population, and taxes, TSP concentrations have effects on housing prices that are both statistically and economically important. The authors estimate that the roughly 10 percent cut in TSPs brought about by the Clean Air Act in nonattainment counties raised house prices in those counties by about 3 percent. This translates into roughly $45 billion worth of benefits to the people in those locales.
This rise in housing values is modest, to be sure. Moreover, the authors make no attempt in this study to assess the possible costs of the Clean Air Act. Hence, we do not know whether these air quality improvements have been worth the cost. Nevertheless, this paper joins the authors’ prior research (reported in my March 2004 column) as the first convincing assessment of the magnitude of the potential benefits from cleaner air.
Chay and Greenstone also show that the value people place on air quality improvements is lower in counties where air quality is the worst. This result is consistent with a process in which people engage in “selfsorting”; i.e., they choose where they live based partly on environmental amenities, such as clean air. Thus, just as trout fishermen tend to congregate in western Montana, people who are better able to tolerate smog are more likely to live in Los Angeles.
Perhaps the most important feature of this study is its unequivocal demonstration that we can use markets to measure the value of environmental amenities. Many economists have doubted the ability of markets to perform this valuation. Until now this doubt has seemed reasonable, for previous research has had difficulty in establishing a clear link between improved environmental quality and credible measures of the resulting benefits. The present study makes it clear that past failures to establish such a link have been the result of failures on the part of economists, not failures on the part of markets. If the economists get the message and refocus their research efforts accordingly, this is a conclusion that surely bodes well for improved environmental policy in the future.
- These amendments are informally called the Clean Air Act of 1970 because they established the basic framework for federal regulation of air pollution.
Chay, Kenneth Y., and Michael Greenstone. 2005. Does Air Quality Matter? Evidence from the Housing Market. Journal of Political Economy 113(April): 376–424.