Happiness is in the air! Levinson uses happiness surveys to put a dollar value on air quality.
The U.S. Environmental Protection Agency (EPA) was responsible for 32 of the 105 major rules issued by U.S. federal agencies in 2010. How do economists put a dollar value on the environmental benefits of such rules? This is one of the greatest challenges facing environmental economics, and a new paper by GCER Faculty Fellow Arik Levinson proposes and tests a new approach.
There are three existing and often-used methods of valuing the environment. The first is the “travel cost” approach which originated in a letter by famed economist Harold Hotelling. Hotelling wrote to the National Park Service in 1947, suggesting that the Park Service examine how much people spend traveling to unpolluted recreational sites. A second method, the hedonic regression approach, regresses housing prices on neighborhood characteristics including air quality. Finally, the contingent valuation approach directly asks people their willingness to pay for environmental improvements.
In recent work, Levinson proposes and estimates an alternative based on “happiness” surveys. The fundamental idea combines data from two sources. The General Social Survey asks respondents how happy they are, on a three-point scale, along with their incomes and other demographic information. And the EPA collects daily air pollution data from thousands of monitors all over the U.S. Combining these two sources, it is possible to estimate respondents’ happiness as a function of their incomes and the air quality in the place and on the day they were asked the happiness question.
The approach is summarized in two equations. The first is a regression equation with each individual’s response to the happiness survey as the left hand side variable. On the right hand side are the individual’s income and demographic data and the local air quality conditions. From this equation, Levinson derives a second equation that describes the individual’s marginal willingness to trade income for pollution reduction. From this second equation, Levinson estimates how much more income people would have to earn in order to feel at least as happy as they would with an improvement in air quality.
Levinson applies this approach to airborne particulates smaller than 10 microns (PM10), a common measure of air pollution. He finds that, on average, people appear to be willing to forgo about $40 of annual income for a one-standard-deviation reduction in particulate pollution for one day. How large is this change? A one-standard-deviation change represents a 50 percent increase (or decrease) in pollution! This corresponds to a move by an individual from an average county in the United States to one of the most polluted counties, for instance to Riverside or San Bernardino, CA. It also corresponds approximately to the improvement in air quality attributed to the 1970 and 1977 Clean Air Acts.