Valuing Public Goods Using Happiness Data: The Case of Air Quality

This paper describes and implements a method for estimating the average marginal value of a time-varying local public good: air quality. It uses the General Social Survey (GSS), which asks thousands of people in various U.S. locations how happy they are, along with other demographic and attitude questions. These data are matched with the Environmental Protection Agency's Air Quality System (AQS) to find the level of pollution in those locations on the dates the survey questions were asked. People with higher incomes in any given year and location report higher levels of happiness, and people interviewed on days when air pollution was worse than the local seasonal average report lower levels of happiness. Combining these two concepts, I derive the average marginal rate of substitution between income and air quality - a compensating variation for air pollution.