Working Papers
The U.S. National Park System receives 300 million visits each year, generating surplus for visitors and supporting parks and surrounding communities. I build a versatile model of demand for US national parks, using nationally representative telephone surveys, fifteen years of park-level visitor counts, and a statistical atlas describing park attributes. Using a novel estimation and calibration procedure, I control for substitution between parks while rigorously identifying marginal willingness to pay for environmental amenities. The model produces a park awesomeness index that controls for travel costs and consistently ranks iconic parks like Glacier, Rocky Mountain, and Yellowstone in the top-10. Observable park attributes explain 51% of variation in the index. Temperature drives visitation more than any other attribute, and anticipated temperatures influence visitation decisions more than four times as much as short-run deviations from average temperatures. This framework has broad applications to challenges facing the National Park System, including wildfire and crowd management strategies.
- Causal Inference, High-Frequency Data, and the Recreational Value of Water Quality (available upon request)
with Hyunjung Kim
Work in Progress
- Willingness to Pay to Avoid Crowding on Public Beaches
with Frank Lupi, Caroline Tompson, and Roger von Haefen
- Weather and College Student Achievement
with Raghav Rakesh
- Temporary Migration and the Climate Refugia of the United States
with John Reaves