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.

Work in Progress

with Hyunjung Kim

with Frank Lupi, Caroline Thompson, and Roger von Haefen

with Raghav Rakesh