Hotelling Meets Wright: Spatial Sorting and Measurement Error in Recreation Demand Models

Jacob Bradt

Journal of the Association of Environmental and Resource Economists, 2025, vol. 12, issue 6, 1563 - 1600

Abstract: Conventional applications of recreation demand models likely suffer from two standard challenges with demand estimation, namely, omitted variables bias and measurement error. Idiosyncratic prices in the form of individual-level travel costs can exacerbate these two challenges: the potential for nonrandom selection into travel costs through residential sorting and the difficulty of observing individual-level travel costs both work to bias traditional model estimates. I demonstrate the magnitude of this potential bias in conventional estimates of recreation demand models. I provide a relatively simple instrumental variables approach to address these two empirical challenges that substantially outperforms traditional estimates in numerical simulations. Replicating English et al., I find that accounting for potential selection into travel costs and measurement error through the instrumental variables approach decreases estimates of the welfare costs of the 2010 Deepwater Horizon oil spill by 12%.

Date: 2025
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