This thesis estimates welfare impacts of two types of water quality warnings using a combined revealed-stated preference approach. The data was collected in a survey that randomly sampled visitors to 28 public beaches in Michigan and Ohio. The first essay uses a discrete choice experiment to measure preferences for common beach attributes including the presence of active or recent warnings for harmful algal blooms (HAB) or bacterial contamination. We find respondents are willing to drive over 200 miles to avoid a site with either of these warnings, with a negative lag effect for both hazards that remains at least 6 days after warnings are lifted. The second essay builds on this understanding of beachgoers’ preferences for attributes of beaches, by modeling site substitution behavior when beachgoers face warnings. We use a multi-site demand model that explicitly accounts for site substitution to estimate welfare impacts of site closures and HAB and bacterial warnings. A contraction map identifies the disutility of warnings by calibrating changes in site demands to match contingent behavior questions. The findings show that, at the average beach, season-long bacterial or HAB warnings cause losses of about 1.4 million dollars per year for either hazard. For 2019, the observed HAB and bacterial warnings caused about $5.8 million in welfare losses. This estimate accounts for beachgoers’ lagged aversion to recently lifted warnings; omitting lagged effects would understate welfare losses by 34 percent. Together, the essays show that cost-benefit analyses that fail to account for the dynamic disamenity effects of HAB and bacterial warnings will likely understate the costs of these events, which are projected to increase in frequency and intensity under climate change.
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