Understanding Trade-Offs between Built and Natural Assets in Coastal Management Projects for Inland, Coastal Residents using Latent Class Modeling Techniques: An Application to the Connecticut Coastline
Date of Completion
Stephen Swallow, Charles Towe, Juliana Barrett
Field of Study
Agricultural and Resource Economics
Master of Science
Climate change threatens our established communities worldwide through consistently increased average surface temperatures, rising sea levels, and precipitation extremes, and Connecticut is no exception (U.S. Global Change Research Program 2017). As coastal communities in Connecticut increase their focus on mitigating the effects of climate change, they are not always able to incorporate town residents’ preferences and values into their planning; particularly those residents who may not receive a direct benefit from the plan of which they contribute tax dollars towards. Our study attempts to estimate these preferences and values by using a choice experiment survey distributed across the Connecticut coastline which compares various coastal management plans and their outcomes. We use the survey’s results to estimate how public support for a coastal management plan is affected by a plan’s impacts on natural and built assets, and by respondents’ geographic location along the Connecticut coastline. Additionally, we employ Latent Class Modeling which groups respondents by their underlying preferences in order to further evaluate how respondents’ unobservable characteristics affect their choice of a coastal management plan.
Dumaine, Julia, "Understanding Trade-Offs between Built and Natural Assets in Coastal Management Projects for Inland, Coastal Residents using Latent Class Modeling Techniques: An Application to the Connecticut Coastline" (2019). Master's Theses. 1346.
Professor Stephen Swallow