Socioeconomic impacts

Despite the intensifying risks from extreme weather, individuals typically exhibit low preference and willingness to pay for insurance products against extreme weather, due to behavioral complexity, cognitive biases and policy and regulatory barriers. This project proposes the use of survey data collection to (1) Identify factors influencing public demand for extreme weather insurance, (2) Evaluate willing to pay for different insurance coverage products, (3) Examine demographic, geographic, and experiential differences in willingness to pay, and (4) Provide actionable insights for insurance providers and policymakers.

Team: Zhang (GMU), Solecki (CUNY), Morris (MIT), Peng (CUNY)

Insurance regulation is complicated and too often encourages homeowners to take risks. Little is known about public understanding of home insurance markets and how they could be restructured to maximize private coverage and minimize moral hazard and public expense. Here we will conduct strategic communication research that can guide efforts to increase public and political will for insurance market regulations that maximize private coverage and minimize moral hazards. We will do this through (1)a nationally-representative survey conducted online (N=6,000 to 8,000), (2) use of MRP to downscale and map the data, and (3) multivariate analysis to identify predictors of support for climate-smart insurance market regulation. 

Team: Center for Climate Change Communication (GMU) and Yale Program on Climate Change Communication (Yale)

The changing landscape of weather-related risk is straining the ability of finance and insurance sectors to adequately assess risk and its impacts on real estate. Moreover, there remain many uncertainties on the impact of adaptive actions and investments on risk at the parcel level. In this project, we aim to develop AI-powered, parcel level flood risk data incorporating infrastructure and building adaptation. We will further enhance this data with a financial framework for resilience assessment that dynamically accounts for system behavioral responses.

Team: Zheng (MIT) and Fan (MIT)

The research project will quantify how environmental factors and adaptive measures affect national economic growth. We will implement an enhanced economic-biophysical modeling framework to quantify the impacts of climate and environmental change as well as adaptive responses on economic growth at national and sectoral levels under a wide range of scenarios. We can make use of case studies to establish growth constraints in the climate-environmental-economic space. We can standardize the process to enable quick application of framework to any country of interest.

Team: Morris (MIT) and Schlosser (MIT)