Mortality Cause by Tropical Cyclones in the United States
Young, R., Hsiang, S. Nature (2024).
Selected coverage: AP, NYTimes, Wall Street Journal, Washington Post, CNN, The Guardian, NPR, Scientific American, USA Today, The Verge, National Geographic, CBS News, Axios
Why Is Electricity Use No Longer Growing?
Nadel, S., Young, R.M. Issue. Public Utilities Fortnightly (2014).
Estimating Tropical Cyclone Vulnerability: A Review of Different Open-Source Approaches.
Wilson, K.M., Baldwin, J.W., Young, R.M. In: Collins, J.M., Done, J.M. (eds) Hurricane Risk in a Changing Climate. Hurricane Risk, vol 2. Springer, Cham. (2022).
Inferring Fine-Grained Migration Patterns Across the United States.
Agostini, G., Young, R., Fitzpatrick, M., Garg, N., & Pierson, E. (2025). https://migrate.tech.cornell.edu/.
Abstract: Fine-grained migration data illuminate important demographic, environmental, and health phenomena. However, migration datasets within the United States remain lacking: publicly available census data are neither spatially nor temporally granular, and proprietary data have higher resolution but demographic and other biases. To address these limitations, we develop a scalable iterative-proportional-fitting based method which reconciles high-resolution but biased proprietary data with low-resolution but more reliable Census data. We apply this method to produce MIGRATE, a dataset of annual migration matrices from 2010 - 2019 which captures flows between 47.4 billion pairs of Census Block Groups — about four thousand times more granular than publicly available data. These estimates are highly correlated with external ground-truth datasets, and improve accuracy and reduce bias relative to raw proprietary data. We publicly release MIGRATE estimates and provide a case study illustrating how they reveal granular patterns of migration in response to California wildfires.
Young, R.M. (in prep). Draft presented at APPAM Fall 2022 Conference. Washington D.C., Camp Resource XXX Confererence 2024. Asheville NC, and Stanford University 2024 Preparing for a Changing Climate Conference. Stanford, CA.
Abstract: With climate change increasing the likelihood of future extreme weather events, the federal government is looking to expand programs designed to help people permanently move out of harm’s way. Despite growing interest, there is limited causal evidence on the long-term effectiveness of these programs for both participating households and taxpayers. This study evaluates the Federal Emergency Management Agency (FEMA) property acquisition programs, commonly referred to as "buyouts." Using administrative and commercial datasets, I track residential locations for 15,000 individuals before and after they participated in a federal buyout between 2000 and 2017. I find that 50% of participants move within 10 kilometers (6 miles) of their buyout homes. Participants are 12.6 percentage points less likely to reside in a high flood-risk area (100-year flood zone) post-buyout (p<0.001) relative to a comparable control group. Participants are 7 percentage points more likely to move to wealthier census tracts, yet show no significant long-term gains in financial well-being, as measured by credit scores or available credit. Moreover, program benefits—such as reduced credit card debt, lower flood risk, and relocation to higher-income neighborhoods—are more substantial for individuals originally residing in higher-income, predominantly white census tracts. Finally, I demonstrate that the costs of buyouts are comparable to those of traditional disaster relief, indicating that the program is cost-neutral from a taxpayer perspective. However, enhanced administration and compliance could increase its overall effectiveness and public value.
Limited Migration from Tropical Cyclones in the United States.
Young, R.M., Kolodner, K.L., & Oppenheimer, M. (in prep). Presented at 2023 Managed Retreat Conference, Habitability and Mobility in an Era of Climate Change, Columbia University, New York, New York.
Abstract: Extreme weather events have significant long-term impacts on economic productivity and human health. Migration from high-risk areas may help protect individuals, reduce future harm, and serve as a form of adaptation and self-insurance. However, existing studies on climate, weather, and migration disagree on the extent and drivers of hazard-induced migration. U.S. internal migration research has primarily focused on a few catastrophic events, such as Hurricanes Maria and Katrina, and is constrained by limitations in available data. For instance, publicly available U.S. migration data is aggregated at the county level, and household-level damage assessments are scarce. This study addresses these gaps by analyzing migration responses across three spatial and temporal scales using multiple datasets. First, we examine migration from tropical cyclones at the county level, using publicly available county-to-county migration data from the Internal Revenue Service (IRS) and parametrically reconstructed wind speed data. At the county level, migration is difficult to detect on average. Second, we leverage a private consumer reference database comprising 260 million U.S. adult addresses (1990–2020) combined with high-resolution wind speed estimates. This analysis reveals minimal relocation from high-risk areas, except after extremely destructive storms in the top 99th percentile of wind incidence. Finally, employing machine learning and aerial imagery, we estimate building-level damage from two hurricanes and observe low permanent migration rates even among households experiencing severe destruction. Overall, these findings challenge the assumption that populations naturally relocate from disaster-prone areas, highlighting the need for nuanced policy approaches to support affected communities.
Impact of Hurricanes on U.S. Department of Housing and Urban Development Assisted Households
Young, R.M., Din A. 2024. Accepted for presentation at APPAM Fall 2024 Conference. (in prep).
Abstract: Evidence continues to mount of the unequal effects of climate change and climate-driven natural hazards across different racial and income groups. The U.S. Department of Housing and Urban Development (HUD) provides rental assistance for 4.6 million low-income households across the US. HUD program participants are poorer and, therefore, vulnerable to damage from natural disasters. However, little is known about the impact of disasters on HUD programs and their program participants. There is some evidence that HUD assistance participation is negatively impacted by natural disasters and that households subsidized by federal renter assistance are potentially more vulnerable to disasters that non-subsidized housing, but the research is limited. This project fills the current knowledge gap by uncovering: 1) the impact of natural disasters on entries and exits from HUD assistance; and 2) the change in neighborhood quality, including future hazard risk, for HUD assisted individuals that are impacted by Hurricane Harvey. We combine rich set of administrative data for all HUD households that participate in Public Housing or the Housing Choice Voucher (HCV) programs in Harvey impacted areas the time of the hurricane with a consumer reference database of household’s addresses over time and property-level damage ratings generated through aerial imagery and machine learning predicted. Using a propensity score matching procedure we estimate the causal effect of the hurricane on HUD participants on their likelihood of participating in HUD rental assistance programs, changes in neighborhood natural hazard risk, and neighborhood poverty. We also estimate the differential effects by property damage-level for each household. Individuals in homes destroyed by Hurricane Harvey are forced to relocate at higher rates than their counterparts in low damage properties, making them more vulnerable to losing their HUD assistance vouchers. Findings from this paper have important implications for HUD program priorities and for government assistance in the aftermath of major natural disasters.
Young, Rachel, Chetana Kallakuri, Sarah Hayes. 2015. 2015 International Scorecard Self-Scoring Tool. Washington D.C.: American Council for an Energy-Efficient Economy.
Young, Rachel and Sara Hayes. 2015. The State and Utility Pollution Reduction (SUPR) Calculator. Research Report E1501. Washington D.C.: American Council for an Energy-Efficient Economy.
Young, Rachel, Sara Hayes, Meegan Kelly, Shruti Vaidyanathan, Sameer Kwatra, Rachel Cluett, and Garrett Herndon. 2014. 2014 International Energy Efficiency Scorecard. Research Report E1402. Washington D.C.: American Council for an Energy-Efficient Economy.
Young, Rachel, Sara Hayes, Steven Nadel, Garrett Herndon, and Jim Barrett. 2013. Economic Impacts of the Energy Efficiency Provisions in the Energy Savings & Industrial Competitiveness Act of 2013 and Select Amendments. White Paper. Washington D.C.: American Council for and Energy-Efficient Economy.
Young, Rachel and Eric Mackres. 2013. Tackling the Nexus: Exemplary Programs that Save Both Energy and Water. Research Report E131. Washington D.C.: American Council for an Energy-Efficient Economy.
Young, Rachel, R. Neal Elliott, Martin Kushler. 2012. Saving Money and Reducing Risk: How Energy Efficiency Enhances the Benefits of the Natural Gas Boom. White Paper. Washington D.C.: American Council for and Energy-Efficient Economy.
Hayes, S. and Young, R.M. 2012. Reducing the Cost of Environmental Regulations: Energy Efficiency as an Air Quality Compliance Mechanism. Volume XXIV Issue 4. The Georgetown International Environmental Law Review. Washington D.C.: Georgetown University.