Applications of big data on residential properties to provide decision-support for decarbonization policies

Sep 27, 2021, 12:15 pm1:15 pm
virtual via zoom
  • Center for Policy Research on Energy and the Environment
  • High Meadows Environmental Institute
Open to the public, RSVP required.
Event Description

Yueming (Lucy) Qiu is an Associate Professor in the School of Public Policy at University of Maryland College Park. Her research group focuses on using big data with quasi-experimental and experimental methods to answer empirical questions related to the interactions among consumer behaviours, energy technologies, and incentives. Her research projects have been funded by the National Science Foundation, the Sloan Foundation, Department of Defence, and Water Research Foundation. Dr. Qiu received her Ph.D. from Stanford University and B.S. from Tsinghua University. She has published in scientific journals including Journal of Environmental Economics and Management, Nature Energy, Nature Sustainability, and Nature Communications.

This talk discusses three studies that apply big data on residential properties to provide decision-support for decarbonization policies. The data include residential property attributes and values in the United States that cover more than 150 million homes in 51 states. First, we use such data to assess the effectiveness of decarbonization policies that provide rebates and low-interest loans to incentivize consumers to adopt heat pumps. Heat pumps offer an energy-efficient way to electrify space heating and thus provides a pathway to achieving cost-effective deep decarbonization of the economy. Second, we estimate a positive house price premium associated with air source heat pump installations across 23 states in the United States, which provides important messages for potential government informational programs to incentive the adoption. Lastly, we estimate the impact of local natural gas (methane) leakages on housing prices. Methane is an important greenhouse gas. Our results provide the estimates of willingness-to-pay for repairing gas leakages, which is important for policymakers to evaluate any repair programs.