Fiona Burlig

In the United States, consumers invest billions of dollars annually in energy efficiency, often on the assumption that these investments will pay for themselves via future energy cost reductions. We study energy efficiency upgrades in K-12 schools in California. We develop and implement a novel machine learning approach for estimating treatment effects using high-frequency panel data, and demonstrate that this method outperforms standard panel fi xed effects approaches. We and that energy efficiency upgrades reduce electricity consumption by 3 percent, but that these reductions total only 24 percent of ex ante expected savings. HVAC and lighting upgrades perform better, but still deliver less than half of what was expected. Finally, beyond location, school characteristics that are readily available to policymakers do not appear to predict realization rates across schools, suggesting that improving realization rates via targeting may prove challenging.

Areas of Focus: Energy Markets
Definition
Energy Markets
Well-functioning markets are essential for providing access to reliable, affordable energy. EPIC research is uncovering the policies, prices and information needed to help energy markets work efficiently.
Energy Efficiency
Definition
Energy Efficiency
Improving energy efficiency is lauded as a promising way reduce emissions and lower energy costs. Yet, a robust body of research demonstrates that not all efficiency investments deliver. EPIC faculty...