University of California, Berkeley

To collect and analyze experimental data for powerful statistical tests of how weatherization affects household energy efficiency

  • Amount $270,250
  • City Berkeley, CA
  • Investigator Catherine Wolfram
  • Year 2011
  • Program Research
  • Sub-program Economic Institutions, Behavior, & Performance

In the United States, buildings account for about 39% of all energy use, 68% of all electricity consumption, and 38% of all carbon dioxide emissions. Engineers estimate that retrofits for weatherizing built environments can substantially reduce waste enough to quickly pay for themselves, while also helping to decrease energy consumption and curb carbon emissions. But given the chance to save money and energy this way, the conventional wisdom is that many individuals and businesses do not take full advantage of energy efficiency investments that can save them money in the long run. The Sloan Foundation has begun funding work on this important issue by different kinds of researchers, ranging from behavioral economists to environmental engineers. Sloan funds have also helped launch the first large-scale randomized experiment to study weatherization programs. Based at the University of California, Berkeley, this pilot project has already discovered unexpected evidence that low-income homeowners are even less willing to take advantage of weatherization programs than previously thought. Moreover, such reluctance remains strong even among homeowners randomly chosen to receive encouragement and help with the process of weatherization. One implication of this finding is that the pilot study as originally planned will not have enough "statistical power" to justify robust policy conclusions. In order to refine the statistical validity of the findings, a larger sample of households is needed. Funds from this grant will support efforts by the University of California, Berkeley team to strengthen their experimental design and expand the number of households surveyed, allowing for more robust statistical conclusions that have the potential to appropriately shape policy discussions about energy utilization.

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