Reducing Decision Cost of Taking Up an Energy Retrofitting Program in the Northeast

• In Event: How Policy Design and Social Context Shape Energy Behavior and Outcomes

Abstract

Consumers commonly underinvest in energy-efficiency measures as if they valued future energy savings at a heavily discounted rate today (Allcott & Greenstone, 2012). Such underinvestment is particularly salient among low- and moderate-income (LMI) households, who have little disposable income to spare on energy-efficiency upgrades while experiencing a heavy energy burden (Lewis et al., 2020). LMI households’ underinvestment in energy efficiency measures is a missed opportunity for cost savings and carbon emission reductions.  

In this research, we answer four research questions: 1) Does providing customized cost-savings information increase energy retrofitting program application and completion rates? 2) Does additionally explaining the principle of cost–benefit analysis further increase take-up? 3) Is there evidence of spillover or word-of-mouth effects at the county level beyond direct survey participants? And 4) does the effect of the information treatment differ between low-income and moderate-income participants? We answer our research questions by using a simple decision tool based on National Renewable Energy Lab (NREL) estimations to help LMI homeowners in a northeastern state understand the cost-savings implications of improve the energy efficiency of their homes through a state-level energy retrofitting program. Administered by the state’s energy authority, the state-level energy retrofitting program helps income-eligible residents implement core energy efficiency improvements such as air sealing and insulation.  

We will use a two-wave (April and August 2026) survey experiment to test the effect of this decision tool, specifically, whether decision-cost reduction increases LMI homeowners' willingness to sign up for the program in the first wave, and self-reported application for the program and completion of home enclosure in the second wave. Our initial sample is 1,000 low-income and 1,000 moderate-income homeowners drawn from half of the northeastern state’s counties, recruited by Qualtrics. Additionally, the research team has requested anonymized, administrative information from the state’s energy authority for the purpose of determining whether a survey respondent submitted an application to the energy-retrofitting program and whether the applicant completed the program. To assess potential spillover effects, the study will compare counties in which the survey was conducted with counties in which no survey was conducted, including monthly counts of energy-retrofitting program applications submitted and monthly counts of program completions from January 2025 through December 2026. 

We will use OLS regression to examine the main effects of decision-cost reduction. We expect that reducing cognitive decision costs at the onset of home energy-efficiency upgrade decisions would increase homeowners' applications for and completion of energy-efficiency upgrade programs among LMI homeowners. We also expect that additionally explaining the principle of cost–benefit analysis will increase take-up compared to simply providing customized cost-saving information. We implement a differences-in-difference design to examine the size of the spillover effect in counties where we conduct the survey vs where we do not. We also investigate the heterogeneous effect of decision cost reduction across low- and moderate-income groups. This research contributes to the theoretical understanding of LMI households’ energy efficiency investment decisions, and critically inform future communication efforts of energy agencies and non-profits administering similar programs.

Author

• Catherine Chen, Hamilton College
  Presenting Author