Self-Managed Energy Assistance

Our proposed intervention is an alternative way to deliver LIHEAP benefits that gives recipients control over when and how their benefits are applied. The intervention will be implemented through an energy savings account that enables recipient-controlled benefit allocation.

Via the energy savings account, treatment group participants are able to: (1) view their full LIHEAP benefit allocation and their savings account portal, (2) choose how much benefit to apply to each utility bill throughout the year.

2026-10-01

2027-08-15

Primary outcomes include utility disconnection rates, energy spending trade-offs, on-time bill payment rates, total energy consumption, total arrearages (accumulated utility debt).

Disconnection rates will be measured as any service interruption for non-payment during the study period. Energy-related spending tradeoffs will be measured as a household reducing or forgoing other necessities to pay an energy bill. On-time payment rates will be calculated as the proportion of monthly bills paid by or before the due date. Arrearages represent the cumulative unpaid balance on utility accounts at study end.

Secondary outcomes include self-reported financial stress related to energy bills, bill management, ability to maintain comfortable in-home temperatures, understanding of energy usage and costs, sense of control over energy decisions, and household thermal health indicators.

Financial stress will be measured using validated insecurity surveys, including questions about worry over paying bills, difficulty affording energy costs, and trade-offs between energy and other necessities.

Comfortable temperature maintenance is an ordinal indicator based on whether households report being able to keep their home at a comfortable temperature during the heating season without compromising health or safety.

We will conduct a RCT with 1,000 LIHEAP-eligible households in Illinois to evaluate whether a self-managed delivery model via an energy savings account improves energy security outcomes compared to traditional LIHEAP implementation. The treatment group will receive self-managed LIHEAP benefits via an energy savings account with control over allocation timing. The control group will receive traditional LIHEAP delivery (one-time direct payment to utility).

Not available

Recruitment of research participants will occur after utility customers apply for LIHEAP benefits and meet the study requirements, as determined via a study screening form. After meeting these requirements and providing written consent, participants will take a baseline survey. Following this, study participants are sorted into treatment and control groups based on stratified randomization. Participants that meet LIHEAP eligibility remain in the study and those who do not are excluded.

Households will be randomly assigned at the individual level using stratified randomization to ensure balance across key characteristics that may influence treatment effects: poverty level (by income levels), race/ethnicity, and age.

No

NA

1,000

We will employ a 1:1 allocation ratio with 500 households in the treatment and control groups.

We conducted power analysis for the two primary outcomes, with a significance level of 0.05 and power of 0.8. Using the J-PAL Power Calculator, we computed the Minimum Detectable Effect under different assumptions about sample size and attrition. In all cases we assume the proportion in treatment is 0.5. Primary Outcome 1: Household disconnected during heating season. We assume an outcome proportion of 0.1 based on the 2024 EIA Disconnections Report. With our target sample size and no attrition, we will be able to detect about a 5 percentage point difference in disconnections between the treatment and control groups. Under more conservative assumptions of a sample of 600 and 20% attrition, we will be able to detect about a 7 percentage point difference. Sample MDE Attrition (%) 1000 0.0532 0 1000 0.0561 10 1000 0.0595 20 800 0.0595 0 800 0.0627 10 800 0.0665 20 600 0.0687 0 600 0.0724 10 600 0.0778 20 Primary Outcome 2: Household energy spending tradeoffs during heating season. We assume an outcome proportion of 0.2 based on the 2024 EIA Residential Energy Consumption Survey. With our target sample size and no attrition, we will be able to detect a 7 percentage point difference in households trading off energy bills for other expenses between the treatment and control groups. Under more conservative assumptions of a sample of 600 and 20% attrition, we will be able to detect about a 10 percentage point difference. Sample MDE Attrition (%) 1000 0.0709 0 1000 0.07475 10 1000 0.0793 20 800 0.0793 0 800 0.0836 10 800 0.0886 20 600 0.0915 0 600 0.0965 10 600 0.1024 20

SMEA Pre-Analysis Plan Aug2026.pdf