Measuring the Welfare Effects of Residential Energy Efficiency Programs

Last registered on August 23, 2017
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Pre-Trial

Trial Information

General Information

Title
Measuring the Welfare Effects of Residential Energy Efficiency Programs
RCT ID
AEARCTR-0002176
Initial registration date
August 22, 2017

Initial registration date is when the trial was registered.

It corresponds to when the registration was submitted to the Registry to be reviewed for publication.

First published
August 23, 2017, 2:25 PM EDT

First published corresponds to when the trial was first made public on the Registry after being reviewed.

Locations

Country
United States of America
Region
North America

Primary Investigator

Name
Michael Greenstone
Affiliation
University of Chicago
Contact Primary Investigator

Other Primary Investigator(s)

PI Name
Hunt Allcott
PI Affiliation
New York University
Contact Investigator

Additional Trial Information

Status
Completed
Start date
2012-06-01
End date
2013-09-30
Keywords
Environment & Energy
Additional Keywords
energy efficiency, program evaluation, randomized control trials, welfare analysis
JEL code(s)
D12, L94, Q41, Q48
Secondary IDs
Abstract
This paper sets out a framework to evaluate the welfare impacts of residential energy efficiency programs in the presence of imperfect information, behavioral biases, and externalities, then estimates key parameters using a 100,000-household field experiment. Several results run counter to conventional wisdom: we find no evidence of informational or behavioral failures thought to reduce program participation, there are large unobserved benefits and costs that traditional evaluations miss, and realized energy savings are only 58 percent of predictions. In the context of the model, the two programs we study reduce social welfare by $0.18 per subsidy dollar spent, both because subsidies are not well-calibrated to currently-estimated externality damages and because of self-selection induced by subsidies that attract households whose participation generates low social value. However, the model predicts that perfectly-calibrated subsidies would increase welfare by $2.53 per subsidy dollar, revealing the potential of energy efficiency programs.
External Link(s)
J-PAL Evaluation Summary

Registration Citation

Citation
Allcott, Hunt and Michael Greenstone. 2017. "Measuring the Welfare Effects of Residential Energy Efficiency Programs." AEA RCT Registry. August 23. https://doi.org/10.1257/rct.2176-1.0
Former Citation
Allcott, Hunt and Michael Greenstone. 2017. "Measuring the Welfare Effects of Residential Energy Efficiency Programs." AEA RCT Registry. August 23. https://www.socialscienceregistry.org/trials/2176/history/20755
Sponsors & Partners
Experimental Details

Interventions

Intervention(s)
Intervention Start Date
2012-06-01
Intervention End Date
2013-02-28

Primary Outcomes

Primary Outcomes (end points)
audit take-up, investment take-up, welfare impacts
Primary Outcomes (explanation)
welfare impacts are defined by energy savings and externality reductions

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
We sent informational letters by direct mail to the randomly assigned treatment group, part of a subset of households eligible for the Green Madison and Me2 programs. The experimental population included all owner-occupied single-family homes in Madison and Milwaukee that were built in 1990 or before had no lien on the property, and had not scheduled an audit prior to May 2012. When opened, the top half was a picture with a short headline. The bottom half includes simple text that describes the program, lays out next steps, and gives a phone number to call to schedule the home energy audit. We varied the letters along seven dimensions, including audit subsidies and six non-price treatments that were designed to address key market failures thought to reduce take-up of home energy audits. These can be roughly categorized into three "informational" market failures and three "behavioral" failures.
Experimental Design Details
Randomization Method
By computer in Stata
Randomization Unit
Households
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
N/A
Sample size: planned number of observations
101,881 households
Sample size (or number of clusters) by treatment arms
79,994 households in the treatment group
21,887 households in the control group
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Supporting Documents and Materials
IRB

Institutional Review Boards (IRBs)

IRB Name
University of Chicago
IRB Approval Date
2015-05-19
IRB Approval Number
14-0491
IRB Name
Massachusetts Institute of Technology
IRB Approval Date
2011-06-02
IRB Approval Number
1105004499
Analysis Plan

Post-Trial

Post Trial Information

Study Withdrawal

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Intervention

Is the intervention completed?
Yes
Intervention Completion Date
February 28, 2013, 12:00 +00:00
Data Collection Complete
Yes
Data Collection Completion Date
September 30, 2013, 12:00 +00:00
Final Sample Size: Number of Clusters (Unit of Randomization)
Was attrition correlated with treatment status?
No
Final Sample Size: Total Number of Observations
101,881 households
Final Sample Size (or Number of Clusters) by Treatment Arms
79,994 households in the treatment group 21,887 households in the control group
Data Publication

Data Publication

Is public data available?
No

Program Files

Program Files
Reports, Papers & Other Materials

Relevant Paper(s)

Abstract
Citation
Hunt, Allcott, and Michael Greenstone. "Measuring the Welfare Effects of Residential Energy Efficiency Programs." Working Paper, April 2017.
URL
https://www.povertyactionlab.org/sites/default/files/publications/902_Measuring-welfare-effects-of-residential-energy-efficcient-programs_Greenstone_April2017.pdf

Reports & Other Materials