Motivating and supporting load shedding.

Last registered on April 26, 2024
View Trial History

Pre-Trial

Trial Information

General Information

Title
Motivating and supporting load shedding.
RCT ID
AEARCTR-0013422
Initial registration date
April 20, 2024

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
April 26, 2024, 11:41 AM EDT

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

Locations

Country
France
Region

Primary Investigator

Name
sylvain chassang
Affiliation
Princeton University
Contact Primary Investigator

Other Primary Investigator(s)

PI Name
Isabelle Vautier
PI Affiliation
EDF
PI Name
Claire Del Gatto
PI Affiliation
EDF
PI Name
Maxime Lepetit
PI Affiliation
EDF

Additional Trial Information

Status
On going
Start date
2023-01-01
End date
2024-05-31
Keywords
Behavior, Environment & Energy
Additional Keywords
Load shedding, demand for electricity, nudges, incentives, habit formation
JEL code(s)
Secondary IDs
Prior work
This trial is based on or builds upon one or more prior RCTs.
Abstract
This study run by Electricité de France on a sample of its clients evaluates the impact of several measures on load shedding, i.e. voluntary reduction in demand for electricity, designed to reduce load at peak times, and if possible shift it to non-peak time periods.

The study's outcomes of interest include:
- demand reduction at designated peak time
- demand shifting to other time frames
- modes of adaptation, and habit formation by households: does behavior change on specific peak dates, or across the board?
- how the experiment changes consumer's attitude to peak-pricing programs in which the price of electricity can vary significantly with time

A specific design choice is to include multiple nudges in spite of the fact that the study is likely not powered to disentangle individual effects. This is motivated by two assumptions: reasonable nudges tend to have weakly positive effects, and weakly positive interaction effects; the distribution of treatment effects from nudges has a fat right tail. In that setting, optimal experimentation involves establishing a successful package of interventions before further identifying which ones really matter.
External Link(s)

Registration Citation

Citation
chassang, sylvain et al. 2024. "Motivating and supporting load shedding.." AEA RCT Registry. April 26. https://doi.org/10.1257/rct.13422-1.0
Sponsors & Partners
Experimental Details

Interventions

Intervention(s)
Incentives & nudges
Intervention Start Date
2024-01-31
Intervention End Date
2024-05-01

Primary Outcomes

Primary Outcomes (end points)
The study's outcomes of interest include:
- demand reduction at designated peak time
- demand shifting to other time frames
- modes of adaptation, and habit formation by households: does behavior change on specific peak dates, or across the board?
- how the experiment changes consumer's attitude to peak-pricing programs in which the price of electricity can vary significantly with time
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
A specific design choice is to include multiple nudges in spite of the fact that the study is likely not powered to disentangle individual effects. This is motivated by two assumptions: reasonable nudges tend to have weakly positive effects, and weakly positive interaction effects; the distribution of treatment effects from nudges has a fat right tail. In that setting, optimal experimentation involves establishing a successful package of interventions before further identifying which ones really matter.
Experimental Design Details
Not available
Randomization Method
randomization done in office by a computer
Randomization Unit
household
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
170-200
Sample size: planned number of observations
170-200
Sample size (or number of clusters) by treatment arms
20 randomized control + >1000 matched controls
Factorial design with 150-180 treated households, and 3 exclusive factors (incentive) and 2 non exclusive factors (nudges)
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Supporting Documents and Materials
IRB

Institutional Review Boards (IRBs)

IRB Name
IRB Approval Date
IRB Approval Number
Analysis Plan