Households revealed willingness to pay during winter electricity shortages

Last registered on December 01, 2023
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Pre-Trial

Trial Information

General Information

Title
Households revealed willingness to pay during winter electricity shortages
RCT ID
AEARCTR-0012277
Initial registration date
November 17, 2023

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
December 01, 2023, 4:49 AM EST

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

Locations

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Primary Investigator

Name
Nina Boogen
Affiliation
Zurich University of Applied Sciences (ZHAW)
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Other Primary Investigator(s)

PI Name
Christian Winzer
PI Affiliation
Zurich University of Applied Sciences (ZHAW)
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Additional Trial Information

Status
In development
Start date
2023-11-22
End date
2024-06-30
Keywords
Behavior, Environment & Energy
Additional Keywords
JEL code(s)
C93, D12, D90, Q41
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
The war in Ukraine has sparked a global energy crisis. Switzerland's energy supply is also affected. While the winter of 2022/23 was rather mild in Switzerland, this might not be the case for coming winters. Thus, we design and implement a field experiment, in which we want to test the revealed willingness to pay of households for their heat pump’s energy consumption during winter electricity shortages with relatively extreme electricity prices. The experiment will be implemented in cooperation with a Swiss utility, that invites their residential customers with heat pumps to participate to the study. Our intervention provides treated households with weekly high price signals, the households then decide whether to pay these high prices (deduction form a virtual study budget) or to curtail their heat pump’s consumption and avoid some part of the high energy costs.
External Link(s)

Registration Citation

Citation
Boogen, Nina and Christian Winzer. 2023. "Households revealed willingness to pay during winter electricity shortages." AEA RCT Registry. December 01. https://doi.org/10.1257/rct.12277-1.0
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Experimental Details

Interventions

Intervention(s)
Intervention Start Date
2024-01-02
Intervention End Date
2024-04-30

Primary Outcomes

Primary Outcomes (end points)
(i) reduced heat pumps electricity consumption during the days with price signal (analysis of smart-meter data provided by the utility)
(ii) self-reported change of heating settings (elicited in the follow-up survey)
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
A Swiss utility contacts around 2800 households selected among their customers via postal mail to take part in the experiment. This target group supposedly has a heat pump at their home (requirement for participation). Participants that registered to take part in the study are randomly allocated between the treatment group and the control group after the registration. Afterwards, all participants (treatment and control group) are invited to fill in a baseline survey by e-mail.

The intervention is incentive compatible: This means that the treated participants are endowed with a virtual study budget. Between January and April 2024 we contact the households in treatment group first with an e-mail that includes detailed instructions for the next 15 weeks. Then secondly, our intervention (sending SMS to inform them on the study electricity price, the days of validity and the cost per day for an average heat pump) provides treated households with weekly high price signals. Then the treated households can decide whether they want to pay this price for the households’ heat pump consumption (we will then deduct the monetary amount from the virtual study budget), or whether they want to lower the room temperature to reduce energy costs (we will then deduct a smaller monetary amount from the virtual study budget depending on the actual electricity curtailment). Depending on this, the virtual study budget will be reduced accordingly week by week. During this period, we do not contact the households in control group.

In May – after the 15-week study period, we invite the households in the treatment and control group by e-mail to fill in a short follow-up survey. The follow-up survey collects information on the participants’ experience during the intervention and the behaviour regarding their heat pump. Further, we get the smart meter data of the participating households from the utility. Using this data we calculate the remaining balance of the virtual study budget, which we will then pay out to the participants. Also, the households in the control group will be informed about their participant compensation pay-out.
Experimental Design Details
Not available
Randomization Method
Randomization done in university office by a computer
Randomization Unit
Randomization at individual level, within the target group of the utility
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
950
Sample size: planned number of observations
950
Sample size (or number of clusters) by treatment arms
475
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
It is well known that electricity consumption patterns show extremely dispersed distributions. Thus, we focus on first differences in electricity consumption. Changes in electricity consumption are less variable than levels of electricity consumption, since one part of a heat pump’s electricity consumption remains fixed over time (e.g., the efficiency level of the heat pump). This fixed component is filtered out by using the first differences approach. We use day-to-day changes. Minimum detectable effect size is 0.88 kWh/24h, the standard deviation of changes in electricity consumption is 4.82 kWh.
Supporting Documents and Materials
IRB

Institutional Review Boards (IRBs)

IRB Name
ZHAW Ethikausschuss
IRB Approval Date
2023-11-17
IRB Approval Number
EA-ZHAW 2023-021-W
Analysis Plan

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