Disentangling the costs of meter sharing: experimental evidence from Ethiopia

Last registered on May 21, 2025

Pre-Trial

Trial Information

General Information

Title
Disentangling the costs of meter sharing: experimental evidence from Ethiopia
RCT ID
AEARCTR-0015626
Initial registration date
May 09, 2025

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
May 21, 2025, 11:51 AM EDT

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

Locations

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Primary Investigator

Affiliation
UNU-MERIT and Maastricht University

Other Primary Investigator(s)

PI Affiliation
University of Copenhagen
PI Affiliation
Maastricht University
PI Affiliation
University College Dublin (UCD)
PI Affiliation
Duke University
PI Affiliation
Environment and Climate Research Center, Policy Studies Institute

Additional Trial Information

Status
In development
Start date
2025-06-15
End date
2026-12-31
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
A significant share of households in low-income urban areas access electricity from shared meters, which may result in suboptimal electricity use. However, this issue has received little attention from academics and policymakers. While electricity meter sharing may reduce the fixed connection costs, it can contribute to reduced energy efficiency, create agency problems between landlords and tenants (due to imperfect information on different households’ electricity consumption), leading to social conflict (mediated by asymmetries in bargaining power and knowledge), and undermining confidence in service provision by the utility.
More specifically, three potential problems arise from meter sharing. First, households may pay significantly below or above their actual consumption, triggering undesirable responses to price-based energy efficiency policies, or to efforts to promote adoption of energy efficient equipment. Second, the inability to know one's consumption creates trust issues and potential social conflict, as the landlord's interest in bill management may misalign with the tenant's perceptions, needs and actions. Third, suboptimal electricity usage can compromise living standards and slow the energy transition. Thus far, though meter sharing is common in low-income countries and has documented adverse effects on equity under many prevailing tariff regimes, there is a lack of evidence on the challenges that meter sharing poses to bill allocation, energy use behaviour, and related welfare implications in low-income countries. This study aims to provide such evidence, to inform analysis of the social benefits of potential policy interventions that reduce these problems.
The study aims to understand whether introducing a consumption monitoring device resolves information asymmetry in electricity consumption between parties. We aim to answer two questions, using a Randomized Controlled Trial (RCT) with two treatment arms and a comparison group. First, we evaluate the impacts of the consumption monitoring devices on landlord-tenant agency relationship and billing sharing arrangement. Second, we estimate the welfare implications of shared vs. unshared connections, under a volume differentiated tariff structure.
External Link(s)

Registration Citation

Citation
Hailemariam, Robel Seifemichael et al. 2025. "Disentangling the costs of meter sharing: experimental evidence from Ethiopia." AEA RCT Registry. May 21. https://doi.org/10.1257/rct.15626-1.0
Experimental Details

Interventions

Intervention(s)
Our study explicitly targets multifamily homes, in which the landlord’s household is one of the residents, in low-income neighborhoods in Addis Ababa. Our intervention has two treatment arms and a control group. The first treatment arm provides an electricity monitoring device to each household (i.e., landlords and tenants) living in the same compound. The second treatment arm provides an electricity monitoring device to each household, and in addition, facilitates a landlord-tenant meeting at the time of distribution of those devices at the multifamily home level.
Intervention Start Date
2025-08-01
Intervention End Date
2026-04-30

Primary Outcomes

Primary Outcomes (end points)
1. Average monthly electricity consumption
2. Average monthly electricity expenditure
3. Trust on service provision
4. Perception of own electricity consumption
5. Bill sharing arrangement
6. Prevalence and nature of landlord/tenant conflicts
7. Appliance ownership and usage frequency
8. Number of new appliances purchased
9. Number of old appliances replaced
10. Number and types of energy efficient practices
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
We will randomly distribute multi-family homes having shared meters into three groups. All households in Group 1 will receive an electricity monitoring device and a poster as a usage guideline. All households in Group 2 will receive an electricity monitoring device and the same poster, and they will additionally participate in a purposefully coordinated landlord and tenant discussion. Households in Group 3 will serve as a pure control during the study period; they will not receive monitoring devices or participate in a facilitated discussion.
Experimental Design Details
Not available
Randomization Method
We will use a computer to randomize our samples
Randomization Unit
Randomization will be done at the multi-family home level.
Was the treatment clustered?
Yes

Experiment Characteristics

Sample size: planned number of clusters
Our samples clusters at multifamily home level. We anticipate enrolling a total of 600 multifamily homes, wherein 300 homes are allocated to treatment groups (150 in each arm) and 300 to control groups, though this is contingent on a listing that will help us determine the number of households living in multifamily homes enrolled in the study.
Sample size: planned number of observations
2400 households
Sample size (or number of clusters) by treatment arms
On average, we expect each multifamily home to have three tenants and a landlord, yielding four households per home/cluster. The total number of planned observations is 2400 households (600 homes/clusters). We will determine the number of clusters to be used based on a listing, during which the following eligibility criteria will be assessed: multifamily home where the landlord resides in the same home as tenants, all households share a meter, and all households consent to participate in the study.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB

Institutional Review Boards (IRBs)

IRB Name
The Institutional Review Board Committee of the College of Business and Economics of Addis Ababa University
IRB Approval Date
2025-02-13
IRB Approval Number
Ref.CBE/A/Dean/RTT/13/2025