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Input Efficiency as a Solution to Externalities: a randomized controlled trial
Last registered on February 11, 2021

Pre-Trial

Trial Information
General Information
Title
Input Efficiency as a Solution to Externalities: a randomized controlled trial
RCT ID
AEARCTR-0007158
Initial registration date
February 10, 2021
Last updated
February 11, 2021 11:59 AM EST
Location(s)
Region
Primary Investigator
Affiliation
Wageningen University and Research
Other Primary Investigator(s)
PI Affiliation
University of Maryland Baltimore County
PI Affiliation
Carey Business School, Bloomberg School of Public Health, and Whiting School of Engineering, Johns Hopkins University
Additional Trial Information
Status
Completed
Start date
2015-04-01
End date
2016-10-30
Secondary IDs
Abstract
Resource-conserving technologies are widely reported to benefit both the environment and the people who adopt them. Evidence for these “win-win” claims comes largely from modeling or non-experimental designs, and mostly from the energy sector. Using data from a randomized trial of water-efficient technologies, we contrast an experimental estimate of the technologies’ impact on water use with an ex-ante engineering estimate of water use reductions. Using detailed cost information and experimentally elicited time and risk preferences, we estimate the private welfare gains from technology adoption, and contrast those gains using the experimental estimate of impact versus the engineering estimate of impact. A detailed account of installation success and disadoption allows us to explore potential differences.
External Link(s)
Registration Citation
Citation
Alpizar, Francisco, Maria Bernedo del Carpio and Paul J. Ferraro. 2021. "Input Efficiency as a Solution to Externalities: a randomized controlled trial." AEA RCT Registry. February 11. https://doi.org/10.1257/rct.7158-1.0.
Experimental Details
Interventions
Intervention(s)
Treated households were offered water-efficient technologies installed by professional plumbers: (1) 1.5 gpm (gallon per minute) shower heads; and (2) 1 gpm faucet aerators for bathroom and kitchen faucets. During the study period, the offered technologies were not common even in urban areas of Costa Rica. No surveyed home in the study area had such technologies prior to the experiment.
Intervention Start Date
2015-05-01
Intervention End Date
2015-07-30
Primary Outcomes
Primary Outcomes (end points)
Monthly water consumption by households (May 2014 through September 2016, measured by water meters
Primary Outcomes (explanation)
Secondary Outcomes
Secondary Outcomes (end points)
Secondary Outcomes (explanation)
Experimental Design
Experimental Design
Recruitment of Study Communities
In 2014, the Tropical Agriculture and Higher Education Center (CATIE) executed a large Canadian government-funded research project focusing on climate change adaptation and water scarcity in Central America. Part of this project included work in rural communities in western Costa Rica. In particular, the project was interested in exploring the role that water saving technologies could play in reducing the pressure on scarce water resources. In 2014, CATIE’s staff identified community-based water drinking organizations (CBWMO) that had metered household water use and applied variable rate pricing. Staff called the 66 CBWMOs that met these criteria, and asked their management committees if: (1) they had monthly water records of households dating back to 2012 and would share these data by sending them to CATIE, and (2) they were interested in having the project team install water-efficient technology in a randomly chosen subset of their residential customers and in sharing the post-installation water data. Ten CBWMOs transferred the requisite pre-treatment data within 2-3 months after the invitation and nine of them were chosen at random to meet the RCT’s sample size target.

Treatment Intervention
Households were offered water-efficient technologies installed by professional plumbers: (1) 1.5 gpm (gallon per minute) shower heads; and (2) 1 gpm faucet aerators for bathroom and kitchen faucets. During the study period, the offered technologies were not common even in urban areas of Costa Rica. No surveyed home in the study area had such technologies prior to the experiment.
The communities reported 2,246 billed customers in March 2015. Based on the pre-treatment billing data and a pre-treatment field visit, 348 customers were eliminated: customers that had zero consumption between December 2014 and March 2015 (assumed vacant), shared a water meter with another house, or were commercial establishments. The exclusion exercise left 1,898 households for contact.
To contact the households, CATIE had four teams, each with an interviewer and a plumber. Interviewers had bachelors’ degrees and survey experience and were trained to implement the randomization protocol (see below). The four teams, overseen by a field manager, went to the nine communities sequentially. Communities in rural Costa Rica do not have maps with the location of houses and houses are not numbered. Thus, in order to facilitate the randomization procedure and ensure measurement fidelity over time, CATIE created community maps with the location of all houses and placed identification number labels on every water meter in the community. Using the community maps, CATIE divided the community into four equally populated sectors and assigned each team to one of them. Interviews were conducted using a tablet.
The team was able to contact 1,346 heads of households. The interviewer read a short script that comprised: 1) an introduction of team members; 2) information from a CATIE climate study about recent and future weather changes in the region and the implications of these changes for water conservation, 3) a description of the technologies and a video of them in use, and 4) an offer to install the water-efficient technologies for free if their home was selected at random. Households were only randomized to a treatment arm if a head of household indicated he or she was interested in accepting the installed technologies for free that same day.
Of the 1346 households, 1310 agreed to have the technologies installed should they be selected to receive them. Among these households, 395 were visited in May 2015 and the other 915 in June 2015. They were randomized into one of three treatment arms:
1. Control Group: Residents who agreed to install the technologies but did not receive the technologies.
2. No Bonus Group: Residents who agreed to install the technologies and received the technologies.
3. Bonus Group: Residents who agreed to install the technologies and received the technologies. After they had agreed to install the technologies, they were also offered a performance bonus of $38 if they still had all technologies installed when the team returned unannounced sometime in the following six months. A proportional bonus was paid if some, but not all, of technologies were still installed at the time of the audit.
After installation, the team took away the technologies that were replaced.

Audits
CATIE conducted two audits of treated households (November 2015, October 2016) and an audit of a random sample of 63% of the control group four to five months after treatment assignment to check if the technologies had been transferred to control households. None of the control households had the technologies and thus we assume zero non-compliance with the treatment assignment.
Experimental Design Details
Randomization Method
Randomization of Treatment Assignment
In each community, the four teams received a bag of chips. Each team started with an amount equal to half the number of homes in the sector, rounded up and with one or two additional chips if needed to ensure the set was divisible by three (e.g., if there were 160 homes in a sector, the team would receive 81 chips with 27 chips of each color). Once the teams were done with the first bag of chips, the field manager gave them chips in the amount of 50% of the remaining households. When there were fewer than 9 households in the sector, the teams received only 3 chips at a time. This randomization design achieved two objectives. It helped to increase power and it also ensured roughly equal numbers of households assigned to each treatment arm.
Randomization Unit
Household
Was the treatment clustered?
No
Experiment Characteristics
Sample size: planned number of clusters
0
Sample size: planned number of observations
1128 (assuming a 6% minimum detectable effect among 3 groups, alpha=5%, power=80%, based on pretreatment water consumption data from 2012-2104)
Sample size (or number of clusters) by treatment arms
376 in control and 752 in treatment
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB
INSTITUTIONAL REVIEW BOARDS (IRBs)
IRB Name
Georgia State University
IRB Approval Date
2015-03-09
IRB Approval Number
H15413
Post-Trial
Post Trial Information
Study Withdrawal
Intervention
Is the intervention completed?
No
Is data collection complete?
Data Publication
Data Publication
Is public data available?
No
Program Files
Program Files
Reports, Papers & Other Materials
Relevant Paper(s)
REPORTS & OTHER MATERIALS