The effect of short-term subsidies on demand for potable water in rural Bihar, India: Pilot study
Last registered on June 20, 2019

Pre-Trial

Trial Information
General Information
Title
The effect of short-term subsidies on demand for potable water in rural Bihar, India: Pilot study
RCT ID
AEARCTR-0003829
Initial registration date
February 04, 2019
Last updated
June 20, 2019 5:20 AM EDT
Location(s)

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Primary Investigator
Affiliation
UC Berkeley School of Public Health
Other Primary Investigator(s)
PI Affiliation
UC Berkeley School of Public Health
Additional Trial Information
Status
In development
Start date
2019-03-20
End date
2019-12-31
Secondary IDs
Abstract
We investigate the impact of short-term subsidies on demand for a novel preventative health product in rural Bihar, India. Through this pilot we seek to determine current demand for potable water, as well as to test the effects of providing different subsidy levels on future product demand in advance of a larger RCT.
External Link(s)
Registration Citation
Citation
Cameron, Drew and William Dow. 2019. "The effect of short-term subsidies on demand for potable water in rural Bihar, India: Pilot study." AEA RCT Registry. June 20. https://www.socialscienceregistry.org/trials/3829/history/48359
Sponsors & Partners

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Experimental Details
Interventions
Intervention(s)
This pilot study tests the impact of subsidies for week-long subscriptions of daily potable water delivery in 20-liter jugs to participating families.
Intervention Start Date
2019-03-24
Intervention End Date
2019-04-06
Primary Outcomes
Primary Outcomes (end points)
Our primary outcome of interest is uptake of subscription renewals between high price vs. low price treatment groups at end-line.
Primary Outcomes (explanation)
For an intent to treat analysis, we will compare the roughly 50% of households receiving a low price (10 - 20 INR) vs. those receiving a high price (30 - 40 INR). As a sensitivity test we can adjust the threshold for high vs. low prices at baseline by comparing a low price of 10 INR vs. a high price of 20 INR and above, as well as a low price of 30 INR and below vs. a high price of 40 INR. To further test sensitivity of our threshold, we may also include 5 INR increments, testing at each possible point.
Secondary Outcomes
Secondary Outcomes (end points)
Secondary Outcomes (explanation)
Experimental Design
Experimental Design
In this pilot we will use a random price auction to offer random levels of subsidy (at 10 rupee increments between 42.9%-85.7% off the market price) for a 1-week potable water delivery subscription. At end-line, we will return to households and offer the same slightly discounted price for the water delivery subscriptions. The purpose will be to test whether higher subsidies increase or decrease demand for the product when it is offered again later.
Experimental Design Details
Not available
Randomization Method
The drawing of a price for the week-long subscriptions during the random price auction constitutes our method of randomization.
Randomization Unit
Individual households.
Was the treatment clustered?
No
Experiment Characteristics
Sample size: planned number of clusters
No clustering.
Sample size: planned number of observations
A minimum of 200 households. Our IRB approval allows for a maximum of 300 households, but budget constraints will likely keep us to 200.
Sample size (or number of clusters) by treatment arms
Presuming that the in-person randomization process establishes balanced prices, we expect the following groupings to emerge:
10 INR: 50 households
20 INR: 50 households
30 INR: 50 households
40 INR: 50 households
For an intent to treat analysis, we will compare those 100 households receiving a low price (10 - 20 INR) vs. those 100 receiving a high price (30 - 40 INR). Increasing the sample to 300 households would yield a sample of 150 households per arm.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
With alpha 0.05, beta 0.8, for a two-tailed test, assuming a 20% uptake among the "high price" group at end-line, and with 50%, of the sample assigned to either arm, we will be able to detect a 15.9 percentage points MDE in uptake between arms. This also assumes 0% attrition in either sample arm. Increasing the sample to 300 households with all other parameters remaining the same would yield an MDE of 13.0 percentage points difference between arms.
IRB
INSTITUTIONAL REVIEW BOARDS (IRBs)
IRB Name
UC Berkeley Committee for Protection of Human Subjects
IRB Approval Date
2019-02-15
IRB Approval Number
2018-04-11016