Liquidity constraints: Allocating clean water to the rural poor

Last registered on September 08, 2023


Trial Information

General Information

Liquidity constraints: Allocating clean water to the rural poor
Initial registration date
December 05, 2022

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 13, 2022, 9:47 PM EST

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

Last updated
September 08, 2023, 10:09 AM EDT

Last updated is the most recent time when changes to the trial's registration were published.


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Primary Investigator

University of Chicago

Other Primary Investigator(s)

PI Affiliation
University of Chicago
PI Affiliation
University of Warwick

Additional Trial Information

On going
Start date
End date
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
How should scarce resources be allocated in developing countries? Weitzman (1977) highlights a trade-off between prices, which generate allocative efficiency, and quotas, which might have desirable distributional consequences. In partnership with a private company supplying clean water to rural Odisha, India, we plan to run an experiment to measure the relative effectiveness of different allocation mechanisms. We will measure the price elasticity of demand for clean water, health effects from consuming clean water, and the extent to which liquidity constraints and intra-household inefficiencies reduce consumption. To do so, we implement a cluster-randomized trial, where 160 villages are randomized into a pure control group and multiple treatment arms: (i) discounts; (ii) a monthly quota; and (iii) an exchangeable quota, where unused allocation can be exchanged for cash. We subsequently randomize which households within each treatment village will receive treatment. We plan to measure effects of treatment on water consumption and health outcomes using a combination of survey and administrative data.
External Link(s)

Registration Citation

Burlig, Fiona, Amir Jina and Anant Sudarshan. 2023. "Liquidity constraints: Allocating clean water to the rural poor." AEA RCT Registry. September 08.
Sponsors & Partners

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Experimental Details


We implement a cluster-randomized trial in which villages are randomized into one of four conditions: pure control, discount, pure quota, and exchangeable quota. In each treatment (i.e. not pure control) village, households are subsequently randomized to receive clean water through one of the corresponding allocation mechanisms. The discount and exchangeable quotas have sub-arms that vary the level of the marginal incentive.
Intervention Start Date
Intervention End Date

Primary Outcomes

Primary Outcomes (end points)
Quantity of water purchased; health outcomes.
Primary Outcomes (explanation)
Please see our PDF PAP for more details.

Secondary Outcomes

Secondary Outcomes (end points)
Please see our PDF PAP for more detailed information on outcomes.
Secondary Outcomes (explanation)
Please see our PDF PAP for more details.

Experimental Design

Experimental Design
We conduct a cluster-randomized trial that assigns each of 160 villages to one of four groups, and then allocates approximately 40 households per treatment village to treatment and the remainder to control. We also sample approximately 15 households to survey in each village.
Experimental Design Details
Not available
Randomization Method
Randomization done in office by a computer
Randomization Unit
First level: village. Second level: household.
Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters
160 villages
Sample size: planned number of observations
160 villages x approximately 500 households per village: approx 80,000 households. Approx 1,800 households in the survey.
Sample size (or number of clusters) by treatment arms
40 villages pure control; 40 villages discount; 40 villages pure quota; 40 villages exchangeable quota. Approximately 40 treatment households per treated village, and all remaining households are control.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)

Institutional Review Boards (IRBs)

IRB Name
University of Chicago SRS IRB
IRB Approval Date
IRB Approval Number
Analysis Plan

Analysis Plan Documents


MD5: ebbf8734dcf72f9798f6633997606eef

SHA1: b2301c1b4f217c651b501b2a943ac06fc97a0ce9

Uploaded At: December 05, 2022


MD5: 9675584ced3161a8d28518da71ae6f97

SHA1: d6783e2519c189b8753a78384fba112f7e4ca8ab

Uploaded At: September 08, 2023