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Liquidity constraints: Allocating clean water to the rural poor

Last registered on December 13, 2022
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Pre-Trial

Trial Information

General Information

Title
Liquidity constraints: Allocating clean water to the rural poor
RCT ID
AEARCTR-0010545
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.

Locations

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Primary Investigator

Name
Fiona Burlig
Affiliation
University of Chicago
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Other Primary Investigator(s)

PI Name
Amir Jina
PI Affiliation
University of Chicago
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PI Name
Anant Sudarshan
PI Affiliation
University of Warwick
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Additional Trial Information

Status
On going
Start date
2022-05-20
End date
2025-05-01
Keywords
Environment & Energy, Health
Additional Keywords
water, resource allocation, quotas
JEL code(s)
D45, O13, Q25, Q53
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
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

Citation
Burlig, Fiona, Amir Jina and Anant Sudarshan. 2022. "Liquidity constraints: Allocating clean water to the rural poor." AEA RCT Registry. December 13. https://doi.org/10.1257/rct.10545-1.0
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Experimental Details

Interventions

Intervention(s)
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
2023-05-20
Intervention End Date
2023-05-31

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?
Yes

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)
Supporting Documents and Materials
IRB

Institutional Review Boards (IRBs)

IRB Name
University of Chicago SRS IRB
IRB Approval Date
2022-05-16
IRB Approval Number
IRB22-0036
Analysis Plan

Analysis Plan Documents

BJS_LiquidityConstraints_PAP_20221205.pdf

MD5: ebbf8734dcf72f9798f6633997606eef

SHA1: b2301c1b4f217c651b501b2a943ac06fc97a0ce9

Uploaded At: December 05, 2022