Price Incentives for Resource Conservation: Experimental Evidence from Groundwater Irrigation

Last registered on November 03, 2022
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Pre-Trial

Trial Information

General Information

Title
Price Incentives for Resource Conservation: Experimental Evidence from Groundwater Irrigation
RCT ID
AEARCTR-0009337
Initial registration date
May 02, 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
May 03, 2022, 9:47 AM EDT

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

Last updated
November 03, 2022, 5:41 PM EDT

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

Locations

Country
India
Region
Gujarat

Primary Investigator

Name
Ariel Zucker
Affiliation
UC Santa Cruz
Contact Primary Investigator

Other Primary Investigator(s)

PI Name
Nick Hagerty
PI Affiliation
Montana State University
Contact Investigator

Additional Trial Information

Status
On going
Start date
2022-06-01
End date
2024-12-01
Keywords
Agriculture, Environment & Energy, Governance
Additional Keywords
JEL code(s)
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
Groundwater is a vital input to agricultural production worldwide, but a widespread lack of effective regulation leads to overconsumption and depletion, while water supplies are becoming scarcer and less reliable in many regions. We will evaluate a program of price incentives for voluntary groundwater conservation among smallholder farmers in Gujarat, India, where water (and the electricity used to pump it) is scarce and unregulated. To do so, we install meters and offer payments for reduced groundwater pumping in a randomized controlled trial. First, we use the price variation introduced by this program to estimate the price elasticity of groundwater demand, a key parameter required for efficient regulation by any means. Then, we evaluate conservation payments as a potentially useful policy tool in itself, measuring its treatment effects, spillovers, and cost-effectiveness. Pilot evidence confirms that conservation payments are feasible and suggests effects on water use could be large.
External Link(s)

Registration Citation

Citation
Hagerty, Nick and Ariel Zucker. 2022. "Price Incentives for Resource Conservation: Experimental Evidence from Groundwater Irrigation." AEA RCT Registry. November 03. https://doi.org/10.1257/rct.9337-1.2
Sponsors & Partners
Experimental Details

Interventions

Intervention(s)
Farmers receiving the intervention will receive a conservation credit – a financial incentive – for reducing their monthly water usage below an individual-specific benchmark.
Intervention Start Date
2022-11-30
Intervention End Date
2023-03-01

Primary Outcomes

Primary Outcomes (end points)
irrigation intensity
Primary Outcomes (explanation)
inverse hyperbolic sine of hours of use of groundwater pumps

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
To answer our research questions, we will conduct an RCT of incentives to promote irrigation efficiency in agriculture in Saurashtra, a region in the state of Gujarat, India. We aim to test the impact of marginal resource conservation incentives on energy and water conservation.
Experimental Design Details
Not available
Randomization Method
randomization done in office by a computer
Randomization Unit
farmer water-sharing group (this will be a single farmer if the farmer does not share a groundwater irrigation source with others, or a group of neighboring farmers who share a groundwater irrigation source)
Was the treatment clustered?
Yes

Experiment Characteristics

Sample size: planned number of clusters
1340 farmer-sharing groups
Sample size: planned number of observations
1742 farmers
Sample size (or number of clusters) by treatment arms
871 farmers Control
871 farmers Conservation Credits (Treatment), of which:
-25% high payment high benchmark
-25% high payment low benchmark
-25% low payment high benchmark
-25% low payment low benchmark
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
17.2 percent of pumping hours without controls (MDE of .172 for the inverse hyperbolic sine of pumping hours) 6.5 percent of pumping hours using pumping hours residualized following a random-forest prediction method (MDE of .065 for the inverse hyperbolic sine of pumping hours)
Supporting Documents and Materials

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IRB

Institutional Review Boards (IRBs)

IRB Name
MIT COUHES
IRB Approval Date
2017-03-09
IRB Approval Number
1602472778
IRB Name
University of California, Santa Cruz IRB
IRB Approval Date
2022-06-02
IRB Approval Number
HS-FY2022-261
IRB Name
IFMR IRB
IRB Approval Date
2021-05-31
IRB Approval Number
IRB00007107
Analysis Plan