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Investing Public Goods: Evidence from Experiments on Groundwater Management in Gujarat
Initial registration date
October 23, 2017
October 24, 2017 1:00 PM EDT
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Other Primary Investigator(s)
Additional Trial Information
This project seeks to understand the role of externalities in limiting agricultural irrigation efficiency. In a randomized controlled trial among farmers in coastal areas of Gujarat, we will experimentally offer direct incentives for increasing irrigation efficiency in the form of marginal prices for pumping groundwater. We expect to follow up this small-scale experiment with further work in a larger experiment with additional treatment groups, and more statistical power.
By measuring the effects of this intervention on electricity and water consumption, we can learn how farmers respond to this policy. We provide some of the first experimental evidence on responses to water prices in a developing country. Registration Citation
Hagerty, Nick and Ariel Zucker. 2017. "Investing Public Goods: Evidence from Experiments on Groundwater Management in Gujarat." AEA RCT Registry. October 24.
We will examine the effects of offering “Conservation Credits” to farmers. Farmers receiving this intervention will receive a conservation credit – a financial incentive – for reducing their monthly water usage below an individual-specific benchmark.
Intervention Start Date
Intervention End Date
Primary Outcomes (end points)
Primary Outcomes (explanation)
Secondary Outcomes (end points)
Secondary Outcomes (explanation)
Farmers in the sample will be individually randomized into either a treatment group or control, stratified on village and an irrigation intensity “benchmark” calculated from baseline survey data.
• Group A (Control Group) – will receive no new incentives.
• Group B (Conservation Credits) – will receive payments for reducing electricity consumption below a carefully modeled baseline consumption level.
Experimental Design Details
Random assignment to treatment/comparison groups will be generated by statistical software (STATA).
Was the treatment clustered?
Sample size: planned number of clusters
Sample size: planned number of observations
Sample size (or number of clusters) by treatment arms
45 farmers in each of treatment and control groups.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
INSTITUTIONAL REVIEW BOARDS (IRBs)
MIT Committee on the Use of Humans as Experimental Subjects
IRB Approval Date
IRB Approval Number