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Direct Benefit Transfers for Electricity - Punjab
Last registered on March 23, 2019

Pre-Trial

Trial Information
General Information
Title
Direct Benefit Transfers for Electricity - Punjab
RCT ID
AEARCTR-0004002
Initial registration date
March 18, 2019
Last updated
March 23, 2019 8:07 PM EDT
Location(s)

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Primary Investigator
Affiliation
Yale University
Other Primary Investigator(s)
PI Affiliation
University of Chicago
Additional Trial Information
Status
On going
Start date
2018-01-01
End date
2020-03-31
Secondary IDs
Abstract
Bad governance can be due not only to corruption but to deliberate, inefficient policy choices that pander to interest groups. The free provision of power to farmers in Punjab, India, is an example of such a policy. Farmers, given power for free, use too much, and have rapidly drained the groundwater resources of the state. The policy persists despite its high social costs due to the political power of the farmers’ unions. This project will conduct a large experiment, in partnership with the Government of Punjab, to offer lump-sum transfers in exchange for farmers’ voluntarily agreeing to face a marginal price for power. We use this experiment to study the persistence of inefficient policies. In particular, we will measure what farmers choose to enroll in the new tariff, and how this depends on both their expected financial gains and their political leanings (such as union affiliation). We will estimate adopters’ electricity demand to measure the efficiency gains from pricing power and use these estimates to learn about what the government’s redistributional objective must be in order to justify continuing the policy of free power. Improved state capacity, in the form of better monitoring and transfer technology, may now make targeted lump-sum transfers a viable alternative policy to the traditional and inefficient in-kind redistribution of electricity.
External Link(s)
Registration Citation
Citation
Ryan, Nicholas and Anant Sudarshan. 2019. "Direct Benefit Transfers for Electricity - Punjab." AEA RCT Registry. March 23. https://doi.org/10.1257/rct.4002-1.0
Former Citation
Ryan, Nicholas, Nicholas Ryan and Anant Sudarshan. 2019. "Direct Benefit Transfers for Electricity - Punjab." AEA RCT Registry. March 23. https://www.socialscienceregistry.org/trials/4002/history/43940
Experimental Details
Interventions
Intervention(s)
Intervention Start Date
2019-06-20
Intervention End Date
2019-10-20
Primary Outcomes
Primary Outcomes (end points)
Electricity consumption, Groundwater consumption, methods adopted for reducing the consumption for electricity and groundwater
Primary Outcomes (explanation)
Secondary Outcomes
Secondary Outcomes (end points)
Secondary Outcomes (explanation)
Experimental Design
Experimental Design
In this study, we propose to evaluate Direct Benefit Transfers for Electricity (DBTE) with a cluster-randomized design at the level of the electricity feeder. The evaluation design is a cluster-based design in 400 agricultural feeders from two power circles (similar to districts) namely – Patiala and Ludhiana. An electricity feeder is the lowest level of the electricity grid, at which power supply is controlled, and typically serves from 50 to 150 farmers. We will randomly assign half of feeders to treatment and the remaining to control. The sample circles have been selected on the basis of groundwater scarcity. In treatment feeders, farmers will have the opportunity, but not the obligation, to enroll, whereas in control feeders farmers will not be permitted to enroll. We therefore expect imperfect compliance (an encouragement design) in the treatment feeders but perfect compliance in the control.
Experimental Design Details
Not available
Randomization Method
Randomization is done in office by a computer to assign 200 feeders randomly to the treatment group and the remaining to the control group.
Randomization Unit
Feeder level randomization. An electricity feeder is the lowest level of the electricity grid, at which power supply is controlled, and typically serves from 50 to 150 farmers.
Was the treatment clustered?
Yes
Experiment Characteristics
Sample size: planned number of clusters
400 feeders
Sample size: planned number of observations
Surveying 5600 farmers falling under 400 feeders
Sample size (or number of clusters) by treatment arms
200 feeders treatment and 200 feeders control
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB
INSTITUTIONAL REVIEW BOARDS (IRBs)
IRB Name
Institute of Financial Management and Research
IRB Approval Date
2018-10-29
IRB Approval Number
N/A
IRB Name
University of Chicago (AURA)
IRB Approval Date
2018-12-13
IRB Approval Number
IRB18-1448
IRB Name
Yale University Human Subjects Committee
IRB Approval Date
2018-12-06
IRB Approval Number
2000023926