x

Please fill out this short user survey of only 3 questions in order to help us improve the site. We appreciate your feedback!
Leveraging Local Electoral Accountability to Improve Service Delivery in Rural India
Last registered on March 22, 2021

Pre-Trial

Trial Information
General Information
Title
Leveraging Local Electoral Accountability to Improve Service Delivery in Rural India
RCT ID
AEARCTR-0007380
Initial registration date
March 19, 2021
Last updated
March 22, 2021 1:21 PM EDT
Location(s)
Region
Primary Investigator
Affiliation
Yale University
Other Primary Investigator(s)
PI Affiliation
University of Michigan
PI Affiliation
Yale University
PI Affiliation
Yale University
Additional Trial Information
Status
On going
Start date
2020-09-01
End date
2022-07-01
Secondary IDs
Abstract
This study focuses on how information constraints for local bureaucrats and politicians affect processing of wage payments for low-income workers who participate in the Indian government’s primary safety net program for the rural poor, designed around the Mahatma Gandhi National Rural Employment Guarantee Act, or MGNREGA. The intervention tests whether providing wage-payment-related information through the local bureaucratic and political governance structures can expedite processing of worker wage payments, whether there is complementarity or substitutability in providing this information to both bureaucrats and elected leaders, and the extent to which electoral incentives and other incentives to collaborate mediate these results.
External Link(s)
Registration Citation
Citation
Allard, Jenna et al. 2021. "Leveraging Local Electoral Accountability to Improve Service Delivery in Rural India." AEA RCT Registry. March 22. https://doi.org/10.1257/rct.7380-1.0.
Sponsors & Partners

There are documents in this trial unavailable to the public. Use the button below to request access to this information.

Request Information
Experimental Details
Interventions
Intervention(s)
In this randomized control trial (RCT), which takes place across three districts in the state of Bihar, we examine how MGNREGA worker wage payment processing times are affected by sending messages which potentially decrease the costs of acquiring management-relevant information and monitoring for local-level bureaucrats and/or elected officials involved with the program.
Intervention Start Date
2020-09-21
Intervention End Date
2021-09-30
Primary Outcomes
Primary Outcomes (end points)
Our primary outcome of interest is average time to complete the steps of worker wage payment processing under panchayat and block officer purview.
Primary Outcomes (explanation)
Secondary Outcomes
Secondary Outcomes (end points)
We will additionally examine variability of processing times (relying primarily on average absolute deviation), volume of work, and local electoral performance of mukhiyas in the expected 2021 election cycle.
Secondary Outcomes (explanation)
Experimental Design
Experimental Design
Treatment assignment is randomized at the level of gram panchayat (village cluster). Messages with information related to wage payment processing are sent at regular intervals to officials’ own mobile phones and only provide information about the locality over which they have responsibility.
Treatment arms are defined as follows:
1. Control: status quo, bureaucrats and elected officials do not receive payment-related messages.
2. TB: only bureaucrats are sent payment-related messages.
3. TP: only elected officials (politicians) are sent payment-related messages.
4. TBP: elected officials and bureaucrats both receive payment-related messages.
Experimental Design Details
Not available
Randomization Method
The randomization of districts was completed in an office by a computer using STATA.
Randomization Unit
Gram panchayat
Was the treatment clustered?
No
Experiment Characteristics
Sample size: planned number of clusters
1,077 gram panchayats
Sample size: planned number of observations
We plan to focus the analysis of our primary outcome of interest at the panchayat-month level for the 1,077 gram panchayats in our sample for a 10+ month period (subject to budget). We also plan to utilize electoral results data, at the panchayat/candidate level, from an election that is expected to occur during our intervention period. Additionally, we aim to collect and use baseline and follow up survey data from the local elected officials (mukhiyas) and bureaucrats (PRSes) present at baseline in our sample panchayats. Each gram panchayat has a single elected official. In some cases, these officials also have representatives that assist them in their work. In these cases, we attempt to survey both mukhiyas and their representatives.
Sample size (or number of clusters) by treatment arms
1. Control: status quo, bureaucrats and elected officials do not receive payment-related messages: 268 gram panchayats
2. TB: only bureaucrats are sent payment-related messages: 270 gram panchayats
3. TP: only elected officials (politicians) are sent payment-related messages: 270 gram panchayats
4. TBP: elected officials and bureaucrats both receive payment-related messages: 269 gram panchayats
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB
INSTITUTIONAL REVIEW BOARDS (IRBs)
IRB Name
Yale University Human Research Protection Program
IRB Approval Date
2020-05-08
IRB Approval Number
2000025840
Analysis Plan

There are documents in this trial unavailable to the public. Use the button below to request access to this information.

Request Information