Leveraging Local Electoral Accountability to Improve Service Delivery in Rural India

Last registered on December 28, 2022

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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

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

March 22, 2021, 1:21 PM EDT

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

Last updated

December 28, 2022, 2:13 PM EST

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

Locations

Country

India

Region

Primary Investigator

Name

Jenna Allard

Affiliation

Yale University

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Other Primary Investigator(s)

PI Name

Charity Troyer Moore

PI Affiliation

Yale University

Contact Investigator

PI Name

Rohini Pande

PI Affiliation

Yale University

Contact Investigator

PI Name

Yusuf Neggers

PI Affiliation

University of Michigan

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Additional Trial Information

Status

On going

Start date

2020-09-01

End date

2023-12-31

Keywords

Electoral, Finance & Microfinance, Governance

Additional Keywords

JEL code(s)

D7, I3, J4, M5, O1

Secondary IDs

Prior work

This trial does not extend or rely on any prior RCTs.

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. 2022. "Leveraging Local Electoral Accountability to Improve Service Delivery in Rural India." AEA RCT Registry. December 28. https://doi.org/10.1257/rct.7380-2.1

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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

2022-02-28

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

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

Randomization Method

The randomization of districts was completed in an office by a computer using STATA.

Randomization Unit

Gram panchayat

Was the treatment clustered?

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)

Supporting Documents and Materials

IRB