Non-payment and strategic enforcement: Experimental evidence from Indian electricity

Last registered on September 01, 2026

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Pre-Trial

Trial Information

General Information

Title

Non-payment and strategic enforcement: Experimental evidence from Indian electricity

RCT ID

AEARCTR-0008742

Initial registration date

December 24, 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

December 27, 2021, 11:06 PM EST

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

Last updated

September 01, 2026, 2:48 PM EDT

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

Locations

Country

India

Region

Madhya Pradesh

Primary Investigator

Name

Fiona Burlig

Affiliation

University of Chicago

Contact Primary Investigator

Other Primary Investigator(s)

PI Name

Anant Sudarshan

PI Affiliation

University of Chicago

Contact Investigator

Additional Trial Information

Status

Completed

Start date

2021-11-01

End date

2023-12-27

Keywords

Environment & Energy

Additional Keywords

Development, enforcement, bill non-payment, electricity

JEL code(s)

O13, Q48, H26

Secondary IDs

Prior work

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

Abstract

State revenue collection is challenging in developing-country settings, which in turn reduces the ability of the state to provide public goods. Electricity is a key sector facing substantial revenue challenges. Frequent bill non-payment leads utilities to provide low-quality power supply, including imposing regular blackouts (Burgess et al 2020). In this project, we are working with two state utilities in Madhya Pradesh, India to measure the effectiveness of and design an optimal targeting strategy for enforcement. We randomize 30,000 households into a control group and a variety of enforcement treatments, informed by the public finance literature on tax payments (e.g. De Neve et al 2021), ranging from SMS reminders to disconnections. We plan to compute direct effects of these treatments on bill payments and electricity consumption. We will also estimate treatment effect heterogeneity. To consider optimal targeting from the household's perspective, we will conduct an endline survey to measure household finances, consumption, psychological well-being, and other measures, in order to consider optimal targeting from the household's perspective.

External Link(s)

Registration Citation

Citation

Burlig, Fiona and Anant Sudarshan. 2026. "Non-payment and strategic enforcement: Experimental evidence from Indian electricity." AEA RCT Registry. September 01. https://doi.org/10.1257/rct.8742-1.1

Sponsors & Partners

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Experimental Details

Interventions

Intervention(s)

30,000 households with a record of unpaid electricity bills will be randomly assigned to a control group or a series of utility enforcement treatments starting in December 2021.

Intervention (Hidden)

Households will be assigned to one of 7 groups: pure control, where the utility is requested to take no action; business as usual control, where the utility is given no specific requests; SMS reminder, where households are reminded to pay; SMS social comparison, where households are reminded to pay and informed about average payments among their neighbors; mailed disconnection notice, where households receive a formal disconnection notice via the mail; in-person notice with no disconnection, where households receive this notice via in-person delivery, but no follow-up occurs; and in-person notice with subsequent disconnection, where households receive a notice and, if they do not pay in full, have their electricity disconnected.

See our attached PDF PAP for more details.

Intervention Start Date

2021-12-27

Intervention End Date

2022-06-27

Primary Outcomes

Primary Outcomes (end points)

Electricity consumption, bill payment, arrears, re-connection to the grid (if applicable). Endline survey outcomes to be added prior to fielding the survey.

Primary Outcomes (explanation)

See our attached PDF PAP for more details.

Secondary Outcomes

Secondary Outcomes (end points)

Secondary Outcomes (explanation)

Experimental Design

We perform a stratified randomization where we randomly assign 30,000 households to the treatments described above. We are collecting administrative data from the utility on electricity consumption, bill payments, and connection status. We conducted a baseline survey in November-December 2021, and plan to conduct an endline survey in summer 2022 to examine impacts on additional outcomes such as household finances, consumption, and mental health.

Experimental Design Details

See our attached PDF PAP for more details.

Randomization Method

Stratified randomization done in Stata

Randomization Unit

Household

Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters

30,000 households

Sample size: planned number of observations

30,000 households

Sample size (or number of clusters) by treatment arms

7,500 households pure control. 2,500 households business as usual control. 5,000 households SMS reminder. 5,000 households SMS social comparison. 5,000 households mailed disconnection notice. 2,500 households in-person disconnection notice with no follow-up. 2,500 households in-person disconnection notice with subsequent disconnection.

Minimum detectable effect size for main outcomes (accounting for sample design and clustering)

Supporting Documents and Materials

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