When Do Citizens Hold Governments Accountable for Air Pollution Policy?

Last registered on August 31, 2026
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Pre-Trial

Trial Information

General Information

Title
When Do Citizens Hold Governments Accountable for Air Pollution Policy?
RCT ID
AEARCTR-0019514
Initial registration date
August 28, 2026

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
August 31, 2026, 8:39 AM EDT

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

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Primary Investigator

Name
Martin Mattsson
Affiliation
National University of Singapore
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Other Primary Investigator(s)

PI Name
Sangita Vyas
PI Affiliation
Hunter College CUNY
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PI Name
Archana Dhinakar Bala
PI Affiliation
Columbia University
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Additional Trial Information

Status
In development
Start date
2026-08-28
End date
2027-04-30
Keywords
Environment & Energy, Governance
Additional Keywords
Air Pollution, Government Policy, Policy Targets, Policy Implementation
JEL code(s)
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
We will conduct a survey experiment to measure how information about the Indian government’s air pollution policy (the National Clean Air Programme, NCAP), and about the policy’s success or failure, affects citizens’ satisfaction with the government. The experiment is designed to answer three research questions: (i) do citizens reward the government for promising to reduce air pollution, (ii) do citizens reward the government for success in reducing air pollution, and (iii) do citizens punish the government for failure to deliver, and if not, what informational conditions activate a failure penalty? Respondents are randomized across ten arms that combine five informational components: a description of the policy, its quantitative target, a factual framing of its results as either a success (emphasizing the pre-post improvement) or failure (emphasizing the null diff-in-diff estimate), a cue raising citizens’ awareness of the severity of local air pollution, and a cue attributing the policy’s failure to low government effort. The primary outcome is satisfaction with the government’s air pollution policy.
External Link(s)

Registration Citation

Citation
Dhinakar Bala, Archana, Martin Mattsson and Sangita Vyas. 2026. "When Do Citizens Hold Governments Accountable for Air Pollution Policy?." AEA RCT Registry. August 31. https://doi.org/10.1257/rct.19514-1.0
Sponsors & Partners
Experimental Details

Interventions

Intervention(s)
Respondents are randomized into one of ten arms, each combining a subset of five informational components delivered by the enumerator during the phone interview: (1) a policy description: that NCAP was started by the central government in 2019 to reduce air pollution, that the respondent's city is covered, and what the program does; (2) the policy target: NCAP's goal of reducing air pollution by 40% from 2017 levels by 2026; (3) a policy result framing, either a success framing (pollution in NCAP cities has fallen by almost 20% since before the program) or a failure framing (NCAP cities have not seen any decline relative to cities not covered by NCAP), both factually accurate; (4) a pollution awareness cue: the current pollution level in the respondent's city as a multiple of the safe limit, and its health consequences; (5) a low-effort cue: a statement that the government has paid little attention to NCAP since its announcement. The control arm receives none of these components and is debriefed about NCAP at the end of the interview.
Intervention Start Date
2026-08-28
Intervention End Date
2027-04-30

Primary Outcomes

Primary Outcomes (end points)
Satisfaction with the Indian government's policies and actions on air pollution.
Primary Outcomes (explanation)
Questions asked immediately after the information treatment: "If 1 means not satisfied at all, and 5 means extremely satisfied, how satisfied are you with the Indian national government's policies and actions on air pollution?" Responses are rescaled into standard deviations from the control group mean. The order of the national, state, and municipal satisfaction questions is randomized at the individual level, independently of treatment assignment.

Secondary Outcomes

Secondary Outcomes (end points)
(1) rating of the national government's work to reduce air pollution; (2) perceived dedication of the national government to reducing air pollution; (3) perceived ability of the national government to reduce air pollution; (4) satisfaction with the state government's and (5) with the municipal corporation's policies and actions on air pollution; (6) beliefs about NCAP's effect on air pollution (treated arms); (7) the extent to which air pollution affects the likelihood of voting for the ruling party; (8) beliefs about the effect of an unrelated, recently announced government policy (the Pradhan Mantri Viksit Bharat Rozgar Yojana jobs policy), measuring whether information about NCAP spills over to expectations about the government delivering on other promises.
Secondary Outcomes (explanation)
All items are on 1-5 scales and are rescaled into standard deviations from the control group mean.

Experimental Design

Experimental Design
Ten arms: (1) control, no information; (2) policy description; (3) description + target (the full "promise"); (4) description + target + awareness cue; (5) description + target + low-effort cue; (6) description + target + success framing; (7) description + target + success framing + awareness cue; (8) description + target + failure framing; (9) description + target + failure framing + awareness cue; (10) description + target + failure framing + low-effort cue. The primary analysis is a regression of the outcome on arm indicators (control omitted) with city and enumerator fixed effects and heteroskedasticity-robust standard errors; every hypothesis is a pre-specified linear combination of the arm coefficients (promise premium, policy announcement, target above announcement, success framing, failure penalty, implementation incentive, low-effort cue, awareness x failure, effort x failure, awareness x success, awareness on the implementation incentive), plus one joint Wald test that all interaction contrasts are zero. Full details are in the attached pre-analysis plan.
Experimental Design Details
Not available
Randomization Method
Computer-generated within the survey software: at the start of each interview the form draws a uniform random number once, stores it, and maps it to an arm using fixed thresholds corresponding to the target shares. No stratification; the draw and the assigned arm are recorded for every respondent who begins the interview.
Randomization Unit
Individual respondent.
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
N/A
Sample size: planned number of observations
Approximately 10,000 respondents, or more if funding allows.
Sample size (or number of clusters) by treatment arms
Control 900; description 600; description + target 1,800; description + target + awareness 700; description + target + effort 700; description + target + success 1,300; description + target + success + awareness 700; description + target + failure 1,600; description + target + failure + awareness 1,000; description + target + failure + effort 700.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Minimum detectable effects at 80% power for the pre-specified contrasts range from 0.10 to 0.18 standard deviations of the outcome (0.10 SD for the failure penalty, 0.11 SD for the promise premium, 0.17-0.18 SD for the interaction tests).
Supporting Documents and Materials
IRB

Institutional Review Boards (IRBs)

IRB Name
University Integrated Institutional Review Board - City University of New York
IRB Approval Date
2026-06-25
IRB Approval Number
2024-0221-Hunter
Analysis Plan

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