Whom Do Citizens Credit: Attribution and the Limits of Participatory Budgeting in Uzbekistan

Last registered on September 21, 2026
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Pre-Trial

Trial Information

General Information

Title
Whom Do Citizens Credit: Attribution and the Limits of Participatory Budgeting in Uzbekistan
RCT ID
AEARCTR-0019722
Initial registration date
September 14, 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
September 21, 2026, 9:13 AM EDT

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

Locations

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Primary Investigator

Name
Ikromjon Tuhtasunov
Affiliation
University of illinois at Urbana Champaign
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Other Primary Investigator(s)

Additional Trial Information

Status
On going
Start date
2026-09-09
End date
2026-10-31
Keywords
Governance
Additional Keywords
JEL code(s)
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
Participatory budgeting gives citizens a direct role in deciding how public resources are spent. Existing studies show that such participation can improve citizens’ evaluations of government. Yet my previous survey experiment in Uzbekistan finds close to zero average effects of participatory budgeting on state legitimacy. I argue that this puzzle can be explained, in part, by attribution. Participatory institutions can increase state legitimacy only when citizens directly credit the state for public goods that these institutions bring. Citizens may instead credit their communities or view the state and community as jointly responsible. I test this argument with a five arm survey experiment in Uzbekistan. Respondents receive different information about who is responsible for the same successful participatory budgeting project: the government, the community, both actors, or no actor in particular. I examine how these different attribution frames affect state legitimacy, evaluations of government, horizontal trust and collective efficacy, and support for participatory budgeting. I also test whether knowledge of social rights shape how citizens respond to state credit. The study shows how attribution can help explain when participatory institutions strengthen state legitimacy and when their effects remain at the community level.
External Link(s)

Registration Citation

Citation
Tuhtasunov, Ikromjon. 2026. "Whom Do Citizens Credit: Attribution and the Limits of Participatory Budgeting in Uzbekistan." AEA RCT Registry. September 21. https://doi.org/10.1257/rct.19722-1.0
Sponsors & Partners
Experimental Details

Interventions

Intervention(s)
I use an original online survey with a target of 2,500 adults who are permanent residents of Uzbekistan. I randomly assign eligible respondents with equal probability to one of five unlabeled conditions in a between-subjects design. T1 is a pure control. T2 through T5 receive the same common description of Initiatives Budgeting and the same successful clean-water project. The four treated arms differ only in the attribution language that follows the common description.
Intervention Start Date
2026-09-09
Intervention End Date
2026-10-31

Primary Outcomes

Primary Outcomes (end points)
Perceptions of legitimacy
Primary Outcomes (explanation)
Perception of state legitimacy is a four-point response scales. It includes three questions about voluntary deference and obligation toward the national state. The questions include 1) agreement that the state maintains right to make laws that everybody obeys; agreement that people should follow government decisions even when they disagree, agreement that tax authorities have the right to require tax payments. I will use an index that combines these three items. As an exploratory outcome variable, I look at the reported likelihood of reporting a missing QR-coded receipt to the tax agency.

Secondary Outcomes

Secondary Outcomes (end points)
Legitimating beliefs and horizontal trust as exploratory post-outcome variables
Secondary Outcomes (explanation)
Secondary outcomes measure horizontal trust and legitimating beliefs. It captures complaint responsiveness, trust in national and local government leaders, whether residents believe they can work together to solve common problems and whether they trust people in their neighborhood. The questions also include support for Initiatives Budgeting. It includes a choice between letting the government allocate local funds on its own and using participatory budgeting. I also measure whether respondents have participated in the program before. I use this measure for descriptive analysis and may explore it as a moderator, but it is not a primary outcome.

Experimental Design

Experimental Design
The study will recruit adult participants from Uzbekistan via online advertisements on the Telegram messaging platform, leveraging large Telegram channels/groups. Using an online survey allows broad reach and an approximately nationally diverse sample of citizens active on social media. My target sample size is approximately 2500 respondents, which (accounting for some attrition) should provide around 1500-2000 analyzable cases.

Participants will be randomly assigned with equal probability into one of five treatment groups. A simple random assignment will be implemented through the survey platform Qualtrics to ensure true randomization. A small caveat: if a respondent begins but does not complete the survey, it may slightly affect the distribution of random assignment, potentially resulting in minor imbalances across treatment groups. Each participant will thus have a somewhat equal chance of being in any one condition:
Experimental Design Details
Not available
Randomization Method
Qualtrics function randomly places every new participant into one of five groups
Randomization Unit
individual participant
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
2500 individuals
Sample size: planned number of observations
2500
Sample size (or number of clusters) by treatment arms
500 for each treatment arm
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
I target 2,500 respondents, or 500 per arm. With this sample, a two-arm comparison has approximately 80 percent power to detect an effect of 0.18 standard deviations at the 5 percent level. If pre-treatment covariates account for one fifth of outcome variance, the corresponding detectable difference is approximately 0.16 standard deviations. The study is therefore designed for small-to-moderate pairwise effects
Supporting Documents and Materials

Documents

Document Name
Survey questionnaire
Document Type
survey_instrument
Document Description
File
Survey questionnaire

MD5: 3eb25ea08cf07330089ab6fcafac9584

SHA1: 82c3b108d1770e21654e2799edd5fdaf94e69f5d

Uploaded At: September 14, 2026

IRB

Institutional Review Boards (IRBs)

IRB Name
University of Illinois Urbana-Champaign
IRB Approval Date
2026-09-03
IRB Approval Number
IRB25-0100
Analysis Plan

Analysis Plan Documents