Public Opinion in Wartime Russia: Internet Restrictions, Repression, and Support for the War

Last registered on September 21, 2026

Pre-Trial

Trial Information

General Information

Title
Public Opinion in Wartime Russia: Internet Restrictions, Repression, and Support for the War
RCT ID
AEARCTR-0019662
Initial registration date
September 08, 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, 8:01 AM EDT

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

Locations

Region
Region
Region

Primary Investigator

Affiliation
ifo Institute für Wirtschaftsforschung e.V.

Other Primary Investigator(s)

PI Affiliation
Columbia University
PI Affiliation
TU Munich
PI Affiliation
Nazarbayev University

Additional Trial Information

Status
In development
Start date
2026-09-09
End date
2026-11-30
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
Our study examines how Russian citizens evaluate political candidates under conditions of war and political repression. The full-scale invasion of Ukraine in 2022 substantially transformed Russia’s domestic political environment, raising concerns that conventional surveys may overstate support for government and wartime policies because respondents face social and legal risks when expressing dissent. To address these challenges, the study employs a forced-choice conjoint experiment in which respondents evaluate pairs of hypothetical State Duma candidates whose profiles vary randomly across eight demographic and policy attributes. These include age, gender, occupation, positions on the war and its termination, internet and social-media restrictions, migration, budget priorities, and mobilization.

The experiment estimates the relative importance of competing wartime and domestic policy preferences while reducing the salience of sensitive political questions. The study also investigates drivers of electoral turnout in Russia, distinguishing between abstention arising from candidate similarity (indifference) and dissatisfaction with the available candidates (alienation). Pre-registered hypotheses focus on preferences toward mobilization, war termination, veteran candidates, migration restrictions, social spending, and information controls, as well as differences across media consumption, age, gender, and education.
External Link(s)

Registration Citation

Citation
Chargaziia, Lasha et al. 2026. "Public Opinion in Wartime Russia: Internet Restrictions, Repression, and Support for the War." AEA RCT Registry. September 21. https://doi.org/10.1257/rct.19662-1.0
Sponsors & Partners

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Experimental Details

Interventions

Intervention(s)
Each respondent is shown six tasks asking to choose between two State Duma candidates with given characteristics, and asked which of them they would choose if the elections to be held. After that they are asked if they would turn out at all if these two candidates were the only ones on the ballot.
Intervention Start Date
2026-09-09
Intervention End Date
2026-11-30

Primary Outcomes

Primary Outcomes (end points)
Choices between candidates and the choice whether to vote at all or not.
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Ranking of each candidate.
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
Forced-choice conjoint experiment.
Experimental Design Details
Not available
Randomization Method
Randomization is done by a computer using JavaScript on a survey platform.
Randomization Unit
Individual
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
2500
Sample size: planned number of observations
In each survey, each individual has an own randomization of the characteristics and stances of the candidates.
Sample size (or number of clusters) by treatment arms
There are no clusters in the typical sense of an RCT; profiles vary across 8 conjoint attributes. Standard errors are clustered on the individual level.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
>99% to detect 5% effect.
IRB

Institutional Review Boards (IRBs)

IRB Name
Ethics Commission, Department of Economics, University of Munich (LMU)
IRB Approval Date
2026-07-27
IRB Approval Number
2026-19
Analysis Plan

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