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Voting or abstaining in "managed" elections? An RCT in Bangladesh
Last registered on December 20, 2018

Pre-Trial

Trial Information
General Information
Title
Voting or abstaining in "managed" elections? An RCT in Bangladesh
RCT ID
AEARCTR-0003509
Initial registration date
December 14, 2018
Last updated
December 20, 2018 9:31 PM EST
Location(s)

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Primary Investigator
Affiliation
Monash University
Other Primary Investigator(s)
PI Affiliation
University of St.Gallen
Additional Trial Information
Status
In development
Start date
2018-12-03
End date
2019-10-30
Secondary IDs
Abstract
In many recent elections across the globe, the incumbent government has taken actions prior to or on election day to make its defeat very unlikely. We call such elections "managed" (or authoritarian) elections. We aim to understand the determinants of whether and how people vote in managed elections. In such elections, citizens who oppose the incumbent government have mainly two options: They can vote for an opposition candidate to signal their policy preferences to the regime; or they can abstain from voting to reduce the regime's post-election legitimacy. Our research questions are how the salience of these two options affect whether and how people vote in managed elections; and how this effect differs between areas in which the party of the current incumbent prime minister enjoyed strong support in the past and areas in which it did not. We study these questions in the general elections in Bangladesh that are scheduled for December 30, 2018. Given the current political climate, Bangladesh offers an ideal setting for studying voting behavior in managed elections.
External Link(s)
Registration Citation
Citation
Hodler, Roland and Asad Islam. 2018. "Voting or abstaining in "managed" elections? An RCT in Bangladesh." AEA RCT Registry. December 20. https://doi.org/10.1257/rct.3509-1.0.
Former Citation
Hodler, Roland and Asad Islam. 2018. "Voting or abstaining in "managed" elections? An RCT in Bangladesh." AEA RCT Registry. December 20. https://www.socialscienceregistry.org/trials/3509/history/39290.
Sponsors & Partners

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Experimental Details
Interventions
Intervention(s)
There are two types of treatments. The first is the message that voting outcomes may affect policy-making (T-policy). The second is the message that high turnout may increase the political legitimacy of the government (T-legit).
Intervention Start Date
2018-12-23
Intervention End Date
2019-04-30
Primary Outcomes
Primary Outcomes (end points)
Individual voting participation coded based on the observation of an ink mark on the finger.
Official polling station-level data on turnout and the incumbent vote share.
Survey information about the voting participation of other voters within the respondents' family.
Primary Outcomes (explanation)
Secondary Outcomes
Secondary Outcomes (end points)
Changes between pre-treatment and post-vote surveys in the respondents' view on the value of democracy and their opinion about the role of members of parliament.
Secondary Outcomes (explanation)
Experimental Design
Experimental Design
We choose 150 villages that supported the party of the current incumbent government in past elections and 150 villages that supported the main opposition party. From within these two blocks of villages, we randomly choose 50 villages that receive treatment T-policy, 50 villages that receive treatment T-legit, and 50 control villages. We then randomly select 35-40 individuals per village, with roughly equal gender balance.
Experimental Design Details
Not available
Randomization Method
Randomization done in office by a computer.
Randomization Unit
Village/polling station
Was the treatment clustered?
Yes
Experiment Characteristics
Sample size: planned number of clusters
300 villages
Sample size: planned number of observations
around 11,000 households/individuals
Sample size (or number of clusters) by treatment arms
150 villages that supported AL in past elections and 150 villages that supported BNP. We randomly divide both groups of 150 villages into 50 villages that receive treatment T-policy, 50 villages that receive treatment T-legit, and 50 control villages.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB
INSTITUTIONAL REVIEW BOARDS (IRBs)
IRB Name
Monash University Human Research Ethics Committee
IRB Approval Date
2018-10-29
IRB Approval Number
17640
Analysis Plan

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