Responding to the COVID-19 pandemic: How municipal government performance affects electoral accountability in Mexico
Last registered on June 14, 2021

Pre-Trial

Trial Information
General Information
Title
Responding to the COVID-19 pandemic: How municipal government performance affects electoral accountability in Mexico
RCT ID
AEARCTR-0007789
Initial registration date
June 12, 2021
Last updated
June 14, 2021 11:36 AM EDT
Location(s)

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Primary Investigator
Affiliation
Columbia University
Other Primary Investigator(s)
PI Affiliation
Harvard University
PI Affiliation
Harvard University
PI Affiliation
ITAM
Additional Trial Information
Status
On going
Start date
2021-05-28
End date
2021-09-30
Secondary IDs
Abstract
Political accountability is regarded as critical for responsive government, economic development, and equitable policy-making. However, effective accountability is often constrained by voters lacking the information required to evaluate the performance of elected politicians. Moreover, conditional on receiving information, political polarization and selective engagement with content may lead voters to reject credible information. Policy responses to the COVID-19 pandemic, which is both salient while also polarizing public opinion on policy responses, provides an opportunity for voters to learn about the priorities and competence of governments. To understand how voters hold elected politicians accountable for their crisis management, we conduct a randomized evaluation of the effect of Facebook ads---sent by Data Cívica, a local civil society organization---documenting the policies and COVID-19 case and death counts of Mexican municipalities, relative to other municipalities in the same state, ahead of the June 2021 elections. This project examines the effect of such information, as well as an additional randomized message encouraging consumers to view the information through a nonpartisan lens, on the beliefs, attitudes, and voting behaviors of Mexican citizens in medium-sized municipalities across the country. To this end, we will examine the effects of localized Facebook ad campaigns on electoral returns and the effects of the ads on citizen beliefs and intended vote in the context of a pre-election online survey.
External Link(s)
Registration Citation
Citation
Enríquez, José Ramón et al. 2021. "Responding to the COVID-19 pandemic: How municipal government performance affects electoral accountability in Mexico." AEA RCT Registry. June 14. https://doi.org/10.1257/rct.7789-1.0.
Sponsors & Partners

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Experimental Details
Interventions
Intervention(s)
In collaboration with local civil society organization, Data Cívica, we examine the effects of providing Mexican voters with information about their municipal government's response to COVID-19 and relative COVID-19 cases and deaths in their municipality. In particular, Data Cívica's informational video ads benchmark COVID-19 cases and deaths per capita in their municipality against other municipalities within the same state. Variants of the ad further inform viewers of policies implemented by the municipal government in response to the pandemic and---given the increasingly polarized political space in Mexico---seek to increase internalization of the information by encouraging viewers to consider the information in a non-partisan way.
Intervention Start Date
2021-05-28
Intervention End Date
2021-06-02
Primary Outcomes
Primary Outcomes (end points)
Precinct-level electoral outcomes: turnout, incumbent vote share.

Survey outcomes: beliefs about municipal governments and vote intentions.
Primary Outcomes (explanation)
Secondary Outcomes
Secondary Outcomes (end points)
Secondary Outcomes (explanation)
Experimental Design
Experimental Design
The impact of the ads will be evaluated by two parallel experiments. First, a two-level randomization process is used to assign municipalities to receive different Facebook ad campaigns and then to assign different geographical segments within those municipalities to receive these ads. This will enable the research team to measure the direct and (within-municipality) spillover effects of the ads on precinct-level voting behavior. Second, to better understand how voter beliefs and vote intentions are influenced by the video ads and the mechanisms driving any effects, the research team will conduct a pre-election online survey that includes a battery of questions about voter preferences and randomizes exposure to the ads within the survey itself.
Experimental Design Details
Not available
Randomization Method
Facebook ad intervention: computer in office.

Survey-level intervention: Qualtrics.
Randomization Unit
Facebook ad intervention:
--- Higher-level randomization: municipality.
--- Lower-level randomization: segments within municipalities.

Survey intervention: individual.
Was the treatment clustered?
Yes
Experiment Characteristics
Sample size: planned number of clusters
Facebook ad intervention: 500 municipalities, each divided in 5 segments.
Sample size: planned number of observations
Facebook ad intervention: 2,500 segments (this randomization unit in turn contains electoral precincts). Survey-level intervention: ~2,400 individual respondents.
Sample size (or number of clusters) by treatment arms
Facebook ad intervention: 300 control municipalities (1,500 control segments); 100 basic treatment municipalities (100 basic treatment, 100 basic + policies segments, and 300 control segments); 100 polarization treatment municipalities (100 polarization treatment, 100 polarization + policies segments, and 300 control segments).

Survey-level intervention: ~800 control individuals; ~400 basic treatment individuals; ~400 polarization treatment individuals; ~400 basic + policies treatment individuals; ~400 basic + policies treatment individuals.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB
INSTITUTIONAL REVIEW BOARDS (IRBs)
IRB Name
Columbia Institutional Review Board
IRB Approval Date
2021-05-28
IRB Approval Number
AAAT7402
IRB Name
Harvard Committee on the Use of Human Subjects
IRB Approval Date
2021-06-03
IRB Approval Number
IRB21-0559
Analysis Plan

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