NIMBYism and Participatory Bias in Latin America

Last registered on August 22, 2025

View Trial History

Pre-Trial

Trial Information

General Information

Title

NIMBYism and Participatory Bias in Latin America

RCT ID

AEARCTR-0016601

Initial registration date

August 21, 2025

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 22, 2025, 6:08 AM EDT

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

Locations

Country

Argentina

Region

Country

Brazil

Region

Country

Colombia

Region

Country

Mexico

Region

Primary Investigator

Name

Carlos Scartascini

Affiliation

Inter-American Development Bank

Contact Primary Investigator

Other Primary Investigator(s)

Additional Trial Information

Status

In development

Start date

2025-08-21

End date

2025-09-26

Keywords

Governance

Additional Keywords

NIMBY; Decision-making

JEL code(s)

Secondary IDs

Prior work

This trial does not extend or rely on any prior RCTs.

Abstract

We run a set of survey experiments to evaluate participation in public consultation meetings and preferences for development projects

External Link(s)

Registration Citation

Citation

Scartascini, Carlos. 2025. "NIMBYism and Participatory Bias in Latin America." AEA RCT Registry. August 22. https://doi.org/10.1257/rct.16601-1.0

Sponsors & Partners

Experimental Details

Interventions

Intervention(s)

A survey experiment designed to study citizen responses to proposed infrastructure projects—specifically metro stations and highways—in Latin American cities. First, we examine how local opposition shapes urban development outcomes, focusing on how geographic proximity to a project influences policy preferences. Second, we review evidence on who tends to participate in public hearings, emphasizing how concentrated costs and diffuse benefits generate a participatory bias. Third, we analyze how the perceived legitimacy of decision-making actors—such as government agencies versus citizen panels—can alter levels of support. Fourth, we consider how the public or private nature
of preference expression influences stated positions, particularly in contexts where social norms or reputational concerns are salient.

Intervention (Hidden)

Intervention Start Date

2025-08-21

Intervention End Date

2025-09-26

Primary Outcomes

Primary Outcomes (end points)

1. Self-reported willingness of respondent to attend a local meeting
2. Preferred project location

Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)

Secondary Outcomes (explanation)

Experimental Design

Randomization of:
1. Proximity to project site
2. Source of recommendation of project development
3. Secret vs public voting

Experimental Design Details

Randomization Method

Randomization was embedded in the LAPOP survey and conducted by them (computer). The experiment employs a randomized factorial design that manipulates two dimensions: (1) the respondent’s spatial proximity to the proposed infrastructure project, and (2) the institutional source of the project’s recommendation. Each dimension includes three and two levels, respectively, resulting in a total of six treatment
arms. Respondents are randomly assigned to each spatial condition with equal probability (1/3), and to each recommendation source with equal probability (1/2), yielding an even distribution across the full 3×2 design.

Randomization Unit

Individual

Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters

The final analytic sample includes 4,147 respondents: 1,006 in Argentina, 1,021 in Brazil,
1,016 in Colombia, and 1,104 in Mexico.

Sample size: planned number of observations

The final analytic sample includes 4,147 respondents: 1,006 in Argentina, 1,021 in Brazil, 1,016 in Colombia, and 1,104 in Mexico.

Sample size (or number of clusters) by treatment arms

Each dimension includes three and two levels, respectively, resulting in a total of six treatment arms. Respondents are randomly assigned to each spatial condition with equal probability (1/3), and to each recommendation source with equal probability (1/2), yielding an even distribution across the full 3×2 design.

Minimum detectable effect size for main outcomes (accounting for sample design and clustering)

See attached document

Supporting Documents and Materials

IRB