RCTs and Belief Distortion

Last registered on July 08, 2024

View Trial History

Pre-Trial

Trial Information

General Information

Title

RCTs and Belief Distortion

RCT ID

AEARCTR-0013923

Initial registration date

July 01, 2024

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

July 08, 2024, 12:39 PM EDT

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

Locations

Country

India

Region

Primary Investigator

Name

Florencia Hnilo

Affiliation

Stanford University

Contact Primary Investigator

Other Primary Investigator(s)

Additional Trial Information

Status

In development

Start date

2024-09-01

End date

2025-12-15

Keywords

Agriculture, Behavior, Other

Additional Keywords

Spillovers, motivated reasoning, RCTs

JEL code(s)

Secondary IDs

Prior work

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

Abstract

I test a theory of spillover formation based on behavioral biases related to the interpretation of RCTs assignment methods.

External Link(s)

Registration Citation

Citation

Hnilo, Florencia. 2024. "RCTs and Belief Distortion." AEA RCT Registry. July 08. https://doi.org/10.1257/rct.13923-1.0

Sponsors & Partners

Experimental Details

Interventions

Intervention(s)

Intervention (Hidden)

Intervention Start Date

2024-10-01

Intervention End Date

2025-08-31

Primary Outcomes

Primary Outcomes (end points)

Demand for information (willingness to pay, contact the extension services), changes in links (networks), ability perceptions, trust, crop yields, technology adoption, agricultural knowledge

Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)

Secondary Outcomes (explanation)

Experimental Design

I will provide free access to a soil quality test similar to the Soil Health Card for the treatment group within a village. The variation is between villages: I will randomize villages into 1) ambiguous treatment assignment vs visual treatment assignment; 2) high percentage of eligible population into treatment group vs low percentage of eligible population into treatment group; 3) intervention introduced by local organization vs outsider organization

Experimental Design Details

Randomization Method

Between villages, randomization will be done in the office by a computer (Stata); within villages, randomization will be done by a lottery (visual vs non-visual)

Randomization Unit

First level of randomization: village; second level of randomization: individual

Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters

120 villages

Sample size: planned number of observations

4,000 farmers

Sample size (or number of clusters) by treatment arms

20 villages into local organization + visual treatment assignment, 20 villages into outsider organization + visual treatment assignment, 20 villages into local organization + non-visual treatment assignment + high percentage of eligible population into treatment group, 20 villages into local organization + non-visual treatment assignment + low percentage of eligible population into treatment group, 20 villages into outsider organization + non-visual treatment assignment + high percentage of eligible population into treatment group, 20 villages into outsider organization + non-visual treatment assignment + low percentage of eligible population into treatment group

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

Supporting Documents and Materials

IRB