Local forecasts of development interventions

Last registered on July 22, 2022
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Pre-Trial

Trial Information

General Information

Title
Local forecasts of development interventions
RCT ID
AEARCTR-0009712
Initial registration date
July 10, 2022

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 14, 2022, 4:04 PM EDT

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

Last updated
July 22, 2022, 12:21 AM EDT

Last updated is the most recent time when changes to the trial's registration were published.

Locations

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Primary Investigator

Name
Nicholas Otis
Affiliation
University of California, Berkeley
Contact Primary Investigator

Other Primary Investigator(s)

Additional Trial Information

Status
In development
Start date
2022-07-22
End date
2024-07-22
Keywords
Behavior, Health, Labor, Welfare
Additional Keywords
JEL code(s)
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
This study involves collecting forecasts of results of randomized controlled trials in development. Further study information will be released after data collection has been completed to avoid the possibility of demand effects.
External Link(s)

Registration Citation

Citation
Otis, Nicholas. 2022. "Local forecasts of development interventions." AEA RCT Registry. July 22. https://doi.org/10.1257/rct.9712-2.0
Sponsors & Partners
Experimental Details

Interventions

Intervention(s)
Intervention Start Date
2022-07-22
Intervention End Date
2024-07-22

Primary Outcomes

Primary Outcomes (end points)
Forecast accuracy: The ability of forecasters to predict the causal effects of interventions measured in large randomized experiments.
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
Further study information will be released after data collection has been completed to avoid the possibility of demand effects.
Experimental Design Details
Not available
Randomization Method
Randomization will be done by computer.
Randomization Unit
Randomization will be done at the individual level.
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
N/A
Sample size: planned number of observations
A minimum of 1,500 forecasts will be collected.
Sample size (or number of clusters) by treatment arms
N/A
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Supporting Documents and Materials
IRB

Institutional Review Boards (IRBs)

IRB Name
Berkeley OPHS
IRB Approval Date
2022-07-09
IRB Approval Number
2017-11-10516
Analysis Plan

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