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Illegal activity's response to revealing its existence
Last registered on September 06, 2017

Pre-Trial

Trial Information
General Information
Title
Illegal activity's response to revealing its existence
RCT ID
AEARCTR-0002397
Initial registration date
September 05, 2017
Last updated
September 06, 2017 1:55 PM EDT
Location(s)

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Request Information
Primary Investigator
Affiliation
Other Primary Investigator(s)
Additional Trial Information
Status
In development
Start date
2017-08-29
End date
2021-08-29
Secondary IDs
Abstract
Illegal activity is widespread around the world. Local authorities probably observe illegal
activity with a large footprint, but decide not report to the National government. To overcome the
challenge of measuring illegal mining, we constructed a novel dataset using machine learning
predictions on satellite imagery features. In this research proposal we outline how we plan to
disclose this information to the authorities to address three research questions: Does revealing
the existence of illegal activity reduces the extent of the activity?; Does the agent informed
matters for the effect?; Does illegal activity relocate to neighboring municipalities not treated?
External Link(s)
Registration Citation
Citation
Saavedra, Santiago. 2017. "Illegal activity's response to revealing its existence." AEA RCT Registry. September 06. https://doi.org/10.1257/rct.2397-1.0.
Former Citation
Saavedra, Santiago. 2017. "Illegal activity's response to revealing its existence." AEA RCT Registry. September 06. http://www.socialscienceregistry.org/trials/2397/history/21224.
Experimental Details
Interventions
Intervention(s)
The proposed intervention is a 2x2 Randomized Control Trial revealing the predicted location of mines to the local and national Government.
Intervention Start Date
2017-08-29
Intervention End Date
2017-12-31
Primary Outcomes
Primary Outcomes (end points)
Percentage of area illegally mined
Primary Outcomes (explanation)
We plan to monitor the evolution of illegal mining using satellite imagery. The methodology is described in Saavedra-Romero (2017)
Secondary Outcomes
Secondary Outcomes (end points)
Secondary Outcomes (explanation)
Experimental Design
Experimental Design
The proposed intervention is a 2x2 Randomized Control Trial revealing the predicted location of mines to the local and national Government.
Experimental Design Details
Not available
Randomization Method
Randomization done in office with Stata
Randomization Unit
State level ("Departamento")
Was the treatment clustered?
Yes
Experiment Characteristics
Sample size: planned number of clusters
32 states
Sample size: planned number of observations
There are 927 municipalities with mining potential
Sample size (or number of clusters) by treatment arms
200 municipalities where BOTH the National and local governments are informed of the location of mines
200 municipalities where ONLY local governments are informed of the location of mines
200 municipalities where ONLY the national government is informed of the location of mines
327 municipalities control
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
The Minimum Detectable Effect is 2.21 percentage points. The mean of the fraction of mined area mined illegally in 2014 was 83.47 ppts (23.61 standard deviation).
IRB
INSTITUTIONAL REVIEW BOARDS (IRBs)
IRB Name
IRB Approval Date
IRB Approval Number