Illegal activity's response to revealing its existence

Last registered on June 14, 2023

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

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
September 06, 2017, 1:55 PM EDT

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

Last updated
June 14, 2023, 12:36 PM EDT

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

Locations

Region

Primary Investigator

Affiliation

Other Primary Investigator(s)

Additional Trial Information

Status
Completed
Start date
2017-08-29
End date
2023-06-13
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
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. 2023. "Illegal activity's response to revealing its existence." AEA RCT Registry. June 14. https://doi.org/10.1257/rct.2397-1.3
Former Citation
Saavedra, Santiago. 2023. "Illegal activity's response to revealing its existence." AEA RCT Registry. June 14. https://www.socialscienceregistry.org/trials/2397/history/182518
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 (Hidden)
In half of the municipalities we will inform local authorities of the location of mines in their municipality. For another random half of the municipalities we will inform the Air Force of the location of mines in those municipalities. For all parties, we will have a questionnaire asking whether they confirmed the presence of mining activity.
Intervention Start Date
2017-08-29
Intervention End Date
2021-10-29

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
In half of the municipalities we will inform local authorities of the location of mines in their municipality. For another random half of the municipalities we will inform the Air Force of the location of mines in those municipalities. For all parties, we will have a questionnaire asking whether they confirmed the presence of mining activity.
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
IPA-IRB
IRB Approval Date
2020-05-20
IRB Approval Number
14468
Analysis Plan

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Post-Trial

Post Trial Information

Study Withdrawal

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Intervention

Is the intervention completed?
No
Data Collection Complete
Yes
Data Collection Completion Date
Final Sample Size: Number of Clusters (Unit of Randomization)
Was attrition correlated with treatment status?
Final Sample Size: Total Number of Observations
Final Sample Size (or Number of Clusters) by Treatment Arms
Data Publication

Data Publication

Is public data available?
No

Program Files

Program Files
Reports, Papers & Other Materials

Relevant Paper(s)

Abstract
Monitoring technologies can help curb illegal activities by providing new information or the threat that the information is widely available. I created a novel technology using machine-learning on satellite imagery to detect illegal mining. Then I disclosed the technology and possible mine locations to government agents to study the impact on illegal activity. I randomly assigned municipalities to one of four groups: (1) information to the observer (local government) about the technology and potential mine locations in his jurisdiction; (2) information to the enforcer (National government); (3) information to both observer and enforcer, and (4) a control group, where I informed no agent. I use an independent expert-validated dataset to evaluate the effect of the intervention in the percentage of gold mining area mined illegally. I find that the treatment effect of disclosing the technology is relatively similar regardless of who is informed: in treated municipalities, illegal mining is reduced in the disclosed locations and surrounding areas. When accounting for negative spillovers --- increases in illegal mining in areas not targeted by the information --- the net reduction is one third smaller. These results illustrate the benefits of new technologies for building state capacity and reducing illegal activity.
Citation
Saavedra, Santiago, Technology and State Capacity: Experimental Evidence from Illegal Mining in Colombia (April 28, 2023). Available at SSRN: https://ssrn.com/abstract=3933128 or http://dx.doi.org/10.2139/ssrn.3933128

Reports & Other Materials