Illegal mining

Project: Research project

Project Details

Description

Illegal activity is widespread in developing countries due to weak law enforcement. Two contributing factors to the problem are the lack of monitoring technologies and the incentives of local bureaucrats. If illegal activity is not monitored, even honest bureaucrats cannot control the problem. Technology has the potential to detect illegal activity. But the effect of information on reducing illegal activity will depend on the enforcement of the bureaucrat. More over the net effect of revealing information on the extent of illegal activity will depend on the displacement of illegal activity to areas with lower enforcement. We plan to study the effect of revealing the location on illegal activity in the case of illegal mining in Colombia.

Illegal mining is very common around the world: The origin of the minerals used in their supply chain could not be identified by 67% of the companies in the United States (GAO, 2016). Illegal mining has both environmental and fiscal impacts for host countries. On the environmental side, illegal mining is associated with greater levels of pollution (TGIATOC, 2016). On the fiscal side, illegal mines typically evades taxes.

Reducing the extent of illegal mining has many fiscal, environmental, and social benefits. It is estimated that the lost tax revenue per hectare of illegal gold mining is $1,100 and the differential health effect on newborns of legal vs illegal mines is $76-$227 (Saavedra-Romero, 2017). Note that this is a lower bound of the health costs because the effect in other population groups has not been quantified. It is estimated that at least 62,000 hectares are mined illegally for gold (UNODC, 2016), consequently the cost for the country is around 77 million dollars.

The current method used by Colombia’s National Government relies on field reports andmanual inspection of satellite images taken two years before. Given that the area of Colombia is 1’042,000 sqkm, many mines go undetected. It is estimated that 78% of gold area is illegally mined (UNODC, 2016). Our innovation uses satellite images that are freely available and can predict the location of illegal activity in the entirety of the country overnight. This would represent a significant reduction in monitoring costs for the government.
In our previous paper (Saavedra-Romero (2017)) we developed a random forest detection model with a 79% precision. For that study we applied the mines detection model for the years 2004-2014. Now we are working on updating the predictions to 2017, to perform the randomized intervention described below.

Keywords

I will produce a paper with the results of the randomized controlled experiment to study the response of illegal activity to revealing its existence. Municipalities were randomly assigned to one of four groups: (1) the observer (local government) was informed of 5 potential mine locations in his jurisdiction; (2) the enforcer (National Government) was informed of five potential mine locations; (3) both observer and enforcer were informed, and (4) control group, where no agent was informed
StatusActive
Effective start/end date2/18/192/18/22

Main Funding Source

  • Internal

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