dc.contributorGrupo de investigaciones. Facultad de Economía. Universidad del Rosario
dc.creatorSaavedra, Santiago
dc.date.accessioned2022-05-02T13:06:48Z
dc.date.accessioned2022-09-22T14:20:54Z
dc.date.available2022-05-02T13:06:48Z
dc.date.available2022-09-22T14:20:54Z
dc.date.created2022-05-02T13:06:48Z
dc.date.issued2022-04-29
dc.identifierhttps://repository.urosario.edu.co/handle/10336/34088
dc.identifierhttps://doi.org/10.48713/10336_34088_
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/3437964
dc.description.abstractNew monitoring technologies can help curb illegal activities by reducing information asymmetries between enforcing and monitoring government agents. I created a novel dataset using machine learning predictions on satellite imagery that detects illegal mining. Then I disclosed the predictions to government agents to study the response of illegal activity. I randomly assigned municipalities to one of four groups: (1) information to the observer (local government) of potential mine locations in his jurisdiction; (2) information to the enforcer (National government) of potential mine locations; (3) information to both observer and enforcer, and (4) a control group, where I informed no one. The effect of information is relatively similar regardless of who is informed: in treated municipalities, illegal mining is reduced by 11% in the disclosed locations and surrounding areas. However, when accounting for negative spillovers --- increases in illegal mining in areas not targeted by the information --- the net reduction is only 7%. These results illustrate the benefits of new technologies for building state capacity and reducing illegal activity.
dc.languageeng
dc.publisherUniversidad del Rosario
dc.publisherFacultad de Economía
dc.relationhttps://ideas.repec.org/p/col/000092/020078.html
dc.rightsinfo:eu-repo/semantics/openAccess
dc.rightsAbierto (Texto Completo)
dc.sourceinstname:Universidad del Rosario
dc.sourcereponame:Repositorio Institucional EdocUR
dc.subjectMinería ilegal en Colombia
dc.subjectTecnologías de monitoreo
dc.subjectActividades ilegales
dc.subjectPredicciones de machine learning
dc.subjectNuevas tecnologías para aumentar la capacidad estatal
dc.titleThe response of illegal mining to revealing its existence
dc.typeworkingPaper


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