A machine learning approach to find the determinants of peruvian ccocaine local price
Descripción del Articulo
The coca leaf has many uses in the Peruvian culture. Although there are legal usages, people employ coca for illicit business. The most infamous illegal use is cocaine production. The cocaine business is highly profitable, but it harms human health. Then, what are the determinants of cocaine price?...
| Autores: | , , |
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| Formato: | tesis de grado |
| Fecha de Publicación: | 2022 |
| Institución: | Universidad Continental |
| Repositorio: | CONTINENTAL-Institucional |
| Lenguaje: | inglés |
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| Enlace del recurso: | https://hdl.handle.net/20.500.12394/12266 https://doi.org/10.5267/j.ijdns.2021.11.009 |
| Nivel de acceso: | acceso abierto |
| Materia: | Cultivos ilegales de coca https://purl.org/pe-repo/ocde/ford#2.02.04 |
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A machine learning approach to find the determinants of peruvian ccocaine local price |
| title |
A machine learning approach to find the determinants of peruvian ccocaine local price |
| spellingShingle |
A machine learning approach to find the determinants of peruvian ccocaine local price Huaman Ivala, Yulisa Margoth Cultivos ilegales de coca https://purl.org/pe-repo/ocde/ford#2.02.04 |
| title_short |
A machine learning approach to find the determinants of peruvian ccocaine local price |
| title_full |
A machine learning approach to find the determinants of peruvian ccocaine local price |
| title_fullStr |
A machine learning approach to find the determinants of peruvian ccocaine local price |
| title_full_unstemmed |
A machine learning approach to find the determinants of peruvian ccocaine local price |
| title_sort |
A machine learning approach to find the determinants of peruvian ccocaine local price |
| author |
Huaman Ivala, Yulisa Margoth |
| author_facet |
Huaman Ivala, Yulisa Margoth Flores Guillen, Alexander Perez Evangelista, Elizabeth Yadhira |
| author_role |
author |
| author2 |
Flores Guillen, Alexander Perez Evangelista, Elizabeth Yadhira |
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author author |
| dc.contributor.advisor.fl_str_mv |
Ruiz Parejas, Rubén Ángel |
| dc.contributor.author.fl_str_mv |
Huaman Ivala, Yulisa Margoth Flores Guillen, Alexander Perez Evangelista, Elizabeth Yadhira |
| dc.subject.es_ES.fl_str_mv |
Cultivos ilegales de coca |
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Cultivos ilegales de coca https://purl.org/pe-repo/ocde/ford#2.02.04 |
| dc.subject.ocde.es_ES.fl_str_mv |
https://purl.org/pe-repo/ocde/ford#2.02.04 |
| description |
The coca leaf has many uses in the Peruvian culture. Although there are legal usages, people employ coca for illicit business. The most infamous illegal use is cocaine production. The cocaine business is highly profitable, but it harms human health. Then, what are the determinants of cocaine price? The current analysis aims to get the variables with the capability to explain the cocaine prices in Peru. The period analyzed is 2003-2019. The study gathered variables from DEVIDA and UNDOC databases. The Lasso technique selected the variables with the best capability to predict cocaine price. Those variables were: ENACO acquisition, coca seizures, and coca crops. OLS, VAR, and Granger analyses employed those variables to analyze the relationship between them. According to the OLS analysis, both ENACO acquisition and coca crops had adverse effects on cocaine prices, while coca seizures were positively related to the cocaine price. VAR analysis showed that only ENACO acquisition had a short-term relationship with the dependent variable. Moreover, it showed that the whole set of variables influenced the dependent variable. The Granger analysis proved that there was a cause-effect relationship between ENACO acquisition and cocaine price. Hence, the ENACO purchases expansion can rest the attractiveness of illegal groups to farmers. However, low- ering cocaine prices might attract more users. Therefore, educational activities are also required. |
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2022 |
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2023-01-13T16:54:12Z |
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2023-01-13T16:54:12Z |
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2022 |
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Huaman, Y. Flores, A. y Perez, E. (2022). A machine learning approach to find the determinants of peruvian ccocaine local price. Tesis para optar el título profesional de Ingeniero Industrial . Escuela Académica Profesional de Ingeniería. Universidad Continental. Huancayo. Perú. |
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https://hdl.handle.net/20.500.12394/12266 |
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https://doi.org/10.5267/j.ijdns.2021.11.009 |
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Huaman, Y. Flores, A. y Perez, E. (2022). A machine learning approach to find the determinants of peruvian ccocaine local price. Tesis para optar el título profesional de Ingeniero Industrial . Escuela Académica Profesional de Ingeniería. Universidad Continental. Huancayo. Perú. |
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Ruiz Parejas, Rubén ÁngelHuaman Ivala, Yulisa MargothFlores Guillen, AlexanderPerez Evangelista, Elizabeth Yadhira2023-01-13T16:54:12Z2023-01-13T16:54:12Z2022Huaman, Y. Flores, A. y Perez, E. (2022). A machine learning approach to find the determinants of peruvian ccocaine local price. Tesis para optar el título profesional de Ingeniero Industrial . Escuela Académica Profesional de Ingeniería. Universidad Continental. Huancayo. Perú.https://hdl.handle.net/20.500.12394/12266https://doi.org/10.5267/j.ijdns.2021.11.009The coca leaf has many uses in the Peruvian culture. Although there are legal usages, people employ coca for illicit business. The most infamous illegal use is cocaine production. The cocaine business is highly profitable, but it harms human health. Then, what are the determinants of cocaine price? The current analysis aims to get the variables with the capability to explain the cocaine prices in Peru. The period analyzed is 2003-2019. The study gathered variables from DEVIDA and UNDOC databases. The Lasso technique selected the variables with the best capability to predict cocaine price. Those variables were: ENACO acquisition, coca seizures, and coca crops. OLS, VAR, and Granger analyses employed those variables to analyze the relationship between them. According to the OLS analysis, both ENACO acquisition and coca crops had adverse effects on cocaine prices, while coca seizures were positively related to the cocaine price. VAR analysis showed that only ENACO acquisition had a short-term relationship with the dependent variable. Moreover, it showed that the whole set of variables influenced the dependent variable. The Granger analysis proved that there was a cause-effect relationship between ENACO acquisition and cocaine price. Hence, the ENACO purchases expansion can rest the attractiveness of illegal groups to farmers. However, low- ering cocaine prices might attract more users. Therefore, educational activities are also required.application/pdfp. 1-12engUniversidad ContinentalPEhttps://bit.ly/3wb9u0QSUNEDUinfo:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by/4.0/Attribution 4.0 International (CC BY 4.0)Acceso abiertoUniversidad ContinentalRepositorio Institucional - Continentalreponame:CONTINENTAL-Institucionalinstname:Universidad Continentalinstacron:CONTINENTALCultivos ilegales de cocahttps://purl.org/pe-repo/ocde/ford#2.02.04A machine learning approach to find the determinants of peruvian ccocaine local priceinfo:eu-repo/semantics/bachelorThesisinfo:eu-repo/semantics/publishedVersionIngeniero de Sistemas e InformáticaUniversidad Continental. 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Nota importante:
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La información contenida en este registro es de entera responsabilidad de la institución que gestiona el repositorio institucional donde esta contenido este documento o set de datos. El CONCYTEC no se hace responsable por los contenidos (publicaciones y/o datos) accesibles a través del Repositorio Nacional Digital de Ciencia, Tecnología e Innovación de Acceso Abierto (ALICIA).