[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-124958-es":3,"doc-seo-124958-110":31,"detail-sidebar-cat-0-es-110":92},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":20,"is_deleted":4,"is_public":21,"is_downloadable":21,"audit_status":21,"page_count":22,"language":23,"language_code":24,"site_id":25,"html_lang":24,"table_of_contents":26,"faqs":27,"seo_title":28,"seo_description":14,"update_tm":29,"read_time":30},124958,2336474459895,"Aria","https://ap-avatar.wpscdn.com/avatar/22000baeef7a5ed0655?x-image-process=image/resize,m_fixed,w_180,h_180&k=1786071322749376916",41,"Investigación e Informes","IA en Mercados de Alimentos en Colombia - Usando Machine Learning para Enfrentar Crisis de Precios","Los choques de precios constituyen un problema persistente para agricultores en países en desarrollo, al amenazar su inversión y bienestar cuando, en el momento de la cosecha, enfrentan precios bajos y condiciones de pobreza. Las respuestas de gobiernos locales suelen recurrir a ayudas poco eficientes y distribuidas sin focalización. El estudio propone evaluar la viabilidad de una herramienta de machine learning de bajo costo que identifique municipios más probables afectados por un shock de precios para orientar la asistencia. Se emplean random forest y árboles de decisión, logrando hasta 79% de predicción y mejorando eficiencia a menor costo.","ECONÓMICAS  \n\n| Niño-Chaparro, Niño-Chaparro and Chaparro-Pesca / Económicas CUC, vol. 45 no. 1, pp. e24818 (Postprint versión) | CUC |\n| --- | --- |\n| AI in Colombian Food Markets: Using Machine Learning to Address |  |\n| Price Crisis |  |\n| IA en Mercados de Alimentos en Colombia: Usando Machine Learning |  |\n| para Enfrentar Crisis de Precios |  |\n\nDOI: [https://doi.org/10.17981/econcuc.Org.4818](https://doi.org/10.17981/econcuc.Org.4818)  \n[Scientific and Technological Research Article.](Scientific and Technological Research Article.)  \n[Date Received: 06/03/2023](Date Received: 06/03/2023)  \n[Date of Return: 19/25/10/2023](Date of Return: 19/25/10/2023)  \n[Date of Acceptance: 22/10/2023](Date of Acceptance: 22/10/2023)  \n[Date of publication: 27/10/2023](Date of publication: 27/10/2023)  \nGustavo Enrique Niño Chaparro   \nUniversity of Illinois Urbana – Champaign Urbana, Illinois (USA)  \n[genino2@illinois.edu](genino2@illinois.edu)  \nAlejandro Niño Chaparro   \nUniversidad Nacional de Colombia Bogotá, Cundinamarca (Colombia)  \n[aninoch@unal.edu.co](aninoch@unal.edu.co)  \nJorge Alberto Chaparro Pesca   \nUniversidad Internacional del Trópico Americano Yopal, Casanare (Colombia)  \n[chaparropesca@unitropico.edu.co](chaparropesca@unitropico.edu.co)   \nTo cite this Article:  \nNino Chaparro, G.E., Nino Chaparro, A., & Chaparro Pesca, J.A.(2023). AI in Colombian Food Markets: Using Machine Learning to Address Price Crisis. Económicas CUC, 45(1), e24818.  \n[https://doi.org/10.17981/econcuc.Org.4818](https://doi.org/10.17981/econcuc.Org.4818)  \n[JEL: C45](JEL: C45), Q11, N56 .  \nAbstract  \nPrice shocks have long been a challenge for farmers in developing countries, posing a substantial threat to their investments and livelihoods when they encounter low prices at the time of harvest , often pushing them towards poverty. Local governments' crisis responses often use inefficient, indiscriminate aid distribution. While local and regional governments can apply many tools to prevent sudden changes in crop prices, those tools tend to be expensive and difficult to implement in local communities. The principal objective of this study is to illustrate the feasibility of a cost-effective machine learning tool that predicts the most likely affected municipalities by a price shock, enabling local governments to effectively target assistance where it is needed. Two models were used in the article, a random forest and a decision tree algorithm. The findings suggest that, despite using a simple structure in both algorithms, the models were able to predict up to 79% of the municipalities affected by prices shocks. Furthermore, this article highlights that this relatively uncomplicated model structure can equip governments with accurate data, which could be employed in price crisis responses ata lower cost, thereby enhancing the efficiency of aid distribution. Keywords: Machine learning; crops price crises; policy targeting.  \nResumen  \nLos choques de precios han sido por largo tiempo uno de los principales problemas que los agricultores se enfrentan en paísesen desarrollo. Este problema crea un riesgo a su inversión y estilode vida cuando se encuentran con precios bajos al momento de la cosecha, llevándolos a situación de pobreza. Gobiernos regionales generalmente responden a las crisis de manera ineficiente, repartiendo ayudas indiscriminadamente. A pesar de que gobiernos locales pueden aplicar muchas herramientas paraprevenir los cambios drásticos en los precios agrícolas, esasherramientas tienden a ser muy costosas y difíciles de implementar. El principal objetivo de esta investigación es mostrar la posibilidad de usar una herramienta de machine learning que sea costo efectivo que predice las municipalidades más propensasa ser afectadas por un shock de precios, permitiendo a los gobiernos locales dirigir eficazmente la asistencia donde más se necesita. Dos modelos son usados en este articulo, random forest y arboles de decisión. Los hallazgos sugi","cbCaiiwW8lBrDefA","https://ap.wps.com/l/cbCaiiwW8lBrDefA","pdf",385809,4,1,12,"Spanish","es",110,"# Introduction\n## Price volatility y el problema de incertidumbre de precios\n## Soluciones tradicionales y limitaciones en países de ingresos bajos y medios\n## Enfoque propuesto con machine learning","[{\"question\":\"¿Cuál es el problema central que enfrentan los agricultores ante los choques de precios?\",\"answer\":\"La incertidumbre del precio futuro puede llevar a vender con precios inferiores a los esperados, afectando la rentabilidad y el bienestar, y empujando a los hogares hacia la pobreza.\"},{\"question\":\"¿Por qué las respuestas de los gobiernos suelen ser ineficientes?\",\"answer\":\"Porque tienden a repartir ayudas de forma indiscriminada, en lugar de focalizar donde el shock impacta con mayor probabilidad.\"},{\"question\":\"¿Qué modelos de machine learning se utilizan y qué resultados se reportan?\",\"answer\":\"Se usan random forest y árboles de decisión; los modelos predicen hasta 79% de los municipios afectados por los choques de precios.\"}]","IA en Mercados de Alimentos en Colombia - Usando Machine Learning para Enfrentar Crisis de Precios | PDF",1785895626,18,{"code":4,"msg":32,"data":33},"ok",{"site_id":25,"language":24,"slug":34,"title":13,"keywords":35,"description":14,"schema_data":36,"social_meta":87,"head_meta":89,"extra_data":91,"updated_unix":29},"ai-in-colombian-food-markets-using-machine-learning-to-address-price-crisis","",{"@graph":37,"@context":86},[38,54,69],{"@type":39,"itemListElement":40},"BreadcrumbList",[41,45,49,52],{"item":42,"name":43,"@type":44,"position":21},"https://docshare.wps.com","Home","ListItem",{"item":46,"name":47,"@type":44,"position":48},"https://docshare.wps.com/es/document/","Document",2,{"item":50,"name":12,"@type":44,"position":51},"https://docshare.wps.com/es/document/investigación-e-informes/",3,{"item":53,"name":13,"@type":44,"position":20},"https://docshare.wps.com/es/document/ai-in-colombian-food-markets-using-machine-learning-to-address-price-crisis/124958/",{"url":53,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":24,"description":14,"dateModified":62,"datePublished":63,"encodingFormat":61,"isAccessibleForFree":64,"interactionStatistic":65},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":42,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-16","2026-08-05",true,{"@type":66,"interactionType":67,"userInteractionCount":20},"InteractionCounter",{"@type":68},"ViewAction",{"@type":70,"mainEntity":71},"FAQPage",[72,78,82],{"name":73,"@type":74,"acceptedAnswer":75},"¿Cuál es el problema central que enfrentan los agricultores ante los choques de precios?","Question",{"text":76,"@type":77},"La incertidumbre del precio futuro puede llevar a vender con precios inferiores a los esperados, afectando la rentabilidad y el bienestar, y empujando a los hogares hacia la pobreza.","Answer",{"name":79,"@type":74,"acceptedAnswer":80},"¿Por qué las respuestas de los gobiernos suelen ser ineficientes?",{"text":81,"@type":77},"Porque tienden a repartir ayudas de forma indiscriminada, en lugar de focalizar donde el shock impacta con mayor probabilidad.",{"name":83,"@type":74,"acceptedAnswer":84},"¿Qué modelos de machine learning se utilizan y qué resultados se reportan?",{"text":85,"@type":77},"Se usan random forest y árboles de decisión; los modelos predicen hasta 79% de los municipios afectados por los choques de precios.","https://schema.org",{"og:url":53,"og:type":88,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":90,"canonical":53},"index,follow",{"doc_id":7,"site_id":25},{"code":4,"msg":5,"data":93},[94,99,103,107,111,113,117,121,125,129],{"id":95,"doc_module":4,"doc_module_name":47,"category_name":96,"show_sort_weight":97,"slug":98},39,"Cómic",60,"comic",{"id":100,"doc_module":4,"doc_module_name":47,"category_name":101,"show_sort_weight":97,"slug":102},43,"Estilo de Vida","lifestyle",{"id":104,"doc_module":4,"doc_module_name":47,"category_name":105,"show_sort_weight":97,"slug":106},38,"Examen","exam",{"id":108,"doc_module":4,"doc_module_name":47,"category_name":109,"show_sort_weight":97,"slug":110},44,"General","general",{"id":11,"doc_module":4,"doc_module_name":47,"category_name":12,"show_sort_weight":97,"slug":112},"research-report",{"id":114,"doc_module":4,"doc_module_name":47,"category_name":115,"show_sort_weight":97,"slug":116},37,"Literatura","literature",{"id":118,"doc_module":4,"doc_module_name":47,"category_name":119,"show_sort_weight":97,"slug":120},22,"Relatos y Novelas","story-novel",{"id":122,"doc_module":4,"doc_module_name":47,"category_name":123,"show_sort_weight":97,"slug":124},42,"Religión y Espiritualidad","religion-spirituality",{"id":126,"doc_module":4,"doc_module_name":47,"category_name":127,"show_sort_weight":97,"slug":128},40,"Salud y Atención Médica","healthcare",{"id":130,"doc_module":4,"doc_module_name":47,"category_name":131,"show_sort_weight":97,"slug":132},24,"Tecnología","technology"]