Evaluación del índice económico de Colombia para el período 2020 a 2022 con redes neuronales artificiales

Authors

DOI:

https://doi.org/10.17981/econcuc.42.1.2021.Econ.2

Keywords:

Neural networks, Macroeconomic indicators, Forecasts

Abstract

This article analyze some of the important macroeconomic indicators in Colombia,such as the Consumer Price Index (CPI), the Gross Domestic Product (GDP), the Representative Market Rate (TRM), the Oil Price (BRENT and WIT) and COLCAP. The objective is to study Colombia's economic.The analysis were obtained with artificial neural networks on Colombian indicators data for the period 2001 to 2018 of the National Administrative Department of Statistics (DANE) and Bloomberg. Concluding, for Colombia, the last two cases are highly favorable for the economy, because they will generate a greater influx of dollars, allowing positive effects on the domestic product and the consumer price index.

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Author Biographies

Valeria Alejandra Bustamante Zuleta, Sergio Arboleda University

She is a mathematician focused on data analysis and Big Data, graduated from Sergio Arboleda University. He has a Major in Economics and a Diploma in Big Data for Business.

Hermes Jackson Martinez Navas, Sergio Arboleda University

He is a mathematician from the National University of Colombia, Magister from the Universidad de los Andes, PhD. in mathematics. His review interests are in classification and machine learning method applications.

References

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Echavarría, J. J., Vásquez, D. & Villamizar, D. V. (2010). Impacto de las intervenciones cambiarias sobre el nivel y la volatilidad de la tasa de cambio de Colombia. Revista ESPE. Ensayos sobre Política Económica, 28(62), 12–69. https://doi.org/10.32468/Espe.6201

Hernández, J., Chumaceiro, A. & Ravina, R. (2017). Estado populista y gestión de políticas sociales. Revista Negotium, 38(13), 49–61. Available: https://www.redalyc.org/pdf/782/78253678004.pdf

Kilian, L. & Vigfusson, R. (2014). The Role of Oil Price Shocks in Causing U.S. Recessions. [International Finance Discussion Papers Number 1114]. Available: https://www.federalreserve.gov/pubs/ifdp/2014/1114/ifdp1114.pdf

Rankia Finance Colombia. (2012). ¿Qué es el COLCAP? [Online]. Available: https://www.rankia.co/blog/analisis-colcap/1578756-que-colcap

Rincón, H., Lozano, I. & Ramos, J. (2008). Rentas petroleras, subsidios e impuestos a los combustibles en Colombia: ¿Qué ocurrió durante el choque reciente de precios? Borradores de Economía, (541), 1–24. Available: https://www.banrep.gov.co/es/rentas-petroleras-subsidios-e-impuestos-combustibles-colombia-ocurriodurante-el-choque-reciente

Rodríguez, H. Y. (2011). Estudio del fenómeno de inflación importada vía precios del petróleo y su aplicación al caso colombiano mediante el uso de modelos VAR para el periodo 2000-2009. EG. Estudios Gerenciales, 27(121), 79–98. https://doi.org/10.1016/S0123-5923(11)70182-6

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Published

2020-10-03

How to Cite

Bustamante Zuleta, V. A., & Martinez Navas, H. J. (2020). Evaluación del índice económico de Colombia para el período 2020 a 2022 con redes neuronales artificiales. ECONÓMICAS CUC, 42(1), 25–33. https://doi.org/10.17981/econcuc.42.1.2021.Econ.2

Issue

Vol. 42 No. 1 (2021)

Section

Articles: Economy and Finance

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Copyright (c) 2020 ECONÓMICAS CUC

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