Colombian economic activity nowcasting: addressing nonlinearities and high dimensionality through machine-learning

Juan José Rincón Briceño ()
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Juan José Rincón Briceño: Universidad de los Andes

No 21388, Documentos CEDE from Universidad de los Andes, Facultad de Economía, CEDE

Abstract: Economic decisions are made with high uncertainty about the current and recent past economic activity, due to the limited and imperfect available information. Therefore the following question arises: how can the accuracy of Colombian economic activity nowcasting be enhanced compared to traditional forecasting methods? This paper demonstrates: (a) using a risk-averse customized loss function that accounts for the agent disutility and penalizes directional discrepancies provides a useful alternative for assessing model performance by ensuring more accurate nowcasts, maximizing both precision and economic relevance. And (b) during periods of abrupt shocks and high volatility, such as the COVID-19 (2020–2021) and the post COVID-19 subsequent years (2022-2023), machine learning models outperform traditional nowcasting models

Keywords: Colombian economic activity; nowcast; forecast; Random forests; LSTM. (search for similar items in EconPapers)
JEL-codes: C45 C52 C53 E32 E37 (search for similar items in EconPapers)
Pages: 63 pages
Date: 2025-06-06
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Persistent link: https://EconPapers.repec.org/RePEc:col:000089:021388

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