Author
Listed:
- Franky Juliano Galeano-Ramírez
- Nicolás Martínez-Cortés
- Hernán Dario Perdomo-Sánchez
- Marlon Salazar
Abstract
This paper develops a neural network model to capture nonlinear relationships between inflation and a broad set of macroeconomic variables that may provide insights into the factors behind deviations of inflation from its target in Colombia. The framework estimates implicit latent factors for distinct economic domains and uses them to construct a historical decomposition of the inflation gap. Our specification organizes the information set into five hemispheres covering short-run inflation expectations and inertia, long-run inflation expectations, real activity, the real exchange rate, and cost pressures from international commodity prices and domestic factors. The results suggest that real activity is not the only source of predictive information about inflationary pressures. Inflation expectations, inertia, and cost-related factors also account for a substantial share of observed inflation movements, with their relative contributions varying across inflationary episodes. Overall, the framework provides a flexible and interpretable empirical decomposition of inflation dynamics that can complement structural approaches. *** RESUMEN:Este artículo desarrolla un modelo de redes neuronales para capturar relaciones no lineales entre la inflación y un amplio conjunto de variables macroeconómicas asociadas con sus desviaciones respecto a la meta en Colombia. El modelo estima factores latentes para distintas dimensiones económicas y permite construir una descomposición histórica de la brecha de inflación. La información se organiza en cinco hemisferios: expectativas e inercia de corto plazo, expectativas de largo plazo, actividad económica, tasa de cambio real y presiones de costos. Los resultados sugieren que la actividad económica no es la única fuente de información predictiva sobre las presiones inflacionarias. Las expectativas, la inercia y los costos también tienen contribuciones relevantes, cuya importancia varía entre episodios inflacionarios. En conjunto, el modelo ofrece una descomposición flexible e interpretable de la dinámica inflacionaria que puede complementar los enfoques estructurales.
Suggested Citation
Franky Juliano Galeano-Ramírez & Nicolás Martínez-Cortés & Hernán Dario Perdomo-Sánchez & Marlon Salazar, 2026.
"Inflation Drivers in Colombia: A Hemisphere Neural Network Approach,"
Borradores de Economia
1370, Banco de la Republica de Colombia.
Handle:
RePEc:bdr:borrec:1370
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JEL classification:
- E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
- E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
- E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
- C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
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