Measuring the Unmeasurable: Unraveling the complexities of real-time output gap estimation

Borradores de Economia
Number: 
1284
DOI: 
https://doi.org/10.32468/be.1284
Published: 
Authors:
Karen L. Pulido-Mahechaa,
Sergio Restrepo Ángela,
Franky Juliano Galeano-Ramíreza
Classification JEL: 
E2, E3, E6
Keywords: 
output gaps, real-time estimation, Business cycles
Download document

The most recent

Revista Ensayos Sobre Política Económica - Exploring gender gaps in Colombia
María Teresa Ramírez-Giraldo, Karina Acosta, Olga Lucia Acosta Navarro, Lucia Arango-Lozano, Fernando Arias-Rodríguez, Oscar Iván Ávila-Montealegre, Oscar Reinaldo Becerra Camargo, Leonardo Bonilla-Mejía, Grey Yuliet Ceballos-Garcia, Luz Adriana Flórez, Juan Miguel Gallego-Acevedo, Luis Armando Galvis-Aponte, Luis M. García-Pulgarín, Andrés Felipe García-Suaza, Anderson Grajales, Daniela Gualtero-Briceño, Didier Hermida-Giraldo, Ana María Iregui-Bohórquez, Juliana Jaramillo-Echeverri, Karen Laguna-Ballesteros, Francisco Javier Lasso-Valderrama, Daniel Márquez, Carlos Alberto Medina-Durango, Ligia Alba Melo-Becerra, María Fernanda Meneses-González, Juan José Ospina-Tejeiro, Andrea Sofía Otero-Cortés, Daniel Parra-Amado, Juana Piñeros-Ruiz, Christian Manuel Posso-Suárez, Natalia Ramírez-Bustamante, Mario Andrés Ramos-Veloza, Jorge Leonardo Rodríguez-Arenas, Alejandro Sarasti-Sierra, Bibiana Taboada-Arango, Ana María Tribín-Uribe, Juanita Villaveces
The System of National Accounts by Institutional Sector: A methodological perspective on the colombian case
Carlos David Ardila-Dueñas, Joel Santiago Castellanos-Caballero, Carlos David Murcia-Bustos
A decade of changes in monetary poverty in Colombia: local responses to aggregate shocks
Karina Acosta, Jesus Saldaña

Abstract

This paper evaluates seven output gap models for real-time estimates, based on three criteria: stability of estimations on new observations, data revisions and/or methodological changes; inflation forecasting accuracy; and potential output response to structural economic shocks. Results confirm no single model outperforms across all criteria. Structural VARs exhibit superior inflation forecasts but show high instability, while semi-structural models produce more theoretically consistent potential output responses. To overcome this trade-off, we propose a novel clustering approach to pool models based on their real-time performance, yielding improved estimates. Our findings highlight the value of this method for enhancing real-time output gap measurement and informing monetary policy decisions.