Borradores de Economia
Number:
1256
Published:
Jonathan Muñoz-Martíneza, 
Classification JEL:
E31, E37, E52
Keywords:
Inflation perceptions, Twitter, Real-time data, Central banks
The most recent
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
Wilmer Martinez-Rivera, Manuel Darío Hernández-Bejarano
Carlos David Ardila-Dueñas, Joel Santiago Castellanos-Caballero, Carlos David Murcia-Bustos
Abstract
This study follows a novel approach proposed by Angelico et al. (2022) using Twitter to measure inflation perception in Colombia in real time. By applying machine learning techniques, we implement two real-time indicators of inflation perception and show that both exhibit a dynamic similar to inflation and inflation expectations for the sample period January 2015 to March 2023. Our interpretation of these results suggests that our indicators are closely linked to the underlying factors that drive inflation perception. Overall, this approach provides a valuable instrument for gauging public sentiment towards inflation and complements the traditional inflation expectations measures used in the inflation–targeting framework.