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
Julián Alonso Cárdenas-Cárdenas, Deicy Johana Cristiano-Botia, Eliana Rocío González-Molano, Carlos Alfonso Huertas-Campos
Luis E. Arango, Juan José Ospina-Tejeiro, Fernando Arias-Rodríguez, Oscar Iván Ávila-Montealegre, Jaime Andrés Collazos-Rodríguez, Diana M. Cortázar Gómez, Juan Pablo Cote-Barón, Julio Escobar-Potes, Aarón Levi Garavito-Acosta, Franky Juliano Galeano-Ramírez, Eliana Rocío González-Molano, Maria Camila Gomez Cardona, Anderson Grajales, David Camilo López-Valenzuela, Wilmer Martinez-Rivera, Nicolás Martínez-Cortés, Rocío Clara Alexandra Mora-Quiñones, Sara Naranjo-Saldarriaga, Antonio Orozco, Daniel Parra-Amado, Julián Pérez-Amaya, José Pulido, Karen L. Pulido-Mahecha, Carolina Ramírez-Rodríguez, Sergio Restrepo Ángel, José Vicente Romero-Chamorro, Nicol Valeria Rodríguez-Rodríguez, Norberto Rodríguez-Niño, Diego Hernán Rodríguez-Hernández, Carlos D. Rojas-Martínez, Johana Andrea Sanabria-Domínguez, Diego Vásquez-Escobar
Luis Armando Galvis-Aponte, Adriana Isabel Ortega-Arrieta, Adriana Marcela Rivera-Zárate
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.