Repositorio Institucional Universidad EAFIT :: Examinando por Materia "PREDICCIONES

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Pronóstico de la inflación con modelos MIDAS : evidencia para Colombia
(Universidad EAFIT, 2025-11-28) Hurtado Rivera, Isaac; Almonacid Hurtado, Paula María
Including variables sampled at different frequencies is an empirical challenge in economics. While macroeconomic series are typically released monthly or quarterly, financial series are available daily. A common practice is to aggregate or average the higher-frequency variables (e.g., monthly or daily data) in order to incorporate them into a single model. However, doing so can discard information and distort the temporal dynamics across variables. MIDAS (Mixed Data Sampling) regressions provide a solution to this problem, while also controlling parameter proliferation and yielding unbiased and efficient estimators. Using an application to monthly inflation in Colombia, this study empirically assesses whether high-frequency information improves forecasting performance and whether the use of MIDAS-type models is warranted. The results suggest that monthly inflation is a low-persistence process that can be adequately modeled with a restricted MIDAS specification, whereas U-MIDAS tends to overfit. In addition, forecasts become more accurate and less volatile when combined forecast methods are used.