Forecasting with many predictors: an empirical comparison

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Borradores de Economía; No. 643
Date published
2011-02-20
Date of last update
2011-02-20
Author
González-Molano, Eliana Rocío
Document language
spa
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Las opiniones contenidas en el presente documento son responsabilidad exclusiva de los autores y no comprometen al Banco de la República ni a su Junta Directiva.
Abstract
Three methodologies of estimation of models with many predictors are implemented to forecast Colombian inflation. Two factor models, based on principal components, and partial least squares, as well as a Bayesian regression, known as Ridge regression are
JEL Codes
C15 - Statistical Simulation Methods: GeneralC11 - Bayesian Analysis: GeneralC52 - Model Evaluation, Validation, and SelectionC53 - Forecasting and Prediction Methods; Simulation Methods
Keywords
Partial least squares ; Principal components ; Ridge regression ;
URI
https://repositorio.banrep.gov.co/handle/20.500.12134/5660
https://hdl.handle.net/20.500.12134/5660
https://doi.org/10.32468/be.643
https://ideas.repec.org/p/bdr/borrec/643.html
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This work is licensed under a Creative Commons Reconocimiento-NoComercial 4.0.This document has been deposited by the author (s) under the following certificate of deposit