Forecasting with many predictors: an empirical comparison

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Borradores de Economía; No. 643

Date published

2011-02-20

Date

2011-02-20

Authors

González-Molano, Eliana Rocío

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ISBN

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.

The opinions contained in this document are the sole responsibility of the author and do not commit Banco de la República or its Board of Directors.

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

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JEL Codes

C15 - Statistical Simulation Methods: General

Temática

Keywords

Keywords

Partial least squares , Principal components , Ridge regression

Citation

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https://repositorio.banrep.gov.co/handle/20.500.12134/5660
 https://hdl.handle.net/20.500.12134/5660
 https://ideas.repec.org/p/bdr/borrec/643.html
 https://doi.org/10.32468/be.643

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Esta obra está bajo licencia internacional Creative Commons Reconocimiento-NoComercial 4.0.

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