Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/195414 
Year of Publication: 
2017
Citation: 
[Journal:] Revista de Métodos Cuantitativos para la Economía y la Empresa [ISSN:] 1886-516X [Volume:] 23 [Publisher:] Universidad Pablo de Olavide [Place:] Sevilla [Year:] 2017 [Pages:] 98-118
Publisher: 
Universidad Pablo de Olavide, Sevilla
Abstract (Translated): 
The hierarchical structure of the Colombian Consumer Price Index (CPI) makes possible to calculate inflation as a linear combination of its subcomponents. We use SARIMA models to forecast each component of CPI and construct an forecast of inflation using a lineal combination of the forecasts of these components, i.e. a "bottom to top" approach. In this paper, we asses the out-of-sample performance of the one-step ahead forecast of 12 "bottom to top" methodologies. These methods are compared with an aggregate forecast using a SARIMA model. Our results show that a "bottom to top" method to forecast inflation outperforms an aggregate approach for the case of monthly inflation in Colombia.
Subjects: 
CPI
inflation
forecasts
"bottom to top"
Colombia
JEL: 
C32
C53
E31
E37
Creative Commons License: 
cc-by-sa Logo
Document Type: 
Article

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