Estimación de la variación del precio de los alimentos con modelos de frecuencias mixtas

Julián Alonso Cárdenas-Cárdenas (), Edgar Caicedo-García () and Eliana R. González Molano ()
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Julián Alonso Cárdenas-Cárdenas: Banco de la República de Colombia
Edgar Caicedo-García: Banco de la República de Colombia
Eliana R. González Molano: Banco de la República de Colombia

Borradores de Economia from Banco de la Republica de Colombia

Abstract: El comportamiento de los precios de los alimentos en Colombia ha sido un factor que inquieta a la autoridad monetaria por su volatilidad, alta ponderación en la canasta de IPC y en ocasiones recurrentes altos niveles debido a su reacción a choques de oferta como el clima, lo cual dificulta la tarea de estabilizar la inflación alrededor de la meta. De lo anterior, se desprende la necesidad de tener pronósticos insesgados y más oportunos de los cambios en el precio de los alimentos en el corto plazo. En este documento se desarrolla una metodología que aprovecha la información disponible con alta frecuencia de precios y abastecimiento de alimentos y permite combinar información observada en varias frecuencias para generar pronósticos alternativos de la variación de los precios de los alimentos y sus diferentes componentes. Los resultados encontrados indican que los modelos propuestos de frecuencias mixtas, producen mejores pronósticos que los tradicionales que utilizan solamente información de precios del Sistema de Información de Precios del Sector Agropecuario (SIPSA-DANE).. **** ABSTRACT: The behavior of food prices is a big issue for the monetary authority, due to the high volatility as well as the big weight it has in the CPI basket and because it reacts temporarily to supply shocks, such as climate conditions, what makes difficult the task of keeping total inflation around the target. Thus, it is needed to count with more accurate and timely forecasts of food inflation for the short run in order to guide the macroeconomic model for monetary policy and help the authority in the decision making process. For that purpose, in this document we apply a methodology that combines information of different frequencies (MIDAS) to produce forecasts for food inflation. In particular, information about food prices at a very disaggregate level and an indicator for food supply, which are available in a weekly basis, may help to generate a more accurate nowcast of total food inflation and its components: perishable and processed food. Compared to a naïve nowcast generated every week as the weighted average change of food prices taken by SIPSA, the results show an improvement in the nowcast, generated by the mixed frequency data models that includes not only high frequency variables as explanatory but also some other determinants of food price changes such as unemployment, climate conditions and international commodity prices. Thus, MIDAS models are a promising alternative to generate forecasts in the short run.

Keywords: Inflación de alimentos; nowcasting; modelos de frecuencias mixtas; pronósticos; clima; inflación objetivo; Food inflation; nowcasting; mixed frequency models; inflation targeting; climate conditions (search for similar items in EconPapers)
JEL-codes: C32 C51 C53 E31 E52 (search for similar items in EconPapers)
Pages: 22
Date: 2020-03
New Economics Papers: this item is included in nep-mac
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Persistent link: https://EconPapers.repec.org/RePEc:bdr:borrec:1109

DOI: 10.32468/be.1109

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