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Implementación, Uso e Interpretación del "Fan Chart"

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  • Juan Manuel Julio

Abstract

El "Fan Chart" representa la función de probabilidades de los valores futuros de una variable, condicional a la información conocida en el presente. En contraste con la tradicional senda de pronósticos puntuales y sus bandas confidenciales simétricas, el Fan Chart presenta dos ventajas: Primero, describe completamente la densidad marginal de pronóstico en cada uno de los periodos del horizonte. Y segundo, su formulación permite que la densidad marginal de pronóstico sea asimétrica. Cuando esta densidad no es simétrica, la probabilidad (o riesgo) de que el valor futuro de la variable asuma valores por encima de la senda central de pronóstico es diferente a la de que asuma valores por debajo de dicha senda. Esta característica lo hace muy deseable para representar los riesgos de que se cumplan metas sobre el valor futuro de la variable en cuestión. En el caso del Informe de Inflación el "Fan Chart" cumple con dos objetivos: Primero, comunicar al público las previsiones de la autoridad monetaria sobre la evolución futura de la inflación con base en el "mejor conocimiento" actual de la economía, propósito relacionado con la transparencia del esquema de inflación objetivo y con la credibilidad de las políticas para alcanzar dichas metas. Y segundo, organizar la forma como la autoridad monetaria aborda el problema de pronosticar la inflación, lo cual tiene que ver con el desarrollo del Informe sobre Inflación y su distribución temática. En esta nota se describe en detalle la implementación actual del "Fan Chart" que utiliza el Banco de la Republica para su Informe sobre Inflación, se presenta un ejemplo que ilustra su adecuada utilización, se describe la manera como este se debe interpretar y se describe el uso de un programa que facilita su aplicación. Con esto, se persigue explicitar el uso e interpretación del "Fan Chart".

Suggested Citation

  • Juan Manuel Julio, 2005. "Implementación, Uso e Interpretación del "Fan Chart"," Borradores de Economia 346, Banco de la Republica de Colombia.
    • Handle: RePEc:bdr:borrec:346
    DOI: 10.32468/be.346
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    References listed on IDEAS

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    1. Javier Gómez & Juan Manuel Julio, 2001. "Transmission Mechanisms and Inflation Targeting: The Case of Colombia Disinflation," Borradores de Economia 168, Banco de la Republica de Colombia.
    2. Cogley, Timothy & Morozov, Sergei & Sargent, Thomas J., 2005. "Bayesian fan charts for U.K. inflation: Forecasting and sources of uncertainty in an evolving monetary system," Journal of Economic Dynamics and Control, Elsevier, vol. 29(11), pages 1893-1925, November.
    3. Marco Vega, 2004. "Policy Makers Priors and Inflation Density Forecasts," Econometrics 0403005, University Library of Munich, Germany.
    4. Franz Hamann Salcedo & Juan Manuel Julio & Paulina Restrepo & Alvaro Riascos, 2004. "Inflation Targeting in a Samll Open Economy: The Colombian Case," Borradores de Economia 308, Banco de la Republica de Colombia.
    5. Vega, Marco, 2003. "Reportando la distribución de la proyección de inflación," Revista Estudios Económicos, Banco Central de Reserva del Perú, issue 10.
    6. Javier Gómez & José Darío Uribe & Hernando Vargas, 2002. "The Implementation of Inflation Targeting in Colombia," Borradores de Economia 202, Banco de la Republica de Colombia.
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    Cited by:

    1. Johanna Inés Cárdenas Pinzón & Luis Eudoro Vallejo Zamudio, 2013. "Comportamiento de la inflación en Colombia 2002-2010 y régimen de metas de inflación," Apuntes del Cenes, Universidad Pedagógica y Tecnológica de Colombia.

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    JEL classification:

    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation

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