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Un Pronóstico No Paramétrico De La Inflación Colombiana

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  • Norberto Rodríguez

    ()

  • Patricia Siado

Abstract

En este trabajo se presentan los resultados de un ejercicio de pronóstico no paramétrico múltiples pasos adelante para la inflación colombiana mensual. En particular, se usa estimación Kernel para la media condicional de los cambios de la inflación dada su propia historia. Los resultados de pronóstico se comparan con un modelo ARIMA estacional y un modelo tipo STAR. Se encuentra que, excepto para el pronóstico un mes adelante, el pronóstico no parametrito mejora a las otras dos metodologías que le compiten; además, de entre las tres alternativas consideradas el no paramétrico es el único pronóstico que estadísticamente mejora al pronóstico que se hace con un modelo de caminata aleatoria.

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Bibliographic Info

Paper provided by BANCO DE LA REPÚBLICA in its series BORRADORES DE ECONOMIA with number 003691.

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Length: 49
Date of creation: 30 Jun 2003
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Handle: RePEc:col:000094:003691

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Keywords: Pronóstico No Paramétrico;

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  1. Wolfgang HÄRDLE & H. LÜTKEPOHL & R. CHEN, 1996. "A Review of Nonparametric Time Series Analysis," SFB 373 Discussion Papers 1996,48, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
  2. Wolfgang Hardle & Oliver Linton, 1994. "Applied Nonparametric Methods," Cowles Foundation Discussion Papers 1069, Cowles Foundation for Research in Economics, Yale University.
  3. Siegfried Heiler, 1999. "A Survey on Nonparametric Time Series Analysis," Finance 9904005, EconWPA.
  4. Martha Misas & Enrique López & Pablo Querubín, . "La Inflación en Colombia: Una Aproximación desde las Redes Neuronales," Borradores de Economia 199, Banco de la Republica de Colombia.
  5. Siegfried Heiler, 1999. "A Survey on Nonparametric Time Series Analysis," CoFE Discussion Paper 99-05, Center of Finance and Econometrics, University of Konstanz.
  6. repec:wop:humbsf:1996-53 is not listed on IDEAS
  7. Francis X. Diebold & Robert S. Mariano, 1994. "Comparing Predictive Accuracy," NBER Technical Working Papers 0169, National Bureau of Economic Research, Inc.
  8. Pham, Tuan D. & Tran, Lanh T., 1985. "Some mixing properties of time series models," Stochastic Processes and their Applications, Elsevier, vol. 19(2), pages 297-303, April.
  9. Munir A. Jalil & Luis Fernando Melo, . "Una Relación no Líneal entre Inflación y los Medios de Pago," Borradores de Economia 145, Banco de la Republica de Colombia.
  10. Johnston, Gordon J., 1982. "Probabilities of maximal deviations for nonparametric regression function estimates," Journal of Multivariate Analysis, Elsevier, vol. 12(3), pages 402-414, September.
  11. Wolfgang HÄRDLE & L. YANG, 1996. "Nonparametric Time Series Model Selection," SFB 373 Discussion Papers 1996,53, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
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Cited by:
  1. Juan Manuel Julio & Norberto Rodríguez & Héctor Manuel Zárate, 2005. "Estimating the COP Exchange Rate Volatility Smile and the Market Effect of Central Bank Interventions: A CHARN Approach," BORRADORES DE ECONOMIA 002605, BANCO DE LA REPÚBLICA.
  2. Javier Gómez Pineda & María Paola Figueroa, 2003. "Modelo Mensual de Canales de Transmisión," BORRADORES DE ECONOMIA 003240, BANCO DE LA REPÚBLICA.

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