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Un Pronóstico No Paramétrico De La Inflación Colombiana

  • Norberto Rodríguez


  • Patricia Siado

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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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
Date of revision:
Handle: RePEc:col:000094:003691
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  1. Martha Misas Arango & Enrique López Enciso & Pablo Querubín, 2002. "La Inflación En Colombia: Una Aproximación Desde Las Redes Neuronales," ENSAYOS SOBRE POLÍTICA ECONÓMICA, BANCO DE LA REPÚBLICA - ESPE, June.
  2. Luis Fernando Melo & Martha Misas, . "Análisis del Comportamiento de la Inflación Trimestral en Colombia Bajo Cambios de Régimen: Una Evidencia a Través del Modelo: "Switching" de Hamilton," Borradores de Economia 086, Banco de la Republica de Colombia.
  3. 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.
  4. Diebold, Francis X & Mariano, Roberto S, 1995. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(3), pages 253-63, July.
  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. HÄRDLE, Wolfgang, 1992. "Applied nonparametric methods," CORE Discussion Papers 1992003, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  7. Pagan,Adrian & Ullah,Aman, 1999. "Nonparametric Econometrics," Cambridge Books, Cambridge University Press, number 9780521586115.
  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. Oliver LINTON, . "Applied nonparametric methods," Statistic und Oekonometrie 9312, Humboldt Universitaet Berlin.
  10. Siegfried Heiler, 1999. "A Survey on Nonparametric Time Series Analysis," Finance 9904005, EconWPA.
  11. 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.
  12. 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.
  13. 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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