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Un Pronóstico no Paramétrico de la Inflación Colombiana


  • Norberto Rodríguez N.


  • Patricia Siado C.


This paper contains the results of a non parametric multi-step ahead forecast for the monthly Colombian inflation, using Mean conditional Kernel estimation over inflation changes, with no inclusion of exogenous variables. The results are compared with those from an ARIMA and a nonlinear STAR. The nonparametric forecast over perform the others two, as well as being the only, from the three, that statistically improved the naive forecast given by a random-walk model.

Suggested Citation

  • Norberto Rodríguez N. & Patricia Siado C., 2003. "Un Pronóstico no Paramétrico de la Inflación Colombiana," Borradores de Economia 248, Banco de la Republica de Colombia.
  • Handle: RePEc:bdr:borrec:248

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    References listed on IDEAS

    1. 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.
    2. 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, vol. 20(41-42), pages 143-214, June.
    3. Luis Fernando Melo & Martha Misas, 1998. "Análisis del comportamiento de la inflación trimestral en Colombia bajo cambios de régimen: Una evidencia a través del modelo "Switching" de Hamilton," REVISTA DE ECONOMÍA DEL ROSARIO, UNIVERSIDAD DEL ROSARIO, November.
    4. Hardle, Wolfgang & Linton, Oliver, 1986. "Applied nonparametric methods," Handbook of Econometrics,in: R. F. Engle & D. McFadden (ed.), Handbook of Econometrics, edition 1, volume 4, chapter 38, pages 2295-2339 Elsevier.
    5. 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.
    6. Pagan,Adrian & Ullah,Aman, 1999. "Nonparametric Econometrics," Cambridge Books, Cambridge University Press, number 9780521355643, March.
    7. 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.
    8. Siegfried Heiler, 1999. "A Survey on Nonparametric Time Series Analysis," Finance 9904005, EconWPA.
    9. 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.
    10. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
    11. Munir A. Jalil & Luis Fernando Melo, 2000. "Una Relación no Líneal entre Inflación y los Medios de Pago," Borradores de Economia 145, Banco de la Republica de Colombia.
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    Cited by:

    1. Luis Eduardo Arango & Luz Adriana Flórez, 2004. "Expectativas de actividad económica en Colombia y estructura a plazo: un poco más de evidencia," Ensayos sobre Política Económica, Banco de la Republica de Colombia, vol. 22(47), pages 126-160, Diciembre.
    2. 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.
    3. María Paola Figueroa & Javier Gómez Pineda, 2003. "Modelo Mensual de Canales de Transmisión," Borradores de Economia 267, Banco de la Republica de Colombia.
    4. Melo, Luis F. & Loaiza, Rubén A. & Villamizar-Villegas, Mauricio, 2016. "Bayesian combination for inflation forecasts: The effects of a prior based on central banks’ estimates," Economic Systems, Elsevier, vol. 40(3), pages 387-397.

    More about this item


    Nonparametric forecast; Kernel Estimation; Forecast Evaluation; Bandwidth Selection; Rolling Forecast.;

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation


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