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¿Akaike o Schwarz? ¿Cuál elegir para Predecir el PIB Chileno?


  • Carlos Medel


Schwarz. In this paper I evaluate the predictive ability of the Akaike and Schwarz information criteria using autoregressive integrated moving average models, with sectoral data of Chilean GDP. In terms of root mean square error, and after the estimation of more than a million models, the results indicate that —on average— the models based on the Schwarz criterion perform better than those selected with the Akaike, for the four horizons analyzed. Furthermore, the statistical significance of these differences indicates that the superiority in favor of the Schwarz criterion holds mainly at higher horizons.

Suggested Citation

  • Carlos Medel, 2012. "¿Akaike o Schwarz? ¿Cuál elegir para Predecir el PIB Chileno?," Working Papers Central Bank of Chile 658, Central Bank of Chile.
  • Handle: RePEc:chb:bcchwp:658

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    References listed on IDEAS

    1. Marcus Cobb, 2009. "Forecasting Chilean Inflation From Disaggregate Components," Working Papers Central Bank of Chile 545, Central Bank of Chile.
    2. Raffaella Giacomini & Halbert White, 2006. "Tests of Conditional Predictive Ability," Econometrica, Econometric Society, vol. 74(6), pages 1545-1578, November.
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    9. Carlos A. Medel, 2013. "How informative are in-sample information criteria to forecasting? The case of Chilean GDP," Latin American Journal of Economics-formerly Cuadernos de Economía, Instituto de Economía. Pontificia Universidad Católica de Chile., vol. 50(1), pages 133-161, May.
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    14. Kilian, Lutz, 2001. "Impulse Response Analysis in Vector Autoregressions with Unknown Lag Order," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 20(3), pages 161-179, April.
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    18. Pablo Pincheira Brown & Álvaro García Marín, 2009. "Forecasting Inflation in Chile With an Accurate Benchmark," Working Papers Central Bank of Chile 514, Central Bank of Chile.
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    Cited by:

    1. Carlos J. García & Pablo González M. & Antonio Moncado S., 2013. "Macroeconomic Forecasting in Chile: a Structural Bayesian Approach," Journal Economía Chilena (The Chilean Economy), Central Bank of Chile, vol. 16(1), pages 24-63, April.
    2. Carlos Garcia, 2012. "Impacto del Costo de la Energía Eléctrica en la Economía Chilena: Una Perspectiva Macroeconómica," ILADES-Georgetown University Working Papers inv281, Ilades-Georgetown University, Universidad Alberto Hurtado/School of Economics and Bussines.
    3. Stephanie Schmitt-Grohé & Martín Uribe, 2012. "Pegs, Downward Wage Rigidity, and Unemployment: the Role of Financial Structure," Working Papers Central Bank of Chile 672, Central Bank of Chile.

    More about this item

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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