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

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  • Carlos Medel

Abstract

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.

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  • 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

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    Cited by:

    1. Carlos Garcia, 2012. "Impacto del Costo de la Energía Eléctrica en la Economía Chilena: Una Perspectiva Macroeconómica," ILADES-UAH Working Papers inv281, Universidad Alberto Hurtado/School of Economics and Business.
    2. 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.
    3. Stephanie Schmitt-Grohé & Martín Uribe, 2014. "Pegs, Downward Wage Rigidity and Unemployment: The Role of Financial Structure," Central Banking, Analysis, and Economic Policies Book Series, in: Miguel Fuentes D. & Claudio E. Raddatz & Carmen M. Reinhart (ed.),Capital Mobility and Monetary Policy, edition 1, volume 18, chapter 3, pages 69-95, Central Bank of Chile.

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    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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