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Proyección Agregada y Desagregada del PIB Chileno con Procedimientos Automatizados de Series de Tiempo

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  • Carlos Medel
  • Marcela Urrutia

Abstract

This paper compares the out-of-sample error of two forecasting methods for Chile’s GDP. The first method forecasts the aggregate GDP, while the second aggregates the forecasts of the supply-side components. As forecasting method we use the automatic model selection contained in the seasonal adjustment program X12-ARIMA version 0.2.10. Our sample includes the information contained in the first data release until 2009.I. For the whole sample, this paper finds no significant difference between both methods, according to tests commonly used in this literature. However, in periods of low GDP volatility the aggregate method performs better in terms of root mean squared error, while the disaggregate approach outperforms the aggregate one in periods of high GDP volatility.

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Bibliographic Info

Paper provided by Central Bank of Chile in its series Working Papers Central Bank of Chile with number 577.

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Date of creation: May 2010
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Handle: RePEc:chb:bcchwp:577

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  1. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-44, January.
  2. Clements,Michael & Hendry,David, 1998. "Forecasting Economic Time Series," Cambridge Books, Cambridge University Press, number 9780521634809, October.
  3. Marcus Cobb, 2009. "Forecasting Chilean Inflation From Disaggregate Components," Working Papers Central Bank of Chile 545, Central Bank of Chile.
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Cited by:
  1. Medel, Carlos A., 2012. "How informative are in-sample information criteria to forecasting? the case of Chilean GDP," MPRA Paper 35949, University Library of Munich, Germany.

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