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Neural Network Models for Inflation Forecasting: An Appraisal

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Author Info
Ali Choudhary (University of Surrey and State Bank of Pakistan)
Adnan Haider (State Bank of Pakistan)

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Abstract

We assess the power of artificial neural network models as forecasting tools for monthly inflation rates for 28 OECD countries. For short out-of-sample forecasting horizons, we find that, on average, for 45% of the countries the ANN models were a superior predictor while the AR1 model performed better for 21%. Furthermore, arithmetic combinations of several ANN models can also serve as a credible tool for forecasting inflation.

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File URL: http://www.econ.surrey.ac.uk/discussion_papers/2008/DP08-08.pdf
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Publisher Info
Paper provided by Department of Economics, University of Surrey in its series Department of Economics Discussion Papers with number 0808.

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Length: 7 pages
Date of creation: Nov 2008
Date of revision:
Handle: RePEc:sur:surrec:0808

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Related research
Keywords: Artificial Neural Networks; Forecasting; Inflation;

Find related papers by JEL classification:
C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation and Testing
C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Other Model Applications
E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation

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References listed on IDEAS
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  1. William A. Brock & Cars H. Hommes, 1997. "A Rational Route to Randomness," Econometrica, Econometric Society, vol. 65(5), pages 1059-1096, September.
  2. Kuan, Chung-Ming & Liu, Tung, 1995. "Forecasting Exchange Rates Using Feedforward and Recurrent Neural Networks," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 10(4), pages 347-64, Oct.-Dec.. [Downloadable!] (restricted)
  3. Norman R. Swanson & Halbert White, 1995. "A Model Selection Approach to Real-Time Macroeconomic Forecasting Using Linear Models and Artificial Neural Networks," Macroeconomics 9503004, EconWPA. [Downloadable!]
    Other versions:
  4. McAdam, Peter & McNelis, Paul, 2005. "Forecasting inflation with thick models and neural networks," Economic Modelling, Elsevier, vol. 22(5), pages 848-867, September. [Downloadable!] (restricted)
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  5. Marcelo C. Medeiros & Timo Terasvirta & Gianluigi Rech, 2002. "Building Neural Network Models for Time Series: A Statistical Approach," Textos para discussão 461, Department of Economics PUC-Rio (Brazil). [Downloadable!]
    Other versions:
  6. James H. Stock & Mark W. Watson, 1998. "A Comparison of Linear and Nonlinear Univariate Models for Forecasting Macroeconomic Time Series," NBER Working Papers 6607, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
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This page was last updated on 2009-11-27.


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