Neural Network Models for Inflation Forecasting: An Appraisal
AbstractWe 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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Bibliographic InfoPaper provided by School of Economics, University of Surrey in its series School of Economics Discussion Papers with number 0808.
Length: 7 pages
Date of creation: Nov 2008
Date of revision:
Artificial Neural Networks; Forecasting; Inflation;
Other versions of this item:
- M. Ali Choudhary & Adnan Haider, 2012. "Neural network models for inflation forecasting: an appraisal," Applied Economics, Taylor and Francis Journals, vol. 44(20), pages 2631-2635, July.
- C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
- 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
- E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
This paper has been announced in the following NEP Reports:
- NEP-ALL-2008-12-07 (All new papers)
- NEP-CBA-2008-12-07 (Central Banking)
- NEP-CMP-2008-12-07 (Computational Economics)
- NEP-ETS-2008-12-07 (Econometric Time Series)
- NEP-FOR-2008-12-07 (Forecasting)
- NEP-MAC-2008-12-07 (Macroeconomics)
- NEP-MON-2008-12-07 (Monetary Economics)
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
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