Neural Network Models for Inflation Forecasting: An Appraisal

Ali Choudhary and Adnan Haider

No 808, School of Economics Discussion Papers from School of Economics, University of Surrey

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.

Keywords: Artificial Neural Networks; Forecasting; Inflation (search for similar items in EconPapers)
JEL-codes: C51 C52 C53 E31 E37 (search for similar items in EconPapers)
Pages: 7 pages
Date: 2008-11
New Economics Papers: this item is included in nep-cba, nep-cmp, nep-ets, nep-for, nep-mac and nep-mon
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Citations: View citations in EconPapers (1)

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Related works:
Journal Article: Neural network models for inflation forecasting: an appraisal (2012)
Journal Article: Neural network models for inflation forecasting: an appraisal (2012)
Working Paper: Neural Network Models for Inflation Forecasting: An Appraisal (2011)
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Persistent link: https://EconPapers.repec.org/RePEc:sur:surrec:0808

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