Neural Network Models for Inflation Forecasting: An Appraisal

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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Year of publication:	2008-11
Authors:	Choudhary, Ali ; Haider, Adnan
Institutions:	School of Economics, University of Surrey
Subject:	Artificial Neural Networks \| Forecasting \| Inflation

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Extent:	application/pdf
Series:	School of Economics Discussion Papers.
Type of publication:	Book / Working Paper
Language:	English
Notes:	Number 0808 7 pages
Classification:	C51 - Model Construction and Estimation ; C52 - Model Evaluation and Testing ; C53 - Forecasting and Other Model Applications ; E31 - Price Level; Inflation; Deflation ; E37 - Forecasting and Simulation
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10005748075