McAdam, Peter and McNelis, P. (2005) Forecasting Inflation with Thick Models and Neural Networks. Economic Modeling, 22 (5). pp. 848-867. ISSN 0264-9993.
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Abstract
This paper applies linear and neural network-based "thick" models for forecasting inflation based on Phillips-curve formulations in the USA, Japan and the euro area. Thick models represent "trimmed mean" forecasts from several neural network models. They outperform the best performing linear models for "real-time" and "bootstrap" forecasts for service indices for the euro area, and do well, sometimes better, for the more general consumer and producer price indices across a variety of countries. (c) 2005 Elsevier B.V All rights reserved
| Item Type: | Article |
|---|---|
| Subjects: | H Social Sciences |
| Divisions: | Faculties > Social Sciences > School of Economics |
| Depositing User: | Francis Green |
| Date Deposited: | 08 Oct 2008 17:31 |
| Last Modified: | 14 Jan 2010 14:35 |
| Resource URI: | http://kar.kent.ac.uk/id/eprint/9426 (The current URI for this page, for reference purposes) |
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