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dc.contributor.authorFarhat, Dan
dc.date.available2012-11-05T01:19:29Z
dc.date.copyright2012-11
dc.identifier.citationFarhat, D. (2012). Artificial Neural Networks and Aggregate Consumption Patterns in New Zealand (Discussion Paper No. 1205). University of Otago. Retrieved from http://hdl.handle.net/10523/2544en
dc.identifier.urihttp://hdl.handle.net/10523/2544
dc.description.abstractThis study uses artificial neural networks (ANNs) to reproduce aggregate per-capita consumption patterns for the New Zealand economy. Results suggest that non-linear ANNs can outperform a linear econometric model at out-of-sample forecasting. The best ANN at matching in-sample data, however, is rarely the best predictor. To improve the accuracy of ANNs using only in-sample information, methods for combining heterogeneous ANN forecasts are explored. The frequency that an individual ANN is a top performer during in-sample training plays a beneficial role in consistently producing accurate out-of-sample patterns. Possible avenues for incorporating ANN structures into social simulation models of consumption are discussed.en_NZ
dc.format.mimetypeapplication/pdf
dc.language.isoenen_NZ
dc.publisherUniversity of Otagoen_NZ
dc.rightsCC0 1.0 Universal*
dc.rights.urihttp://creativecommons.org/publicdomain/zero/1.0/*
dc.subjectArtificial neural networks, forecasting, aggregate consumption, social simulation. JEL codes: C45, E17, E27en_NZ
dc.titleArtificial Neural Networks and Aggregate Consumption Patterns in New Zealanden_NZ
dc.typeDiscussion Paperen_NZ
dc.date.updated2012-11-05T00:59:35Z
otago.schoolOtago Business School / Department of Economicsen_NZ
otago.openaccessOpenen_NZ
otago.relation.number1205en_NZ
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CC0 1.0 Universal
Except where otherwise noted, this item's licence is described as CC0 1.0 Universal