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dc.contributor.authorFarhat, Dan
dc.identifier.citationFarhat, D. (2012). Artificial Neural Networks and Aggregate Consumption Patterns in New Zealand (Discussion Paper No. 1205). University of Otago. Retrieved from
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.publisherUniversity of Otagoen_NZ
dc.rightsCC0 1.0 Universal*
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
otago.schoolOtago Business School / Department of Economicsen_NZ
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CC0 1.0 Universal
Except where otherwise noted, this item's licence is described as CC0 1.0 Universal