Artificial Neural Networks and Aggregate Consumption Patterns in New Zealand
Farhat, Dan

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Farhat, 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/10523/2544
Permanent link to OUR Archive version:
http://hdl.handle.net/10523/2544
Abstract:
This 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.
Date:
2012-11
Publisher:
University of Otago
Series number:
1205
Keywords:
Artificial neural networks, forecasting, aggregate consumption, social simulation. JEL codes: C45, E17, E27
Research Type:
Discussion Paper
Languages:
English
Collections
- Economics [316]
- Discussion Paper [439]
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