Artificial Neural Networks and Aggregate Consumption Patterns in New Zealand

Dan Farhat ()
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Dan Farhat: Department of Economics, University of Otago, New Zealand

No 1205, Working Papers from University of Otago, Department of Economics

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.

Keywords: International Migration; International Agreements; Regional Labour Markets (search for similar items in EconPapers)
JEL-codes: F22 F55 R23 (search for similar items in EconPapers)
Pages: 26 pages
Date: 2012-12, Revised 2012-12
New Economics Papers: this item is included in nep-cmp, nep-for, nep-ict and nep-ore
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Citations: View citations in EconPapers (1)

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http://www.otago.ac.nz/economics/research/otago076656.pdf First version, 2012 (application/pdf)

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Persistent link: https://EconPapers.repec.org/RePEc:otg:wpaper:1205

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