On Forecasting Recessions via Neural Nets

Yasuhiko Nakamura ()
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Yasuhiko Nakamura: Graduate School of Economics, Waseda University

Economics Bulletin, 2008, vol. 3, issue 13, 1-15

Abstract: In this research, we employ artificial neural networks in conjunction with selected economic and financial variables to forecast recessions in Canada, France, Germany, Italy, Japan, UK, and USA. We model the relationship between selected economic and financial (indicator) variables and recessions 1-10 periods in future out-of-sample recursively. The out-of-sample forecasts from neural network models show that among the 10 models constructed from 7 indicator variables and their combinations that we investigate, the stock price index (index) and spread between bank rates and risk free rates (BRTB) are most likely candidate variables for possible forecasts of recessions 1-10 periods ahead for most countries.

Keywords: business; cycles; neural; network; out-of-sample; forecasts; recession; real; GDP (search for similar items in EconPapers)
JEL-codes: C0 (search for similar items in EconPapers)
Date: 2008-03-04
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