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Vector smooth transition regression models for US GDP and the composite index of leading indicators

Listed author(s):
  • Maximo Camacho

    (Universidad de Murcia, Spain)

In this paper, I extend to a multiple-equation context the linearity, model selection and model adequacy tests recently proposed for univariate smooth transition regression models. Using this result, I examine the nonlinear forecasting power of the Conference Board composite index of leading indicators to predict both output growth and the business-cycle phases of the US economy in real time. Copyright © 2004 John Wiley & Sons, Ltd.

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File URL: http://hdl.handle.net/10.1002/for.912
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Article provided by John Wiley & Sons, Ltd. in its journal Journal of Forecasting.

Volume (Year): 23 (2004)
Issue (Month): 3 ()
Pages: 173-196

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Handle: RePEc:jof:jforec:v:23:y:2004:i:3:p:173-196
DOI: 10.1002/for.912
Contact details of provider: Web page: http://www3.interscience.wiley.com/cgi-bin/jhome/2966

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