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Modelling Business Cycle Nonlinearity in Conditional Mean and Conditional Variance: Some International and Sectoral Evidence


David A. Peel


Lancaster University - Management School

Alan E.H. Speight


University of Wales, Swansea


Economica, Vol. 65, pp. 211-229, May 1998

Abstract:     
This paper tests for the presence of output mean and variance nonlinearities in international industrial production and UK and US sectoral production growth rates using ARMA-GQARCH, bilinear (BL) and joint BL-GQARCH models. ARMA-GQARCH models confirm the presence of asymmetric variance effects in Italian, UK and US industrial production and in all sectors other than US nondurables, and such that the conditional variance of output is increased following negative shocks. BL models are identified for German, Italian and US industrial production and US manufacturing, while BL-GQARCH models of joint non-linearity in both conditional mean and conditional variance are also found to hold for US industrial production and manufacturing. Moreover, with the exception of Italy, all BL and BL-QARCH models provide superior out-of-sample mean forecasts relative to forecasts from both naive models and models of the ARMA-GQARCH class.

Number of Pages in PDF File: 19

Accepted Paper Series


Date posted: October 13, 2003  

Suggested Citation

Peel, David A. and Speight, Alan E.H., Modelling Business Cycle Nonlinearity in Conditional Mean and Conditional Variance: Some International and Sectoral Evidence. Economica, Vol. 65, pp. 211-229, May 1998. Available at SSRN: http://ssrn.com/abstract=440023

Contact Information

David Alan Peel (Contact Author)
Lancaster University - Management School ( email )
Lancaster, LA1 4YX
United Kingdom
+44 (0)1524 593590 (Phone)
+44 (0)1524 594244 (Fax)
HOME PAGE: http://www.lancs.ac.uk/staff/peeld/
Alan E.H. Speight
University of Wales, Swansea ( email )
Singleton Park
Swansea, Wales SA2 8PP
United Kingdom
+44 1792 602111 (Phone)
Feedback to SSRN (Beta)


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