Clive W.J. Granger (), Timo Teräsvirta () and Andrew J. Patton ()
Additional contact information
Clive W.J. Granger: Department of Economics, University of California, San Diego, Postal: La Jolla, CA 92093-0508, USA
Timo Teräsvirta: Dept. of Economic Statistics, Stockholm School of Economics, Postal: Box 6501, SE-113 83 Stockholm, Sweden
Andrew J. Patton: Department of Economics, London School of Economics, Postal: London WC2A 2AE, UK
Abstract: The concept of common factors has in the econometrics literature been applied to conditional means or in some cases to conditional variances. In this paper we generalize this concept to bivariate distributions. This is done using the conditional bivariate copula as the statistical tool. The definition of common factors in distributions is illustrated by an empirical application to the income-consumption relationship, using monthly US time series. Evidence is found to support the claim that the true relationship between these variables is independent of the phase of the business cycle. The indicator representing the business cycle is thus a common factor in distributions of the type defined and discussed in the paper.
Keywords: bivariate time series; business cycles; conditional distribution; consumption-income relationship; copula; multivariate time-series model
12 pages, November 20, 2002
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