Granger, Clive W.J. () (Department of Economics, University of California, San Diego) Teräsvirta, Timo () (Dept. of Economic Statistics, Stockholm School of Economics) Patton, Andrew J. () (Department of Economics, London School of Economics)
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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.
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Length: 12 pages Date of creation: 20 Nov 2002 Date of revision: Publication status: Published in Journal of Econometrics, 2006, pages 43-57. Handle: RePEc:hhs:hastef:0515
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References listed on IDEAS Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
Hansen, Bruce E, 1994.
"Autoregressive Conditional Density Estimation,"
International Economic Review,
Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 35(3), pages 705-30, August.
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