Common Factors in Conditional Distributions
Clive W. J. Granger, Timo Teräsvirta, Andrew J. Patton
Abstract
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Clive W. J. Granger, Timo Teräsvirta, Andrew J. Patton
Abstract
Open-access reader
Dominant properties of various kinds can be defined for distributions including trends, strong seasonality, business cycles, and a persistent component. We say that in the joint distribution of X and Y, conditional on W has a common factor if W is a dominant component, but it does not appear in the copula, only in the conditional marginal distributions for X and Y. An application is discussed involving national income and consumption and a business cycle indicator. The results suggest that the marginals vary with the business cycle but not the copula.
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Dominant properties of various kinds can be defined for distributions including trends, strong seasonality, business cycles, and a persistent component. We say that in the joint distribution of X and Y, conditional on W has a common factor if W is a dominant component, but it does not appear in the copula, only in the conditional marginal distributions for X and Y. An application is discussed involving national income and consumption and a business cycle indicator. The results suggest that the marginals vary with the business cycle but not the copula.
Key concepts: Copula (linguistics), Bivariate analysis, Econometrics, Conditional probability distribution, Mathematics, Conditional variance, Business cycle, Statistics