Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/26023
Authors: 
Doppelhofer, Gernot
Weeks, Melvyn
Year of Publication: 
2007
Series/Report no.: 
CESifo working paper 1978
Abstract: 
This paper introduces a new measure of dependence or jointness among explanatory variables. Jointness is based on the joint posterior distribution of variables over the model space, thereby taking model uncertainty into account. By looking beyond marginal measures of variable importance, jointness reveals generally unknown forms of dependence. Positive jointness implies that regressors are complements, representing distinct, but mutually reinforcing effects. Negative jointness implies that explanatory variables are substitutes and capture similar underlying effects. In a cross-country dataset we show that jointness among 67 determinants of growth is important, affecting inference and informing economic policy.
JEL: 
C11
C52
O20
O50
Document Type: 
Working Paper

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