Jointness of Growth Determinants
51 Pages Posted: 15 May 2007
Date Written: April 2007
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.
Keywords: model uncertainty, dependence among regressors, jointness, determinants of economic growth
JEL Classification: C11, C52, O20, O50
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