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Jointness of Growth Determinants Author info | Abstract | Publisher info | Download info | Related research | Statistics Doppelhofer, G.
Weeks, M.
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Model uncertainty arises from uncertainty about correct economic theories, data issues and empirical specification problems. This paper investigates mutual dependence or jointness among variables in explaining the dependent variable. Jointness departs from univariate measures of variable importance, while addressing model uncertainty and allowing for generally unknown forms of dependence. Positive jointness implies that regressors are complements, representing distinct, but interacting economic factors. Negative jointness implies that explanatory variables are substitutes and act as proxies for a similar underlying mechanism. In a cross-country dataset, we show that jointness among 67 determinants of growth is important, ffecting inference and economic policy.
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Paper provided by Faculty of Economics, University of Cambridge in its series Cambridge Working Papers in Economics with number
0542.
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Date of creation: Sep 2005Date of revision:
Handle: RePEc:cam:camdae:0542Contact details of provider: Web page: http://www.econ.cam.ac.uk/index.htm
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Keywords: Model Uncertainty ; Dependencies among Regressors ; Jointness ; Determinants of Economic Growth ; Other versions of this item:
Find related papers by JEL classification: C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Bayesian Analysis C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation and Testing O20 - Economic Development, Technological Change, and Growth - - Development Planning and Policy - - - General O50 - Economic Development, Technological Change, and Growth - - Economywide Country Studies - - - General
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