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Determinants of Long-Term Growth: A Bayesian Averaging of Classical Estimates (Bace) Approach

  • Gernot Doppelhofer
  • Ronald I. Miller
  • Xavier Sala-i-Martin

This paper examines the robustness of explanatory variables in cross-country economic growth regressions. It employs a novel approach, Bayesian Averaging of Classical Estimates (BACE), which constructs estimates as a weighted average of OLS estimates for every possible combination of included variables. The weights applied to individual regressions are justified on Bayesian grounds in a way similar to the well-known Schwarz criterion. Of 32 explanatory variables we find 11 to be robustly partially correlated with long-term growth and another five variables to be marginally related. Of all the variables considered, the strongest evidence is for the initial level of real GDP per capita ... Ce document examine la robustesse des variables explicatives dans le cadre de régressions internationals pour la croissance économique. Les résultats sont obtenus en utilisant une nouvelle méthode « Bayesian Averaging of Classical Estimates » (BACE), qui construit les estimateurs comme la moyenne pondérée des estimateurs des MCO pour chacune des combinaisons de variables. Les poids appliqués aux regressions sont justifiés sur la base d’un critère bayesien dans une façon similaire au critère bien connu de Schwarz. Sur les 32 variables explicatives, nous trouvons onze variables robustes partiellement corrélés avec la croissance à long terme et cinq autres variables qui sont marginalement liées. De toutes les variables considérées, le résultat le plus probant est obtenu pour le niveau initial du PIB par habitant ...

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File URL: http://dx.doi.org/10.1787/834681262223
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Paper provided by OECD Publishing in its series OECD Economics Department Working Papers with number 266.

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Date of creation: 12 Oct 2000
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Handle: RePEc:oec:ecoaaa:266-en
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