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Variable Selection and Functional Form Uncertainty in Cross-Country Growth Regressions

Tim Salimans ()

No 11-012/4, Tinbergen Institute Discussion Papers from Tinbergen Institute

Abstract: Regression analyses of cross-country economic growth data are complicated by two main forms of model uncertainty: the uncertainty in selecting explanatory variables and the uncertainty in specifying the functional form of the regression function. Most discussions in the literature address these problems independently, yet a joint treatment is essential. We perform this joint treatment by extending the linear model to allow for multiple-regime parameter heterogeneity of the type suggested by new growth theory, while addressing the variable selection problem by means of Bayesian model averaging. Controlling for variable selection uncertainty, we confirm the evidence in favor of new growth theory presented in several earlier studies. However, controlling for functional form uncertainty, we find that the effects of many of the explanatory variables identified in the literature are not robust across countries and variable selections.

Keywords: growth regression; variable selection; model uncertainty; model averaging; semi-parametric Bayes; MCMC (search for similar items in EconPapers)
JEL-codes: C11 C14 C15 O40 O57 (search for similar items in EconPapers)
Date: 2011-01-18
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Related works:
Journal Article: Variable selection and functional form uncertainty in cross-country growth regressions (2012) Downloads
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