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Model uncertainty in cross-country growth regressions

Paper:ewp-em/0110002
From:    
Date: Sat, 6 Oct 2001 15:31:04 -0500

Title: Model uncertainty in cross-country growth regressions
Author: Carmen Fernandez (University of Saint Andrews) Eduardo Ley (IMF Institute) Mark Steel (University of Kent at Canterbury)
Contact:
Comments: Type of Document - Tex; prepared on MacOS, TeXtures; to print on any printer; figures: included. Forthcoming in the Journal of Applied Econometrics
Keywords: Bayesian Model Averaging, Choice of Regressors, Economic Growth, Markov chain Monte Carlo, Prediction
JEL: O49, C11, C52
EWPA-references:
Report-no: ELEY-004

Abstract:

We investigate the issue of model uncertainty in cross-country growth regressions using Bayesian Model Averaging (BMA). We find that the posterior probability is very spread among many models suggesting the superiority of BMA over choosing any single model. Out-of-sample predictive results support this claim. In contrast with Levine and Renelt (1992), our results broadly support the more "optimistic'' conclusion of Sala-i-Martin (1997b), namely that some variables are important regressors for explaining cross-country growth patterns. However, care should be taken in the methodology employed. The approach proposed here is firmly grounded in statistical theory and immediately leads to posterior and predictive inference.

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