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We have just averaged over two trillion cross-country growth regressions

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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 distributed among many models, suggesting the superiority of BMA over any single model. Out-of-sample predictive results support that 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, the variables we identify as most useful for growth regression differ substantially from Sala-i-Martin's results.

Suggested Citation

  • Eduardo Ley & Mark F J Steel, 1999. "We have just averaged over two trillion cross-country growth regressions," ESE Discussion Papers 43, Edinburgh School of Economics, University of Edinburgh.
  • Handle: RePEc:edn:esedps:43
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    File URL: http://www.econ.ed.ac.uk/papers/id43_esedps.pdf
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    Cited by:

    1. Stéphane Straub, 2000. "Empirical Determinants of Good Institutions: Do We Know Anything?," IDB Publications (Working Papers) 6085, Inter-American Development Bank.

    More about this item

    Keywords

    Bayesian model averaging; choice of regressors; economic growth; Markov chain; Monte Carlo prediction;

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • O49 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - Other

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