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Imposing parsimony in cross-country growth regressions

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  • Jarociński, Marek

Abstract

The number of variables related to long-run economic growth is large compared with the number of countries. Bayesian model averaging is often used to impose parsimony in the cross-country growth regression. The underlying prior is that many of the considered variables need to be excluded from the model. This paper, instead, advocates priors that impose parsimony without excluding variables. The resulting models fit the data better and are more robust to revisions of income data. The positive relationship between measures of trade openness and growth is much stronger than found in the literature. JEL Classification: C20, C52, O40, O47

Suggested Citation

  • Jarociński, Marek, 2010. "Imposing parsimony in cross-country growth regressions," Working Paper Series 1234, European Central Bank.
  • Handle: RePEc:ecb:ecbwps:20101234
    Note: 400529
    as

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    File URL: https://www.ecb.europa.eu//pub/pdf/scpwps/ecbwp1234.pdf
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    References listed on IDEAS

    as
    1. De Mol, Christine & Giannone, Domenico & Reichlin, Lucrezia, 2006. "Forecasting using a large number of predictors: is Bayesian regression a valid alternative to principal components?," Discussion Paper Series 1: Economic Studies 2006,32, Deutsche Bundesbank.
    2. De Mol, Christine & Giannone, Domenico & Reichlin, Lucrezia, 2008. "Forecasting using a large number of predictors: Is Bayesian shrinkage a valid alternative to principal components?," Journal of Econometrics, Elsevier, vol. 146(2), pages 318-328, October.
    3. Xavier Sala-I-Martin & Gernot Doppelhofer & Ronald I. Miller, 2004. "Determinants of Long-Term Growth: A Bayesian Averaging of Classical Estimates (BACE) Approach," American Economic Review, American Economic Association, vol. 94(4), pages 813-835, September.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Adaptive Ridge Regression; Bayesian model averaging; economic growth; measurement error;
    All these keywords.

    JEL classification:

    • C20 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - General
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • O40 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - General
    • O47 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - Empirical Studies of Economic Growth; Aggregate Productivity; Cross-Country Output Convergence

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