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An Econometric Model of International Long-run Growth Dynamics

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  • Ulrich K. Müller
  • James H. Stock
  • Mark W. Watson

Abstract

We develop a Bayesian latent factor model of the joint evolution of GDP per capita for 113 countries over the 118 years from 1900 to 2017. We find considerable heterogeneity in rates of convergence, including rates for some countries that are so slow that they might not converge (or diverge) in century-long samples, and evidence of “convergence clubs” of countries. The joint Bayesian structure allows us to compute a joint predictive distribution for the output paths of these countries over the next 100 years. This predictive distribution can be used for simulations requiring projections into the deep future, such as estimating the costs of climate change. The model’s pooling of information across countries results in tighter prediction intervals than are achieved using univariate information sets. Still, even using more than a century of data on many countries, the 100-year growth paths exhibit very wide uncertainty.

Suggested Citation

  • Ulrich K. Müller & James H. Stock & Mark W. Watson, 2019. "An Econometric Model of International Long-run Growth Dynamics," NBER Working Papers 26593, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:26593
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    References listed on IDEAS

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    1. Robert J. Barro, 1991. "Economic Growth in a Cross Section of Countries," The Quarterly Journal of Economics, Oxford University Press, vol. 106(2), pages 407-443.
    2. Diebold, Francis X & Gunther, Todd A & Tay, Anthony S, 1998. "Evaluating Density Forecasts with Applications to Financial Risk Management," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 863-883, November.
    3. Durlauf, Steven N. & Quah, Danny T., 1999. "The new empirics of economic growth," Handbook of Macroeconomics, in: J. B. Taylor & M. Woodford (ed.), Handbook of Macroeconomics, edition 1, volume 1, chapter 4, pages 235-308, Elsevier.
    4. Robert J. Barro, 2012. "Convergence and Modernization Revisited," NBER Working Papers 18295, National Bureau of Economic Research, Inc.
    5. Steven N. Durlauf, 2009. "The Rise and Fall of Cross-Country Growth Regressions," History of Political Economy, Duke University Press, vol. 41(5), pages 315-333, Supplemen.
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    More about this item

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis
    • 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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