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From Which Side to the Steady State of the Augmented Solow Model? The Role of Country-Specific Total Factor Productivity Growth Rates

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  • Hollanders, Hugo

    (MERIT)

Abstract

The human capital-augmented Solow model (Mankiw et al., 1992) has been criticized by Cho and Graham (1996) by stating that half of all countries converge to their steady state from above, i.e. from income levels above those obtained in their steady state. This is clearly at odds with the general idea that countries approach their steady state from a backward position. In this paper we will argue that this result is primarily due to the assumption of an identical exogenous rate of technological progress for all countries. Once different rates of technological progress are introduced into the model, the number of countries approaching their steady state from above is reduced to a number more in line with what the augmented Solow model would predict. However, for a sample consisting of 98 non-oil countries, the assumption of constant returns to scale has to be rejected. For the non-oil sample our analysis thus both supports and challenges the human capital-augmented Solow model. For a more limited sample consisting of 22 OECD countries, the results clearly support the augmented Solow model by both reducing the number of countries converging from above their steady state to zero and by accepting the assumption of constant returns to scale.

Suggested Citation

  • Hollanders, Hugo, 1999. "From Which Side to the Steady State of the Augmented Solow Model? The Role of Country-Specific Total Factor Productivity Growth Rates," Research Memorandum 003, Maastricht University, Maastricht Economic Research Institute on Innovation and Technology (MERIT).
  • Handle: RePEc:unm:umamer:1999003
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    References listed on IDEAS

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    1. E. S. Phelps, 1966. "Models of Technical Progress and the Golden Rule of Research," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 33(2), pages 133-145.
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    3. Barro, Robert J. & Lee, Jong-Wha, 1994. "Sources of economic growth," Carnegie-Rochester Conference Series on Public Policy, Elsevier, vol. 40(1), pages 1-46, June.
    4. Griliches, Zvi, 1980. "R & D and the Productivity Slowdown," American Economic Review, American Economic Association, vol. 70(2), pages 343-348, May.
    5. K. J. Arrow, 1971. "The Economic Implications of Learning by Doing," Palgrave Macmillan Books, in: F. H. Hahn (ed.), Readings in the Theory of Growth, chapter 11, pages 131-149, Palgrave Macmillan.
    6. Cho, Dongchul & Graham, Stephen, 1996. "The other side of conditional convergence," Economics Letters, Elsevier, vol. 50(2), pages 285-290, February.
    7. N. Gregory Mankiw & David Romer & David N. Weil, 1992. "A Contribution to the Empirics of Economic Growth," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 107(2), pages 407-437.
    8. Morrison, Catherine J, 1992. "Unraveling the Productivity Growth Slowdown in the United States, Canada and Japan: The Effects of Subequilibrium, Scale Economies and Markups," The Review of Economics and Statistics, MIT Press, vol. 74(3), pages 381-393, August.
    9. Jones, Charles I, 1995. "R&D-Based Models of Economic Growth," Journal of Political Economy, University of Chicago Press, vol. 103(4), pages 759-784, August.
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    Cited by:

    1. Ziesemer, Thomsas, 2003. "Multiple-steady-state growth models explaining twin-peak empirics?," Research Memorandum 033, Maastricht University, Maastricht Economic Research Institute on Innovation and Technology (MERIT).
    2. Weel, Bas ter, 1999. "Investing in Knowledge: On the Trade-Off between R&D, ICT, Skills and Migration," Research Memorandum 024, Maastricht University, Maastricht Economic Research Institute on Innovation and Technology (MERIT).

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