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Population Growth, Technological Adoption, and Economic Outcomes in the Information Era

Author

Listed:
  • Paul Beaudry

    (University of British Columbia)

  • David A. Green

    (University of British Columbia)

Abstract

In this paper we argue that population growth, through its interaction with recent technological and organizational developments, may account for many cross-country differences in economic outcomes observed among industrialized countries over the past 20 years. In particular, our model illustrates how a large decrease in the price of information technology can create a comparative advantage for high population growth economies to jump ahead in the adoption of computer- and skill-intensive modes of production. They do this as a means of countering their relative scarcity of physical capital. The predictions of the model are that, over the span of the information revolution, industrial countries with higher population growth rates will experience a more pronounced adoption of new technology, a better performance in terms of increased employment rates, a poorer performance in terms of wage growth for less skilled workers, a larger increase in the service sector, and a larger increase in the returns to education. We provide preliminary evidence in support of the theory based on an examination of broad wage movements, employment changes, and computer adoption patterns for a set of OECD countries. (Copyright: Elsevier)

Suggested Citation

  • Paul Beaudry & David A. Green, 2002. "Population Growth, Technological Adoption, and Economic Outcomes in the Information Era," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 5(4), pages 749-774, October.
  • Handle: RePEc:red:issued:v:5:y:2002:i:4:p:749-774
    DOI: 10.1006/redy.2002.0189
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    References listed on IDEAS

    as
    1. Joseph Zeira, 1998. "Workers, Machines, and Economic Growth," The Quarterly Journal of Economics, Oxford University Press, vol. 113(4), pages 1091-1117.
    2. Daron Acemoglu, 1999. "Changes in Unemployment and Wage Inequality: An Alternative Theory and Some Evidence," American Economic Review, American Economic Association, vol. 89(5), pages 1259-1278, December.
    3. Timothy F. Bresnahan & Erik Brynjolfsson & Lorin M. Hitt, 2002. "Information Technology, Workplace Organization, and the Demand for Skilled Labor: Firm-Level Evidence," The Quarterly Journal of Economics, Oxford University Press, vol. 117(1), pages 339-376.
    4. Paul Beaudry & David Green, 2001. "Population Growth, Technological Adoption and Economic Outcomes: A Theory of Cross-Country Differences for the Information Era," NBER Working Papers 8149, National Bureau of Economic Research, Inc.
    5. Peter Gottschalk & Timothy M. Smeeding, 1997. "Cross-National Comparisons of Earnings and Income Inequality," Journal of Economic Literature, American Economic Association, vol. 35(2), pages 633-687, June.
    6. Per Krusell & Lee E. Ohanian & JosÈ-Victor RÌos-Rull & Giovanni L. Violante, 2000. "Capital-Skill Complementarity and Inequality: A Macroeconomic Analysis," Econometrica, Econometric Society, vol. 68(5), pages 1029-1054, September.
    7. Francesco Caselli, 1999. "Technological Revolutions," American Economic Review, American Economic Association, vol. 89(1), pages 78-102, March.
    8. Claudia Goldin & Lawrence F. Katz, 1998. "The Origins of Technology-Skill Complementarity," The Quarterly Journal of Economics, Oxford University Press, vol. 113(3), pages 693-732.
    9. Paul Beaudry & David Green, 1998. "What is Driving US and Canadian Wages: Exogenous Technical Change or Endogenous Choice of Technique?," NBER Working Papers 6853, National Bureau of Economic Research, Inc.
    10. Paul Beaudry & David Green, 2000. "The Changing Structure of Wages in the US and Germany: What Explains the Differences?," NBER Working Papers 7697, National Bureau of Economic Research, Inc.
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    Citations

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    Cited by:

    1. Rimler, Judit, 2003. "Ecset vagy egér. Mesterségbeli tudás és magas szintű technika
      [Brush or mouse. Occupational capabilities and high technology]
      ," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(12), pages 1095-1114.
    2. repec:ids:ijsuse:v:10:y:2018:i:4:p:340-359 is not listed on IDEAS
    3. Michael Danquah & Enrique Moral-Benito & Bazoumana Ouattara, 2014. "TFP growth and its determinants: a model averaging approach," Empirical Economics, Springer, vol. 47(1), pages 227-251, August.
    4. Ho, Sin-Yu & Njindan Iyke, Bernard, 2018. "The Determinants of Economic Growth in Ghana: New Empirical Evidence," MPRA Paper 87123, University Library of Munich, Germany.
    5. Sin-Yu Ho, 2018. "Analysing the sources of growth in an emerging market economy: the Thailand experience," International Journal of Sustainable Economy, Inderscience Enterprises Ltd, vol. 10(4), pages 340-359.
    6. Paul Beaudry & Fabrice Collard & David A. Green, 2005. "Explaining Productivity Growth: The Role of Demographics," International Productivity Monitor, Centre for the Study of Living Standards, vol. 10, pages 45-58, Spring.

    More about this item

    Keywords

    population growth; information revolution; wage structure; human and physical capital accumulation;

    JEL classification:

    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes
    • J31 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Wage Level and Structure; Wage Differentials
    • J11 - Labor and Demographic Economics - - Demographic Economics - - - Demographic Trends, Macroeconomic Effects, and Forecasts

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