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Wealth Inequality

  • Edward B. Barbier
Chapter

Abstract

Up to now, this book has focused on how nature is used to create wealth. Here, we explore how that wealth is distributed, and its economic implications.

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Notes

  1. 1.
    This phrase comes from the title of the book by Claudia Goldin and Lawrence F. Katz (2008) The Race Between Education and Technology. Cambridge: Harvard University Press, as their work motivates the discussion of the overpricing of human capital in this chapter. In their book, Goldin and Katz provide substantial historical and contemporary evidence that this “race” is the main cause of the rise in the wage premium for skilled workers in the United States, and the subsequent growth in income inequality since 1980.Google Scholar
  2. However, it was Jan Tinbergen (1974) “Substitution of Graduate by other Labour”, Kyklos, 27: 217–226,CrossRefGoogle Scholar
  3. who first observed the possibility of this phenomenon occurring, and thus concluded his article by stating (p. 224) that “a reduction in income inequality… depends on the ‘race’ between demand for third-level manpower due to technological development and supply of it due to increased schooling… ” See also his book on this topic, Jan Tinbergen (1975) Income Distribution: Analysis and Policies. Amsterdam: North-Holland Publishing.Google Scholar
  4. 4.
    Goldin and Katz (2008), op. cit. are not the first to make this argument. Since Tinbergen (1974), op. cit., a large literature has emerged that has explored the “race between education and technology”; see Daron Acemoglu and David Autor (2012) “What Does Human Capital Do? A Review of Goldin and Katz’s The Race Between Education and Technology”, Journal of Economic Literature, 50: 426–463.CrossRefGoogle Scholar
  5. However, for a critique of what he calls “the economic textbook model” concerning the race between technology and education, see Anthony B. Atkinson (2008) The Changing Distribution of Earnings in OECD Countries (The Rodolfo De Benedetti Lecture Series). New York: Oxford University Press. Although Atkinson acknowledges that the “textbook model” can explain changes in the relative wage of skilled to unskilled workers, he argues that the model’s focus on rising demand and the lack of skilled workers is too simplistic to explain changes in income distribution, which is also influenced by different levels of skill and access to the capital market. Instead, Atkinson prefers a behavioral model that focuses on pay norms and superstars as key factors in rising income inequality.CrossRefGoogle Scholar
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  7. 12.
    Organization for Economic Cooperation and Development (OECD) (2011) An Overview of Growing Income Inequalities in OECD Countries: Main Findings. Divided We Stand: Why Inequality Keeps Rising. Paris: OECD, p. 31. The OECD member countries that were the focus of the study include: Australia, Austria, Belgium, Canada, Chile, Czech Republic, Denmark, Finland, France, Germany, Greece, Hungary, Ireland, Israel, Italy, Japan, Luxembourg, Mexico, the Netherlands, New Zealand, Norway, Portugal, Spain, Sweden, Turkey, the United Kingdom, and the United States.Google Scholar
  8. 13.
    See, for example, E. Berman and S. Machin (2000) “Skill-biased Technology Transfer Around the World”, Oxford Review of Economic Policy, 16(3): 12–22;CrossRefGoogle Scholar
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  12. 15.
    The link between overpricing of human capital, skill-biased technological change and rising wealth and income inequality is again indicated by evidence from the United States. For example, Steven N. Kaplan and Joshua Rauh (2013) “It’s the Market: The Broad-Based Rise in the Return to the Top Talent”, Journal of Economic Perspectives, 27(3): 35–56, conclude (p. 53): “Overall, we believe that our evidence remains more favorable toward the theories that root inequality in economic factors, especially skill-biased technological change, greater scale, and their interaction. Skill-biased technological change predicts that inequality will increase if technological progress raises the productivit y of skilled workers relative to unskilled workers and/or raises the price of goods made by skilled workers relative to those made by unskilled workers. For example, computers and advances in information technology may complement skilled labor and substitute for unskilled labor. This seems likely to provide part, or even much, of the explanation for the increase in pay of professional athletes (technology increases their marginal product by allowing them to reach more consumers), Wall Street investors (technology allows them to acquire information and trade large amounts more easily) and executives, as well as the surge in technology entrepreneurs in the Forbes 400. Globalization may have contributed to greater scale, but globalization cannot drive the increase in inequality at the top levels given the breadth of the phenomenon across the occupations we study.”CrossRefGoogle Scholar
  13. 17.
    Similarly, Thomas Piketty (2014) Capital in the Twenty-First Century. Cambridge, MA: Harvard University Press, p. 243 maintains that the mechanisms behind unequal distribution of wealth “include the supply of and demand for different skills, the state of the educational system, and the various rules and institutions that affect the operation of the labor market and the determination of wages.”Google Scholar
  14. 19.
    See Edward B. Barbier (2011) Scarcity and Frontiers: How Economies Have Developed Through Natural Resource Exploitation. Cambridge and New York: Cambridge University Press, especially chapters 8 and 9.Google Scholar
  15. 20.
    Ramón López (2010) “Global Economic Crises, Environmental-resource Scarcity and Wealth Concentration”, CEPAL Review, 102: 27–47.Google Scholar
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    See, for example, Facundo Alvaredo, et al. (2013) “The Top 1 Percent in International and Historical Perspective”, Journal of Economic Perspectives, 27: 3–20,CrossRefGoogle Scholar
  17. and Markus Stierli, Anthony Shorrocks, Jim Davies, Rodrigo Lluberas and Antonios Koutsoukis (2014) Global Wealth Report 2014. Zurich: Credit Suisse Research Institute. The ten countries with long-term wealth inequality data that are the focus of the latter report are Australia, Denmark, Finland, France, the Netherlands, Norway, Sweden, Switzerland, the United Kingdom and the United States. Alvaredo et al. (2013) also analyze long-term trends for Canada and Japan, but not Denmark, Finland, the Netherlands, Norway and Switzerland.Google Scholar
  18. 26.
    Piketty (2014), op. cit., pp. 193–194. See also Robin Greenwood and David Scharfstein (2013) “The Growth of Finance”, Journal of Economic Perspectives, 27: 3–28CrossRefGoogle Scholar
  19. and Thomas Philippon and Ariell Reshef (2013) “An International Look at the Growth of Modern Finance”, Journal of Economic Perspectives, 27(2): 73–96.CrossRefGoogle Scholar
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    Alvaredo et al. (2013), op. cit.; Josh Bivens and Lawrence Mishel (2013) “The Pay of Corporate Executives and Financial Professionals as Evidence of Rents in Top 1 Percent Incomes”, Journal of Economic Perspectives, 27: 57–78. The other source of income is commonly referred to as “earned income”, which is the income received in return to work.CrossRefGoogle Scholar
  22. 37.
    Adam Bonica, Nolan McCarty, Keith T. Poole and Howard Rosenthal (2013) “Why Hasn’t Democracy Slowed Rising Inequality?”, Journal of Economic Perspectives, 27(3): 103–124, p. 104.CrossRefGoogle Scholar
  23. See also Larry Bartels (2008) Unequal Democracy: The Political Economy of the New Gilded Age. Princeton, NJ: Princeton University Press;Google Scholar
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  25. 45.
    M. A. Fox, B. A. Connolly and T. D. Snyder (2005) “Youth Indicators 2005: Trends in the Well-Being of American Youth”, Washington, DC: US Department of Education, National Center for Education Statistics, cited in Koechlin (2013), op. cit., p. 16.Google Scholar
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    Martha J. Bailey and Susan M. Dynarski (2011) “Gainsand Gaps: Changing Inequality in US College Entry and Completion”, NBER Working Paper 17633, December 2011. Cambridge, MA: National Bureau of Economic Research.CrossRefGoogle Scholar
  27. 48.
    Tyler Cowen (2013) Average is Over: Powering America Beyond the Age of the Great Stagnation. New York: Dutton, p. 233. For example, Cowen predicts that soon the wealthy will comprise 10% and possibly 15% of the population in the United States, which will make them a powerful political influence, which they will use to oppose broad-based health and educational investment policies. Thus, he argues (p. 233): “Imagine that today’s millionaires comprised 10 percent of the citizenry; that make for an extraordinarily influential and politically potent group, much more so than the wealth today. Can you imagine that group funding the entire future by raising taxes on itself? I don’t see it.”Google Scholar
  28. 53.
    International Monetary Fund (IMF) (2009) World Economic Outlook April 2009: Crisis and Recovery. Washington, DC: IMF, p. 34Google Scholar
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    E. B. Barbier (2010) “Green Stimulus, Green Recovery and Global Imbalances”, World Economics, 11(2): 149–175;Google Scholar
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  34. 60.
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  38. 64.
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Copyright information

© Edward B. Barbier 2015

Authors and Affiliations

  • Edward B. Barbier
    • 1
  1. 1.University of WyomingUSA

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