Work and consumption in an era of unbalanced technological advance

Abstract

Keynes’s “Grandchildren” essay famously predicted both a rapid increase in productivity and a sharp shrinkage of the workweek – to 15 h – over the century from 1930. Keynes was right (so far) about output per capita, but wrong about the workweek. The key reason is that he failed to allow for changing distribution. With widening inequality, median income (and therefore the income of most families) has risen, and is now rising, much more slowly than he anticipated. The failure of the workweek to shrink as he predicted follows. Other factors, including habit formation, socially induced consumption preferences, and network effects are part of the story too. Combining the analysis of Keynes, Meade and Galbraith suggests a way forward for economic policy under the prevailing circumstances.

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Notes

  1. 1.

    Keynes (1930). Keynes apparently wrote the paper two years earlier, before the onset of what became the Great Depression.

  2. 2.

    The first systematic recognition and treatment in the United States appears to have been Wayland’s (1837) political economy text.

  3. 3.

    Page references for Keynes’s essay are from Keynes (1972)

  4. 4.

    Data on per capita gross domestic product are from the Bureau of Economic Analysis.

  5. 5.

    Data on the average workweek are from Vandenbroucke (2009) for 1830–1890, from the Historical Statistics of the United States for 1900–1970, and from the Bureau of Labor Statistics for 1980–2012.

  6. 6.

    See Gordon (forthcoming), Ch. 8, for a detailed discussion of the changes over time in the United States.

  7. 7.

    Data on occupations are from the Historical Statistics of the United States.

  8. 8.

    See, for example, Putnam (2000), Ch. 5.

  9. 9.

    Data on median family income are from the Bureau of the Census.

  10. 10.

    Some part of the difference between the growth of output per capita and of median family income reflects the fact that family size has shrunk over this period, and therefore does not properly bear on the argument here. But the difference is not great in this context. Between 1947 and 2012 the average number of persons per family in the United States fell from 3.67 to 3.13 (data are from the Current Population Survey). With adjustment for family size, the growth of real median family income over this period would produce a multiple of 4.6 over a hundred years – more than for the raw data, but still well below the trajectory of real output per capita.

  11. 11.

    In 1973 the average number of persons per family was 3.48. With adjustment for the smaller size of families, the realized growth between 1973 and 2012 would produce a multiple of 1.5 over one hundred years – somewhat larger than without the family size adjustment, but still far from even doubling.

  12. 12.

    In 1973 female participation in the labor force was 44.7%; by 2012 it was 57.7%. (The peak, in 1999, was 60.0%.) Much of this increase, however, was offset by declining male labor force participation: from 78.8% in 1973 to 70.2% in 2012. As Fig. 2 shows, there was also some modest further decline in average hours worked per week. But the main reason for the slower rise of real family incomes was the decline in real hourly wages. Data on real hourly wages are from the Bureau of Labor Statistics, adjusted (slightly) to correct for a series break at 1966.

  13. 13.

    See especially Goldin and Katz (2008).

  14. 14.

    See Elsby et al. (2013) on the United States and Karabarbounis and Neiman (2014) on the decline of the labor share as a global phenomenon. A large literature has developed suggesting explanations for this development.

  15. 15.

    See Munnell et al. (2014) for a review of the most recent evidence.

  16. 16.

    In the United States the number of people participating in the Supplemental Nutritional Assistance Program (“food stamps”) was roughly stable at 20–25 million until the 2007–9 financial crisis, but since then it has nearly doubled. By contrast, publicly provided housing has shrunk relative to the growing population. Medicaid (the main medical care program for the indigent) has increased enormously in cost, but it is not obvious that recipients feel better off because their medical care costs more.

  17. 17.

    See, for example, Krueger and Perri (2006) and Meyer and Sullivan (2013).

  18. 18.

    Aguiar and Bils (2013), p. 1.

  19. 19.

    Lebergott (1993), for example, has made this argument.

  20. 20.

    The 1902 Edition of the Sears, Roebuck Catalogue (New York: Gramercy Books, 1993).

  21. 21.

    The modern literature on the role of habit formation in consumption preferences is large. For two early contributions, see Constantinides (1990) and Campbell and Cochrane (1999).

  22. 22.

    Data on telephone penetration are from the Historical Statistics of the United States.

  23. 23.

    Frey and Osborne (2013), for example, emphasize this aspect of the shift to service-sector employment.

  24. 24.

    See especially Brynjolfsson and Andrew (2014).

  25. 25.

    Tax payments also come from citizens’ incomes, of course, and so apart from distributional consequences there would be little point, in the context of this discussion, of taxing the median earner’s income in order to fund public-sector demand that creates employment for the median worker. But the tax revenues would largely come from those citizens who already have high-income jobs, while the jobs created – in rebuilding the nation’s infrastructure, for example – would presumably be taken by those who don’t.

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Acknowledgments

I am grateful to Ben Sprung-Keyser for research assistance and to two referees for helpful comments on an earlier draft. The conclusions I offer here differ from those I reached in a paper I wrote on this subject some years ago (Friedman 2008)

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Correspondence to Benjamin M. Friedman.

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Friedman, B.M. Work and consumption in an era of unbalanced technological advance. J Evol Econ 27, 221–237 (2017). https://doi.org/10.1007/s00191-015-0426-4

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Keywords

  • Productivity
  • Income
  • Consumption
  • Leisure
  • Technological unemployment