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The US productivity slowdown, the baby boom, and management quality


This paper examines the relationship between the entry of the baby boom into the workforce and the productivity slowdown. Lucas (Bell J Econ 9(2):508–523, 1978) shows how management quality plays a role in determining output. The baby boom’s entry into the workforce resulted in more managers from smaller, pre-baby boom cohorts. These marginal managers were necessarily of lower quality, leading to a drop in total factor productivity. As the boomers aged, this effect was reversed. A calibrated model of managers, workers, and firms suggests that the management effects of the baby boom may explain roughly 20% of the observed productivity slowdown and resurgence.

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  1. Lazear et al. (2007).

  2. See Nordhaus (2002), Gordon and Sichel (2002), Oliner and Sichel (2000), and Fernald et al. (2007) among many others.

  3. Other work has also found a relationship between demographic change and output. Focusing on the dependency ratio, Bloom et al. (2001) find that increases in the size of the working age population can produce a “demographic dividend” to economic growth. Kogel (2005) finds a relationship between total factor productivity and the dependency ratio. Persson (2002) finds that the age structure of US states affects output. Sarel (1995) finds a significant effect of the age structure of the population on output in a cross section of countries. Bloom et al. (1988) find that being a member of a large cohort leads to lower lifetime earnings.

  4. This section draws on an argument originally made in Feyrer (2008).

  5. Chari and Hoenhayn (1991) find that technologies diffuse slowly due to vintage human capital effects.

  6. For 1980, 1990, and 2000, the data are a 5% sample. For the earlier years, a 1% sample is used. The sample is comprised of full-time workers. Workers categorized as “Managers, Officials, and Proprietors” under the 1950 occupational coding are coded as managers.

  7. Lucas (1978), pp. 514–515.

  8. These talent levels are deterministic and not stochastic. The solution technique should therefore be seen as a numeric integration rather than a Monte Carlo exercise. To be more concrete, if there were 99 agents, the first would be assigned the first percentile cutoff of the distribution, the second the second percentile, and so on to the 99th percentile.

  9. This is the numerical equivalent to performing the integration in Eq. 2 where z is a function of a given wage and exogenous interest rate, r. The term L(x) + 1 is the number of workers plus the manager.


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I am grateful to Pete Klenow, Jon Skinner, Doug Staiger, Jay Shambaugh, and participants at the Population Aging and Economic Growth conference at the Harvard School of Public Health for their helpful comments and advice. All errors are my own.

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Correspondence to James Feyrer.

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Responsible editor: James Albrecht

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Feyrer, J. The US productivity slowdown, the baby boom, and management quality. J Popul Econ 24, 267–284 (2011).

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  • Productivity
  • Demographics
  • Manager

JEL Classification

  • O4
  • J1
  • E2