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The 'Pupil' Factory: Specialization and the Production of Human Capital in Schools

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  • Roland G. Fryer, Jr

Abstract

Starting in the 2013-2014 school year, I conducted a randomized field experiment in fifty traditional public elementary schools in Houston, Texas designed to test the potential productivity benefits of teacher specialization in schools. Treatment schools altered their schedules to have teachers specialize in a subset of subjects in which they have demonstrated relative strength (based on value-add measures and principal observations). The average impact of teacher specialization on student achievement is -0.042 standard deviations in math and -0.034 standard deviations in reading, per year. Students enrolled in special education and those with younger teachers demonstrated marked negative results. I argue that the results are consistent with a model in which the benefits of specialization driven by sorting teachers into a subset of subjects based on comparative advantage is outweighed by inefficient pedagogy due to having fewer interactions with each student. Consistent with this, specialized teachers report providing less attention to individual students (relative to non-specialized teachers), though other mechanisms are possible.

Suggested Citation

  • Roland G. Fryer, Jr, 2016. "The 'Pupil' Factory: Specialization and the Production of Human Capital in Schools," NBER Working Papers 22205, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:22205
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    References listed on IDEAS

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    1. Boyan Jovanovic & Peter L. Rousseau, 2001. "Why Wait? A Century of Life before IPO," American Economic Review, American Economic Association, vol. 91(2), pages 336-341, May.
    2. Abadie, Alberto & Imbens, Guido W., 2011. "Bias-Corrected Matching Estimators for Average Treatment Effects," Journal of Business & Economic Statistics, American Statistical Association, vol. 29(1), pages 1-11.
    3. David S. Lee, 2009. "Training, Wages, and Sample Selection: Estimating Sharp Bounds on Treatment Effects," Review of Economic Studies, Oxford University Press, vol. 76(3), pages 1071-1102.
    4. Moulton, Brent R., 1986. "Random group effects and the precision of regression estimates," Journal of Econometrics, Elsevier, vol. 32(3), pages 385-397, August.
    5. Jacob, Brian A., 2005. "Accountability, incentives and behavior: the impact of high-stakes testing in the Chicago Public Schools," Journal of Public Economics, Elsevier, vol. 89(5-6), pages 761-796, June.
    6. Gary S. Becker, 1994. "Human Capital: A Theoretical and Empirical Analysis with Special Reference to Education, Third Edition," NBER Books, National Bureau of Economic Research, Inc, number beck94-1, June.
    7. Moulton, Brent R, 1990. "An Illustration of a Pitfall in Estimating the Effects of Aggregate Variables on Micro Unit," The Review of Economics and Statistics, MIT Press, vol. 72(2), pages 334-338, May.
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    Cited by:

    1. Kirabo Jackson & Alexey Makarin, 2018. "Can Online Off-the-Shelf Lessons Improve Student Outcomes? Evidence from a Field Experiment," American Economic Journal: Economic Policy, American Economic Association, vol. 10(3), pages 226-254, August.
    2. Hill, Andrew J. & Jones, Daniel B., 2018. "A teacher who knows me: The academic benefits of repeat student-teacher matches," Economics of Education Review, Elsevier, vol. 64(C), pages 1-12.

    More about this item

    JEL classification:

    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
    • I20 - Health, Education, and Welfare - - Education - - - General
    • J0 - Labor and Demographic Economics - - General

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