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Human Capital Spillovers in Manufacturing: Evidence from Plant-Level Production Functions

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  • Enrico Moretti

Abstract

I assess the magnitude of human capital spillovers in US cities by estimating plant level production functions. I use a unique firm-worker matched dataset, obtained by combining the Census of Manufacturers with the Census of Population. After controlling for a plant’s own human capital, plant fixed effects, industry-specific and state-specific transitory shocks, I find that the output of plants located in cities that experience large increases in the share of college graduates rises more than the output of similar plants located in cities that experience small increases in the share of college graduates. Several specification tests indicate that the estimated effect is not completely spurious. First, within a city, the spillover between plants that are geographically and economically close is positive, while spillovers between plants that are geographically close but economically distant is zero. Second, most of the estimated spillover comes from hi-tech plants. For non hi-tech productions, the spillover is virtually zero. When I stratify the sample by the percentage of employees who are college educated, I find that the spillover is larger the larger the percentage of college educated workers in the plant. Third, density of physical capital in a city outside a plant has no effect on a plant’s productivity. Consistent with a model that includes both standard and general equilibrium forces and spillovers, the estimated productivity differences between cities with high and low levels of human capital match remarkably well differences in labor costs that are typically observed between cities with high and low levels of human capital. This is important because, in equilibrium, any productivity gain generated by human capital spillover should be offset by increased costs.

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  • Enrico Moretti, 2002. "Human Capital Spillovers in Manufacturing: Evidence from Plant-Level Production Functions," Working Papers 02-27, Center for Economic Studies, U.S. Census Bureau.
  • Handle: RePEc:cen:wpaper:02-27
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    3. Wang, Chunchao & Zhang, Chenglei & Ni, Jinlan, 2015. "Social network, intra-network education spillover effect and rural–urban migrants' wages: Evidence from China," China Economic Review, Elsevier, vol. 35(C), pages 156-168.
    4. Gustavo A. Crespi & Aldo Geuna & Lionel J. J. Nesta, 2006. "Labour Mobility of Academic Inventors. Career Decision and Knowledge Transfer," SPRU Working Paper Series 139, SPRU - Science Policy Research Unit, University of Sussex Business School.
    5. Lopez-Cermeño, Alexandra, 2016. "Knowledge shocks diffusion and the resilience of regional inequality," IFCS - Working Papers in Economic History.WH 22859, Universidad Carlos III de Madrid. Instituto Figuerola.
    6. Alan Manning, 2004. "We Can Work It Out: The Impact of Technological Change on the Demand for Low‐Skill Workers," Scottish Journal of Political Economy, Scottish Economic Society, vol. 51(5), pages 581-608, November.
    7. Galindo-Rueda, Fernando & Haskel, Jonathan, 2005. "Skills, Workforce Characteristics and Firm-Level Productivity: Evidence from the Matched ABI/Employer Skills Survey," IZA Discussion Papers 1542, Institute of Labor Economics (IZA).
    8. Navon, Guy, 2009. "Human Capital Spillovers in the Workplace: Labor Diversity and Productivity," MPRA Paper 17741, University Library of Munich, Germany.
    9. Matthew E. Kahn & Nancy Lozano‐Gracia & Maria Edisa Soppelsa, 2021. "Pollution'S Role In Reducing Urban Quality Of Life In The Developing World," Journal of Economic Surveys, Wiley Blackwell, vol. 35(1), pages 330-347, February.
    10. Krammer, Sorin M.S., 2014. "Assessing the relative importance of multiple channels for embodied and disembodied technological spillovers," Technological Forecasting and Social Change, Elsevier, vol. 81(C), pages 272-286.
    11. Alan Manning, 2004. "We Can Work It Out: the Impact of Technological Change on the Demand for Low Skill Workers," CEP Discussion Papers dp0640, Centre for Economic Performance, LSE.
    12. Caragliu, Andrea & Del Bo, Chiara, 2011. "Determinants of spatial knowledge spillovers in Italian provinces," Socio-Economic Planning Sciences, Elsevier, vol. 45(1), pages 28-37, March.
    13. Irwin Feller, 2004. "Virtuous and Vicious Cycles in the Contributions of Public Research Universities to State Economic Development Objectives," Economic Development Quarterly, , vol. 18(2), pages 138-150, May.
    14. R. Jason Faberman, 2003. "Job Flows and Establishment Characteristics: Variations Across U.S. Metropolitan Areas," William Davidson Institute Working Papers Series 2003-609, William Davidson Institute at the University of Michigan.
    15. Gustavo Crespi & Aldo Geuna & Lionel Nesta, 2007. "The mobility of university inventors in Europe," The Journal of Technology Transfer, Springer, vol. 32(3), pages 195-215, June.

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    Keywords

    CES; economic; research; micro; data; microdata; chief; economist;
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    JEL classification:

    • J0 - Labor and Demographic Economics - - General
    • I2 - Health, Education, and Welfare - - Education

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