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Interactions Between Workers and the Technology of Production: Evidence from Professional Baseball

  • Gould, Eric D
  • Winter, Eyal

This paper examines how the effort choices of workers within the same firm interact with each other. In contrast to the existing literature, we show that workers can affect the productivity of their co-workers based on income maximization considerations, rather than relying on behavioural considerations such as peer pressure, social norms, and shame. Theoretically, we show that a worker's effort has a positive effect on the effort of co-workers if they are complements in production, and a negative effect if they are substitutes. The theory is tested using panel data on the performance of baseball players from 1970 to 2003. The empirical analysis shows that a player's batting average significantly increases with the batting performance of his peers, but decreases with the quality of the team's pitching. Furthermore, a pitcher's performance increases with the pitching quality of his team-mates, but is unaffected by the batting output of the team. These results are inconsistent with behavioural explanations which predict that shirking by any kind of worker will increase shirking by all fellow workers. The results are consistent with the idea that the effort choices of workers interact in ways that are dependent on the technology of production. These findings are robust to controlling for individual fixed-effects, and to using changes in the composition of one's co-workers in order to produce exogenous variation in the performance of one's peers.

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Paper provided by C.E.P.R. Discussion Papers in its series CEPR Discussion Papers with number 6527.

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Date of creation: Oct 2007
Date of revision:
Handle: RePEc:cpr:ceprdp:6527
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  1. Armin Falk & Andrea Ichino, 2004. "Clean Evidence on Peer Effects," Levine's Bibliography 666156000000000439, UCLA Department of Economics.
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  10. Gould, Eric D. & Lavy, Victor & Paserman, M. Daniele, 2005. "Does Immigration Affect the Long-Term Educational Outcomes of Natives? Quasi-Experimental Evidence," IZA Discussion Papers 1883, Institute for the Study of Labor (IZA).
  11. Itoh, Hideshi, 1991. "Incentives to Help in Multi-agent Situations," Econometrica, Econometric Society, vol. 59(3), pages 611-36, May.
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  17. Caroline Hoxby, 2000. "Peer Effects in the Classroom: Learning from Gender and Race Variation," NBER Working Papers 7867, National Bureau of Economic Research, Inc.
  18. Gould, Eric D & Lavy, Victor & Paserman, M. Daniele, 2003. "Immigrating to Opportunity: Estimating the Effect of School Quality Using a Natural Experiment on Ethiopians in Israel," CEPR Discussion Papers 4052, C.E.P.R. Discussion Papers.
  19. Bruce A. Weinberg & Patricia B. Reagan & Jeffrey J. Yankow, 2004. "Do Neighborhoods Affect Hours Worked? Evidence from Longitudinal Data," Journal of Labor Economics, University of Chicago Press, vol. 22(4), pages 891-924, October.
  20. David J. Zimmerman, 2003. "Peer Effects in Academic Outcomes: Evidence from a Natural Experiment," The Review of Economics and Statistics, MIT Press, vol. 85(1), pages 9-23, February.
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  22. Oreopoulos, Philip, 2007. "The Long-Run Consequences of Living in a Poor Neighborhood," Berkeley Program on Housing and Urban Policy, Working Paper Series qt9np9p7m5, Berkeley Program on Housing and Urban Policy.
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  25. Todd D. Kendall, 2003. "Spillovers, Complementarities, and Sorting in Labor Markets with an Application to Professional Sports," Southern Economic Journal, Southern Economic Association, vol. 70(2), pages 389-402, October.
  26. Brian A. Jacob, 2004. "Public Housing, Housing Vouchers, and Student Achievement: Evidence from Public Housing Demolitions in Chicago," American Economic Review, American Economic Association, vol. 94(1), pages 233-258, March.
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