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Skill-biased Technological Change, Earnings of Unskilled Workers, and Crime

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  • Naci H. Mocan
  • Bulent Unel

Abstract

This paper investigates the impact of unskilled workers' earnings on crime. Following the literature on wage inequality and skill-biased technological change, we employ CPS data to create state-year as well as state-year-and (broad) industry specific measures of skill-biased technological change, which are then used as instruments for unskilled workers' earnings in crime regressions. Regressions that employ state panels reveal that technology-induced variations in unskilled workers' earnings impact property crime with an elasticity of -1, but that wages have no impact on violent crime. The paper also estimates, for the first time in this literature, structural crime equations using micro panel data from NLSY97 and instrumenting real wages of young workers. Using state-year-industry specific technology shocks as instruments yields elasticities that are in the neighborhood of -2 for most types of crime, which is markedly larger than previous estimates. In both data sets there is evidence for asymmetric impact of unskilled workers' earnings on crime. A decline in earnings has a larger effect on crime in comparison to an increase in earnings by the same absolute value.

Suggested Citation

  • Naci H. Mocan & Bulent Unel, 2011. "Skill-biased Technological Change, Earnings of Unskilled Workers, and Crime," NBER Working Papers 17605, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:17605
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    Cited by:

    1. Stephen Machin & Olivier Marie & Sunčica Vujić, 2012. "Youth Crime and Education Expansion," German Economic Review, Verein für Socialpolitik, vol. 13(4), pages 366-384, November.
    2. Csapó, Gergely & Müller, Rudolf, 2013. "Optimal mechanism design for the private supply of a public good," Games and Economic Behavior, Elsevier, vol. 80(C), pages 229-242.
    3. William Harbaugh & Naci Mocan & Michael Visser, 2013. "Theft and Deterrence," Journal of Labor Research, Springer, vol. 34(4), pages 389-407, December.
    4. Steve Brito & Ana Corbacho & Rene Osorio Rivas, 2014. "Remittances and the Impact on Crime in Mexico," IDB Publications (Working Papers) 85093, Inter-American Development Bank.
    5. Christine Braun, 2019. "Crime and the minimum wage," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 32, pages 122-152, April.
    6. Laura Jaitman, 2019. "Frontiers in the economics of crime: lessons for Latin America and the Caribbean," Latin American Economic Review, Springer;Centro de Investigaciòn y Docencia Económica (CIDE), vol. 28(1), pages 1-36, December.
    7. Mocan, Naci & Raschke, Christian & Unel, Bulent, 2015. "The impact of mothers’ earnings on health inputs and infant health," Economics & Human Biology, Elsevier, vol. 19(C), pages 204-223.

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    More about this item

    JEL classification:

    • J23 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Labor Demand
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity
    • J31 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Wage Level and Structure; Wage Differentials
    • K42 - Law and Economics - - Legal Procedure, the Legal System, and Illegal Behavior - - - Illegal Behavior and the Enforcement of Law
    • O3 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights

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