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Government-Mandated Discriminatory Policies


Peter Norman


University of British Columbia - Department of Economics

Hanming Fang


University of Pennsylvania - Department of Economics; National Bureau of Economic Research (NBER)

November 22, 2004

SSRI Working Paper No. 2001-12

Abstract:     
This paper provides a simple explanation for why some minority groups are economically successful, despite being subject to government-mandated discriminatory policies. We study an economy with private and public sectors in which workers invest in imperfectly observable skills that are important to the private sector but not to the public sector. A law allows native majority workers to be employed in the public sector with positive probability while excluding the minority from it. We show that even when the public sector offers the highest wage rate, it is still possible that the discriminated group is, on average, economically more successful. The reason is that the preferential policy lowers the majority's incentive to invest in imperfectly observable skills by exacerbating the informational free riding problem in the private sector labor market.

Number of Pages in PDF File: 33

Keywords: Discrimination, successful minorities, free-riding, human capital

JEL Classification: D62, D63, H23, J71, J78

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Date posted: July 30, 2001  

Suggested Citation

Norman, Peter and Fang, Hanming, Government-Mandated Discriminatory Policies (November 22, 2004). SSRI Working Paper No. 2001-12. Available at SSRN: http://ssrn.com/abstract=278267 or http://dx.doi.org/10.2139/ssrn.278267

Contact Information

Peter Norman (Contact Author)
University of British Columbia - Department of Economics ( email )
2329 West Mall
Vancouver, British Columbia BC V6T 1Z2
Canada
(604) 822-2839 (Phone)
HOME PAGE: http://faculty.arts.ubc.ca/pnorman/
Hanming Fang
University of Pennsylvania - Department of Economics ( email )
3718 Locust Walk
Philadelphia, PA 19104
United States
National Bureau of Economic Research (NBER)
1050 Massachusetts Avenue
Cambridge, MA 02138
United States
Feedback to SSRN (Beta)


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