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Does Affirmative Action Lead to Mismatch? A New Test and Evidence

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Author Info

  • Peter Arcidiacono
  • Esteban M. Aucejo
  • Hanming Fang
  • Kenneth I. Spenner

Abstract

We argue that once we take into account the students' rational enrollment decisions, mismatch in the sense that the intended beneficiary of affirmative action admission policies are made worse o could occur only if selective universities possess private information about students' post-enrollment treatment effects. This necessary condition for mismatch provides the basis for a new test. We propose an empirical methodology to test for private information in such a setting. The test is implemented using data from Campus Life and Learning Project (CLL) at Duke. Evidence shows that Duke does possess private information that is a statistically significant predictor of the students' post-enrollment academic performance. We also propose strategies to evaluate more conclusively whether the evidence of Duke private information has generated mismatch.

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Bibliographic Info

Paper provided by Duke University, Department of Economics in its series Working Papers with number 10-26.

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Length: 34
Date of creation: 2010
Date of revision:
Handle: RePEc:duk:dukeec:10-26

Contact details of provider:
Postal: Department of Economics Duke University 213 Social Sciences Building Box 90097 Durham, NC 27708-0097
Phone: (919) 660-1800
Fax: (919) 684-8974
Web page: http://econ.duke.edu/

Related research

Keywords: Mismatch; Private information; Affirmative Action;

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References

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  1. Stacy Berg Dale & Alan Krueger, 1998. "Estimating the Payoff to Attending a More Selective College: An Application of Selection on Observables and Unobservables," Working Papers 788, Princeton University, Department of Economics, Industrial Relations Section..
  2. Pauly, Mark V, 1974. "Overinsurance and Public Provision of Insurance: The Roles of Moral Hazard and Adverse Selection," The Quarterly Journal of Economics, MIT Press, vol. 88(1), pages 44-62, February.
  3. Tomas Philipson & John Cawley, 1999. "An Empirical Examination of Information Barriers to Trade in Insurance," American Economic Review, American Economic Association, vol. 89(4), pages 827-846, September.
  4. Rothschild, Michael & Stiglitz, Joseph E, 1976. "Equilibrium in Competitive Insurance Markets: An Essay on the Economics of Imperfect Information," The Quarterly Journal of Economics, MIT Press, vol. 90(4), pages 630-49, November.
  5. Todd Stinebrickner & Ralph Stinebrickner, 2008. "Learning About Academic Ability and the College Drop-Out Decision," University of Western Ontario, CIBC Centre for Human Capital and Productivity Working Papers 20086, University of Western Ontario, CIBC Centre for Human Capital and Productivity.
  6. Amy Finkelstein & James Poterba, 2000. "Adverse Selection in Insurance Markets: Policyholder Evidence from the U.K. Annuity Market," NBER Working Papers 8045, National Bureau of Economic Research, Inc.
  7. Pierre-Andre Chiappori & Bernard Salanie, 2000. "Testing for Asymmetric Information in Insurance Markets," Journal of Political Economy, University of Chicago Press, vol. 108(1), pages 56-78, February.
  8. Pierre-André Chiappori & Bruno Jullien & Bernard Salanié & François Salanié, 2002. "Asymmetric Information in Insurance : General Testable Implications," Working Papers 2002-42, Centre de Recherche en Economie et Statistique.
  9. Hanming Fang & Michael P. Keane & Dan Silverman, 2008. "Sources of Advantageous Selection: Evidence from the Medigap Insurance Market," Journal of Political Economy, University of Chicago Press, vol. 116(2), pages 303-350, 04.
  10. Arcidiacono, Peter & Khan, Shakeeb & Vigdor, Jacob L., 2011. "Representation versus assimilation: How do preferences in college admissions affect social interactions?," Journal of Public Economics, Elsevier, vol. 95(1), pages 1-15.
  11. Jesse Rothstein & Albert Yoon, 2006. "Mismatch in Law School," Working Papers 79, Princeton University, Department of Economics, Center for Economic Policy Studies..
  12. Li, Tong & Vuong, Quang, 1998. "Nonparametric Estimation of the Measurement Error Model Using Multiple Indicators," Journal of Multivariate Analysis, Elsevier, vol. 65(2), pages 139-165, May.
  13. Cunha, Flavio & Heckman, James J. & Navarro, Salvador, 2004. "Separating Uncertainty from Heterogeneity in Life Cycle Earnings," IZA Discussion Papers 1437, Institute for the Study of Labor (IZA).
  14. Peter Arcidiacono & Jacob L. Vigdor, 2010. "Does The River Spill Over? Estimating The Economic Returns To Attending A Racially Diverse College," Economic Inquiry, Western Economic Association International, vol. 48(3), pages 537-557, 07.
  15. Johanne Boisjoly & Greg J. Duncan & Michael Kremer & Dan M. Levy & Jacque Eccles, 2006. "Empathy or Antipathy? The Impact of Diversity," American Economic Review, American Economic Association, vol. 96(5), pages 1890-1905, December.
  16. Amy Finkelstein & Kathleen McGarry, 2006. "Multiple Dimensions of Private Information: Evidence from the Long-Term Care Insurance Market," American Economic Review, American Economic Association, vol. 96(4), pages 938-958, September.
  17. repec:rje:randje:v:37:y:2006:i:4:p:783-798 is not listed on IDEAS
  18. Wilson, Charles, 1977. "A model of insurance markets with incomplete information," Journal of Economic Theory, Elsevier, vol. 16(2), pages 167-207, December.
  19. Loury, Linda Datcher & Garman, David, 1995. "College Selectivity and Earnings," Journal of Labor Economics, University of Chicago Press, vol. 13(2), pages 289-308, April.
  20. Cardon, James H & Hendel, Igal, 2001. "Asymmetric Information in Health Insurance: Evidence from the National Medical Expenditure Survey," RAND Journal of Economics, The RAND Corporation, vol. 32(3), pages 408-27, Autumn.
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Citations

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Cited by:
  1. Arcidiacono, Peter & Hotz, V. Joseph & Kang, Songman, 2012. "Modeling college major choices using elicited measures of expectations and counterfactuals," Journal of Econometrics, Elsevier, vol. 166(1), pages 3-16.
  2. Debopam Bhattacharya & Shin Kanaya & Margaret Stevens, 2014. "Are University Admissions Academically Fair?," CREATES Research Papers 2014-06, School of Economics and Management, University of Aarhus.
  3. Eric Parsons, 2014. "The Impact of Attending Low-Achieving Schools on High-Performing Student Outcomes," Working Papers 1407, Department of Economics, University of Missouri.
  4. Arcidiacono, Peter & Aucejo, Esteban & Hotz, V. Joseph, 2013. "University Differences in the Graduation of Minorities in STEM Fields: Evidence from California," IZA Discussion Papers 7227, Institute for the Study of Labor (IZA).
  5. Peter Arcidiacono & Esteban Aucejo & V. Joseph Hotz, 2013. "University differences in the graduation of minorities in STEM fields: evidence from California," LSE Research Online Documents on Economics 51564, London School of Economics and Political Science, LSE Library.
  6. Arcidiacono, Peter & Aucejo, Esteban & Coate, Patrick & Hotz, V. Joseph, 2012. "Affirmative Action and University Fit: Evidence from Proposition 209," IZA Discussion Papers 7000, Institute for the Study of Labor (IZA).
  7. Basit Zafar, 2009. "How do college students form expectations?," Staff Reports 378, Federal Reserve Bank of New York.
  8. Peter Arcidiacono & Esteban Aucejo & Patrick Coate & V. Joseph Hotz, 2013. "Affirmative action and university fit: evidence from Proposition 209," LSE Research Online Documents on Economics 51565, London School of Economics and Political Science, LSE Library.

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