Higher Education

, Volume 71, Issue 5, pp 611–649 | Cite as

Affirmative action in higher education in India: targeting, catch up, and mismatch

  • Veronica FrisanchoEmail author
  • Kala Krishna


Using detailed data on the 2008 graduating class from an elite engineering institution in India, we evaluate the impact of affirmative action policies in higher education focusing on three issues: targeting, catch up, and mismatch. We find that admission preferences effectively target minority students who are poorer than average displaced nonminority students. Moreover, we find that minority students, especially those in more selective majors, fall behind their same-major peers in terms of grades as they progress through college. We also identify evidence in favor of the mismatch hypothesis: Once we control for selection into majors, minority students in more selective majors end up earning less than they would have had if they had chosen a less selective major.


Affirmative action Higher education Targeting  Catch up Mismatch 

JEL Classification

I23 I24 J15 J31 J71 


  1. Akyol, P., & Krishna, K. (2014). Preferences, selection, and value added: A structural approach. NBER working paper no. 20013.Google Scholar
  2. Allison, P. (2001). Missing data. Thousand Oaks, CA: Sage.Google Scholar
  3. Alon, S., & Tienda, M. (2005). Assessing the “Mismatch” hypothesis: Differences in college graduation rates by institutional selectivity. Sociology of Education, 78, 294–315.CrossRefGoogle Scholar
  4. Alon, S., & Tienda, M. (2007). Diversity, opportunity, and the shifting meritocracy in higher education. American Sociological Review, 72(4), 487–511.CrossRefGoogle Scholar
  5. Alon, S., & Malamud, O. (2014). The impact of Israel’s class-based affirmative action policy on admission and academic outcomes. Economics of Education Review, 40, 123–139.CrossRefGoogle Scholar
  6. Altonji, J. G., Elder, T. E., & Taber, C. R. (2005). Selection on observed and unobserved variables: Assessing the effectiveness of catholic schools. Journal of Political Economy, 113(1), 151–184.CrossRefGoogle Scholar
  7. Arcidiacono, P. (2005). Affirmative action in higher education: How do admission and financial aid rules affect future earnings? Econometrica, 73(5), 1477–1524.CrossRefGoogle Scholar
  8. Arcidiacono, P., Ausejo, E., & Spenner, K. (2011). What happens after enrollment? An analysis of the time path of racial differences in GPA and major choice. Working paper.Google Scholar
  9. Assuno, J., & Ferman, B. (2013). Does affirmative action enhance or undercut investment incentives? Evidence from quotas in Brazilian public universities. Working paperGoogle Scholar
  10. Bertrand, M., Hanna, R., & Mullainathan, S. (2010). Affirmative action in education: Evidence from engineering college admissions in India. Journal of Public Economics, 94(1–2), 16–29.CrossRefGoogle Scholar
  11. Blau, J., Moller, S., & Jones, L. (2004). Why test? Talent loss and enrolment loss. Social Science Research, 33, 409–434.CrossRefGoogle Scholar
  12. Bowen, W., & Bok, D. (1998). The Shape of the River. Princeton: Princeton University Press.Google Scholar
  13. Carnevale, A. P., & Rose, S. J. (2003). Socioeconomic status, race/ethnicity and selective college admissions. New York: The Century Foundation Press.Google Scholar
  14. Chakravarty, S., & Somanathan, E. (2008). Discrimination in an elite labour market? Job placements at IIM-Ahmedabad. Economic and Political Weekly, 43(44), 45–50.Google Scholar
  15. Chaudhuri, S., & Gupta, N. (2009). Levels of living and poverty patterns: A district-wise analysis for India. Economic and Political Weekly, 44(9), 94–110.Google Scholar
  16. Chay, K., McEwan, P. J., & Urquiola, M. (2005). The central role of noise in evaluating interventions that use test scores to rank schools. American Economic Review, 95, 1237–1258.CrossRefGoogle Scholar
  17. Francis, A., & Tannuri-Pianto, M. (2012). Using Brazil’s racial continuum to examine the short-term effects of affirmative action in higher education. The Journal of Human Resources, 47, 754–784.CrossRefGoogle Scholar
  18. Frisancho, V., & Krishna, K. (2012). Affirmative action in higher education in India: Targeting, catch up, and mismatch. NBER working paper no. 17727.Google Scholar
  19. Frisancho, V., Krishna, K., Lychagin, S., & Yavas, C. (2014). Better luck next time: Learning through retaking. Working paper.Google Scholar
  20. Kahlenberg, R. D. (Ed.). (1996). The Remedy: Class, race, and affirmative action. New York: Basic Books.Google Scholar
  21. Kahlenberg, R. D. (Ed.). (2004). America’s untapped resource: Low-income students in higher education. New York: The Century Foundation Press.Google Scholar
  22. Kochar, A. (2010). Affirmative action through quotas: The effect on learning In India. Stanford Center for International Development, Working paper no. 430.Google Scholar
  23. Loury, L. D., & Garman, D. (1993). Affirmative action in higher education. American Economic Review, 83(2), 99–103.Google Scholar
  24. Loury, L. D., & Garman, D. (1995). College selectivity and earnings. Journal of Labor Economics, 13(2), 289–308.CrossRefGoogle Scholar
  25. NCEUS. (2009). The Challenge of Employment in India An Informal Economy Perspective. National Commission for Enterprises in the Unorganised Sector: Technical Report.Google Scholar
  26. Rosenbaum, P. R., & Rubin, D. B. (1983). The Central Role of the Propensity Score in Observational Studies for Causal Effects. Biometrika, 70, 41–55.CrossRefGoogle Scholar
  27. Rothstein, J., & Yoon, A. (2008). Affirmative action in law school admissions: What do racial preferences do? University of Chicago Law Review, 75(2), 649–714.Google Scholar
  28. Rothstein, J., & Yoon, A. (2009). Mismatch in Law School. Working paper.Google Scholar
  29. Saeme, D. (2014). does the implementation of affirmative action in a competitive setting incentivize underrepresented public school applicants performance? Evidence from So Paulo. The Yale Journal of Economics, 2, 93–114.Google Scholar
  30. Sander, R. (2004). A systemic analysis of affirmative action in American law schools. Stanford Law Review, 57(2), 367–483.Google Scholar
  31. Van Buuren, S., Brand, J. P. L., & Groothuis-Oudshoorn, C. G. M. (2006). Fully conditional specification in multivariate imputation. Journal of Statistical Computation and Simulation, 76, 1046–1064.Google Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2015

Authors and Affiliations

  1. 1.Research DepartmentInter-American Development BankWashingtonUSA
  2. 2.Department of EconomicsThe Pennsylvania State UniversityUniversity ParkUSA

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