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Does Affirmative Action Affect Productivity In The Indian Railways?

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  • Ashwini Deshpande

    (Department of Economics, Delhi School of Economics, Delhi, India)

  • Thomas E. Weisskopf

    (University of Michigan, Ann Arbor)

Abstract

Our objective in this paper is to shed some empirical light on a claim often made by critics of affirmative action policies: that increasing the representation of members of marginalized communities in jobs – and especially in relatively skilled positions – comes at a cost of reduced efficiency. We undertake a systematic empirical analysis of productivity in the Indian Railways in order to determine whether increasing proportions of Scheduled Castes and Scheduled Tribes in railway employment – largely a consequence of India's affirmative action policies – have actually reduced productive efficiency in the railway system. We find no evidence that higher percentages of Scheduled Castes and Scheduled Tribes in the railway labour force have reduced productivity. Indeed, some of our results suggest that the opposite is true, providing tentative support for the claim that greater labour force diversity boosts productivity.

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Bibliographic Info

Paper provided by Centre for Development Economics, Delhi School of Economics in its series Working papers with number 185.

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Length: 44 pages
Date of creation: May 2010
Date of revision:
Handle: RePEc:cde:cdewps:185

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Keywords: affirmative action; labour force; productivity; Indian railways;

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  1. Baltagi, Badi H. & Griffin, James M., 1997. "Pooled estimators vs. their heterogeneous counterparts in the context of dynamic demand for gasoline," Journal of Econometrics, Elsevier, vol. 77(2), pages 303-327, April.
  2. James Levinsohn & Amil Petrin, 2003. "Estimating Production Functions Using Inputs to Control for Unobservables," Review of Economic Studies, Oxford University Press, vol. 70(2), pages 317-341.
  3. David Neumark & Harry Holzer, 2000. "Assessing Affirmative Action," Journal of Economic Literature, American Economic Association, vol. 38(3), pages 483-568, September.
  4. Breusch, T S & Pagan, A R, 1980. "The Lagrange Multiplier Test and Its Applications to Model Specification in Econometrics," Review of Economic Studies, Wiley Blackwell, vol. 47(1), pages 239-53, January.
  5. Baltagi, Badi H. & Li, Qi, 1995. "Testing AR(1) against MA(1) disturbances in an error component model," Journal of Econometrics, Elsevier, vol. 68(1), pages 133-151, July.
  6. Baltagi, Badi H. & Li, Qi, 1991. "A joint test for serial correlation and random individual effects," Statistics & Probability Letters, Elsevier, vol. 11(3), pages 277-280, March.
  7. Jerry Coakley & Ana-Maria Fuertes & Ron Smith, 2002. "A Principal Components Approach to Cross-Section Dependence in Panels," 10th International Conference on Panel Data, Berlin, July 5-6, 2002 B5-3, International Conferences on Panel Data.
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