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Measuring Segregation on Small Units : A Partial Identification Analysis

  • Xavier d'Haultfoeuille

    ()

    (CREST)

  • Roland Rathelot

    ()

    (CREST)

We consider the issue of measuring segregation in a population of small units, considering establishments in our application. Each establishment may have a different probability to hire an individual from the minority group. We define segregation indices as inequality indices on these unobserved, random probabilities. Because these probabilities are measured with error by proportions, standard estimators are inconsistent. We model this problem as a nonparametric binomial mixture. Under this testable assumption and conditions satisfied by standard segregation indices, such indices are partially identified and sharp bounds can be easily obtained by an optimization over a low dimensional space. We also develop bootstrap confidence intervals and a test of the binomial mixture model. Finally, we apply our method to measure the segregation of foreigners in small French firms.

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Paper provided by Centre de Recherche en Economie et Statistique in its series Working Papers with number 2011-18.

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Length: 34
Date of creation: May 2011
Date of revision:
Handle: RePEc:crs:wpaper:2011-18
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  1. Rebecca Allen & Simon Burgess & Frank Windmeijer, 2009. "More Reliable Inference for Segregation Indices," The Centre for Market and Public Organisation 09/216, Department of Economics, University of Bristol, UK.
  2. Hutchens, Robert, 2001. "Numerical measures of segregation: desirable properties and their implications," Mathematical Social Sciences, Elsevier, vol. 42(1), pages 13-29, July.
  3. Michael Carter, 2001. "Foundations of Mathematical Economics," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262531925.
  4. Michael Carter, 2001. "Foundations of Mathematical Economics," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262032899.
  5. Roland Rathelot, 2012. "Measuring Segregation When Units are Small: A Parametric Approach," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(4), pages 546-553, June.
  6. Christian Dustmann & Albrecht Glitz & Uta Schönberg & Herbert Brücker, 2016. "Referral-based Job Search Networks," Review of Economic Studies, Oxford University Press, vol. 83(2), pages 514-546.
  7. Iranzo, Susana & Schivardi, Fabiano & Tosetti, Elisa, 2006. "Skill Dispersion and Firm Productivity: An Analysis with Employer-Employee Matched Data," CEPR Discussion Papers 5539, C.E.P.R. Discussion Papers.
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  10. William J. Carrington & Kenneth R. Troske, 1998. "Sex segregation in U.S. manufacturing," Industrial and Labor Relations Review, ILR Review, Cornell University, ILR School, vol. 51(3), pages 445-464, April.
  11. Victor Chernozhukov & Iván Fernández‐Val & Jinyong Hahn & Whitney Newey, 2013. "Average and Quantile Effects in Nonseparable Panel Models," Econometrica, Econometric Society, vol. 81(2), pages 535-580, 03.
  12. Laura Giuliano & David I. Levine & Jonathan Leonard, 2009. "Manager Race and the Race of New Hires," Journal of Labor Economics, University of Chicago Press, vol. 27(4), pages 589-631, October.
  13. Frederic Lord, 1969. "Estimating true-score distributions in psychological testing (an empirical bayes estimation problem)," Psychometrika, Springer;The Psychometric Society, vol. 34(3), pages 259-299, September.
  14. Luigi Pistaferri, 1999. "Informal Networks in the Italian Labor Market," Giornale degli Economisti, GDE (Giornale degli Economisti e Annali di Economia), Bocconi University, vol. 58(3-4), pages 355-375, December.
  15. Martin Sˆderstrˆm & Roope Uusitalo, 2010. "School Choice and Segregation: Evidence from an Admission Reform," Scandinavian Journal of Economics, Wiley Blackwell, vol. 112(1), pages 55-76, 03.
  16. Donald W. K. Andrews & Sukjin Han, 2009. "Invalidity of the bootstrap and the m out of n bootstrap for confidence interval endpoints defined by moment inequalities," Econometrics Journal, Royal Economic Society, vol. 12(s1), pages S172-S199, 01.
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