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Measuring Segregation When Units are Small: A Parametric Approach

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  • Roland Rathelot

Abstract

This article considers the issue of measuring segregation in a population of units that contain few individuals (e.g., establishments, classrooms). When units are small, the usual segregation indices, which are based on sample proportions, are biased. We propose a parametric solution: the probability that an individual within a given unit belongs to the minority is assumed to be distributed as a mixture of Beta distributions. The model can be estimated and indices deduced. Simulations show that this new method performs well compared to existing ones, even in the case of misspecification. An application to residential segregation in France according to parents’ nationalities is then undertaken. This article has online supplementary materials.

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  • 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.
    • Handle: RePEc:taf:jnlbes:v:30:y:2012:i:4:p:546-553
    DOI: 10.1080/07350015.2012.707586
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    1. Kremer, M & Maskin, E, 1996. "Wage Inequality and Segregation by Skill," Working papers 96-23, Massachusetts Institute of Technology (MIT), Department of Economics.
    2. Martin Söderström & Roope Uusitalo, 2010. "School Choice and Segregation: Evidence from an Admission Reform," Scandinavian Journal of Economics, Wiley Blackwell, vol. 112(1), pages 55-76, March.
    3. Rebecca Allen & Simon Burgess & Frank Windmeijer, 2009. "More Reliable Inference for Segregation Indices," The Centre for Market and Public Organisation 09/216, The Centre for Market and Public Organisation, University of Bristol, UK.
    4. 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.
    5. Manon Domingues Dos Santos, 2005. "Travailleurs maghrébins et portugais en France. Le poids de l'origine," Revue économique, Presses de Sciences-Po, vol. 56(2), pages 447-464.
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    1. Glitz, Albrecht, 2014. "Ethnic segregation in Germany," Labour Economics, Elsevier, vol. 29(C), pages 28-40.
    2. 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.
    3. Matthew Gentzkow & Jesse M. Shapiro & Matt Taddy, 2019. "Measuring Group Differences in High‐Dimensional Choices: Method and Application to Congressional Speech," Econometrica, Econometric Society, vol. 87(4), pages 1307-1340, July.
    4. Rathelot, Roland, 2014. "Ethnic differentials on the labor market in the presence of asymmetric spatial sorting: Set identification and estimation," Regional Science and Urban Economics, Elsevier, vol. 48(C), pages 154-167.
    5. Renan Xavier Cortes & Sergio Rey & Elijah Knaap & Levi John Wolf, 2020. "An open-source framework for non-spatial and spatial segregation measures: the PySAL segregation module," Journal of Computational Social Science, Springer, vol. 3(1), pages 135-166, April.
    6. Xavier D'Haultfœuille & Roland Rathelot, 2017. "Measuring segregation on small units: A partial identification analysis," Quantitative Economics, Econometric Society, vol. 8(1), pages 39-73, March.

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