Segregation of subsidized housing units in france
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Segregation of subsidized housing units in France. Julien Chambrillon, Groupe d’Analyse et de Théorie Economique (CNRS - Université Lyon 2) ERSA Summer School in Groningen 4-12 July 2006.

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Segregation of subsidized housing units in france l.jpg

Segregation of subsidized housing units in France

Julien Chambrillon,

Groupe d’Analyse et de Théorie Economique (CNRS - Université Lyon 2)

ERSA Summer School in Groningen 4-12 July 2006


Motivations l.jpg

Introduction Mesures de distribution spatiale Choix méthodologiques Résultats Conclusion

Motivations

  • The Cutler and Glaeser`s paper in 1997 who anaylsed the segregation degree of black population in the US and found that the degree of segregation of this population has a significant impact on individual outcomes

  • In France, the SRU law (`urban and renewal solidarity law`) who impose to all cities located in urban areas of 50 000 people or + to have a proportion of subsidized housing units of 20%

    The aim purpose of this law is to permit a better distribution of this kind of housing between cities inside urbane areas


Objectives l.jpg

Introduction Mesures de distribution spatiale Choix méthodologiques Résultats Conclusion

Objectives

  • Propose some measures of spatial distribution of subsidized housing units in France

  • Analyse the modifications of the choice of geographic level on spatial indexes

  • Compare the urban areas



Dissimilarity index l.jpg

Introduction Mesures de distribution spatiale Choix méthodologiques Résultats Conclusion

Dissimilarity Index

  • FormulaWith HLMi(NONHLMi): the number of subsidized housing units (non subsidized housing units) in iHLM (NONHLM) : the total number of subsidized housing units HLM (non subsidized housing units) in the urban area

    N the number of spatial unit in the urban area

    Interpretation

    • It equals to 0 if all spatial units have the same proportion of subsidized housing

    • It represents the pourcentage of the housing to move to obtain a uniform distribution

  • One of the most widely used Spatial index

    • Especially in US literature to analyse the ethnic Seg.


Data view and spatial units l.jpg

Introduction Mesures de distribution spatiale Choix méthodologiques Résultats Conclusion

Data view and spatial units

  • French Census data 1999

  • Sample:

    • 112 urban areas of 50 000 people or more

    • Which represent 30 millions of people, 12,8 millions of housing units (with a share of subsidized housing units of 21,67 %)

    • 2220 Communes

    • 13 223 Iris (the mean IRIS pop. is : 2267.23)


Measure of the statistical variability l.jpg

Introduction Mesures de distribution spatiale Choix méthodologiques Résultats Conclusion

Measure of the statistical variability

  • Contribution : Distribution under the nulle hypothesis of random distribution of subsidized housing units rather than the uniform distribution

    • Generate by simulation

    • 100 replicates

  • Estimation of confidence intervals by Boostrap (10 000 replicates)



Dissimilarity index and urban area sizes l.jpg

Introduction Mesures de distribution spatiale Choix méthodologiques Résultats Conclusion

Dissimilarity index and urban area sizes


Dissimilarity index by region l.jpg

Introduction Mesures de distribution spatiale Choix méthodologiques Résultats Conclusion

Dissimilarity index by region




Dissimilarity index at the iris level some explanations l.jpg

Introduction Mesures de distribution spatiale Choix méthodologiques Résultats Conclusion

Dissimilarity Index at the IRIS level : some explanations


Dissimilarity index spatial decomposition l.jpg

Introduction Mesures de distribution spatiale Choix méthodologiques Résultats Conclusion

Dissimilarity Index: spatial decomposition :

  • Formula : Diris = Dcom + Dintracom

    (see Wong, 2003)

Index corrected, Spatial decomposition

By increased values


Conclusion l.jpg

Introduction Mesures de distribution spatiale Choix méthodologiques Résultats Conclusion

Conclusion

  • The 20% criterion is not sufficient to garantee a better repartition of subsidized housing units in urban areas.

  • The choice of the IRIS level seems to be the most appropriate to have a more precise measure of spatial segregation of subsidized housing units

  • First step of a work who aims at estimate the impact of the level of segregation on individual oucomes


Questions l.jpg

Questions Choix méthodologiques

Questions

  • Is it possible to improve my segregation measure in using ArcGIS to calculate a more robust index with for example the possiblity to take into account the contiguity of the IRIS inside urban areas, the density of those, the distance between IRIS or any other idea…?


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