IDEAS home Printed from https://ideas.repec.org/a/sae/envira/v48y2016i10p2046-2066.html

How diverse can measures of segregation be? Results from Monte Carlo simulations of an agent-based model

Author

Listed:
  • Daniel Arribas-Bel
  • Peter Nijkamp
  • Jacques Poot

Abstract

Cultural diversity is a complex and multi-faceted concept. Commonly used quantitative measures of the spatial distribution of culturally defined groups—such as segregation, isolation or concentration indexes—have been designed to capture just one feature of this distribution. The strengths and weaknesses of such measures under varying demographic, geographic and behavioral conditions can only be comprehensively assessed empirically. This has been rarely done in the case of multigroup cultural diversity. This paper aims to fill this gap and to provide evidence on the empirical properties of various segregation indexes by means of Monte Carlo replications of agent-based modelling simulations under widely varying assumptions. Schelling’s classical segregation model is used as the theoretical engine to generate patterns of spatial clustering. The data inputs include the initial population, the assumed geography, the number and shares of various cultural groups, and their preferences with respect to co-location. Our Monte Carlo replications of agent-based modelling data generating process produces output maps that enable us to assess the sensitivity of the various measures of segregation to parameter assumptions by means of response surface analysis. We find that, as our simulated city becomes more diverse, stable residential location equilibria require the preference for co-location with one’s own group to be not much more than the group share of the smallest demographic minority. When equilibria exist, the values of the various segregation measures are strongly dependent on the composition of the population across cultural groups, the assumed preferences and the assumed geography. Index values are generally non-decreasing in increasing preference for within-group co-location. More diverse populations yield—for given preferences and geography—a greater degree of spatial clustering. The sensitivity of segregation measures to underlying conditions suggests that meaningful analysis of the impact of segregation requires spatial panel data modelling.

Suggested Citation

  • Daniel Arribas-Bel & Peter Nijkamp & Jacques Poot, 2016. "How diverse can measures of segregation be? Results from Monte Carlo simulations of an agent-based model," Environment and Planning A, , vol. 48(10), pages 2046-2066, October.
    • Handle: RePEc:sae:envira:v:48:y:2016:i:10:p:2046-2066
    DOI: 10.1177/0308518X16653402
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/0308518X16653402
    Download Restriction: no
    File URL: https://libkey.io/10.1177/0308518X16653402?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Kan Chen & Elena G. Irwin & Ciriyam Jayaprakash & Keith Warren, 2005. "The Emergence of Racial Segregation in an Agent-Based Model of Residential Location: The Role of Competing Preferences," Computational and Mathematical Organization Theory, Springer, vol. 11(4), pages 333-338, December.
    2. Guy Dumais & Glenn Ellison & Edward L. Glaeser, 2002. "Geographic Concentration As A Dynamic Process," The Review of Economics and Statistics, MIT Press, vol. 84(2), pages 193-204, May.
    3. Peter Nijkamp & Jacques Poot, 2015. "Cultural Diversity - A Matter of Measurement," RFBerlin Discussion Paper Series 1502, ROCKWOOL Foundation Berlin (RFBerlin).
    4. David M. Cutler & Edward L. Glaeser & Jacob L. Vigdor, 1999. "The Rise and Decline of the American Ghetto," Journal of Political Economy, University of Chicago Press, vol. 107(3), pages 455-506, June.
    5. Peter Nijkamp & Jacques Poot & Jessie Bakens (ed.), 2015. "The Economics of Cultural Diversity," Books, Edward Elgar Publishing, number 15883, August.
    6. Peter Nijkamp & Jacques Poot & Mediha Sahin (ed.), 2012. "Migration Impact Assessment," Books, Edward Elgar Publishing, number 14476, August.
    7. Schelling, Thomas C, 1969. "Models of Segregation," American Economic Review, American Economic Association, vol. 59(2), pages 488-493, May.
    8. Maurel, Francoise & Sedillot, Beatrice, 1999. "A measure of the geographic concentration in french manufacturing industries," Regional Science and Urban Economics, Elsevier, vol. 29(5), pages 575-604, September.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Tubadji, Annie & Nijkamp, Peter, 2016. "Impact of Intangible Cultural Capital on Regional Economic Development: A Study on Culture-Based Development in Greece," Journal of Regional Analysis and Policy, Mid-Continent Regional Science Association, vol. 46(01).
    2. Moritz Meister & Annekatrin Niebuhr, 2021. "Comparing ethnic segregation across cities—measurement issues matter," Review of Regional Research: Jahrbuch für Regionalwissenschaft, Springer;Gesellschaft für Regionalforschung (GfR), vol. 41(1), pages 33-54, February.
    3. Zhiling Wang & Thomas de Graaff & Peter Nijkamp, 2018. "Barriers of Culture, Networks, and Language in International Migration: A Review," REGION, European Regional Science Association, vol. 5, pages 73-89.
    4. Tubadji, Annie & Nijkamp, Peter & Santarelli, Enrico, 2017. "Shacklean Uncertainty and Cultural Embeddedness as Innovation Constraints in the UK," GLO Discussion Paper Series 111, Global Labor Organization (GLO).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Daniel Arribas-Bel & Peter Nijkamp & Jacques Poot, 2014. "How Diverse can Spatial Measures of Cultural Diversity be? Results from Monte Carlo Simulations on an Agent-Based Model," Tinbergen Institute Discussion Papers 14-081/VIII, Tinbergen Institute.
    2. Nijkamp, Peter & Poot, Jacques, 2015. "Cultural Diversity: A Matter of Measurement," IZA Discussion Papers 8782, Institute of Labor Economics (IZA).
    3. Zhiling Wang & Thomas de Graaff & Peter Nijkamp, 2018. "Barriers of Culture, Networks, and Language in International Migration: A Review," REGION, European Regional Science Association, vol. 5, pages 73-89.
    4. Ferrucci, Edoardo & Lissoni, Francesco, 2019. "Foreign inventors in Europe and the United States: Diversity and Patent Quality," Research Policy, Elsevier, vol. 48(9), pages 1-1.
    5. Annie Tubadji & Peter Nijkamp, 2015. "Cultural impact on regional development: application of a PLS-PM model to Greece," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 54(3), pages 687-720, May.
    6. Mare, David C. & Pinkerton, Ruth M. & Poot, Jaques, 2015. "Residential Assimilation of Immigrants: A Cohort Approach," Motu Working Papers 290580, Motu Economic and Public Policy Research.
    7. Moritz Meister & Annekatrin Niebuhr, 2021. "Comparing ethnic segregation across cities—measurement issues matter," Review of Regional Research: Jahrbuch für Regionalwissenschaft, Springer;Gesellschaft für Regionalforschung (GfR), vol. 41(1), pages 33-54, February.
    8. Bøg, Martin, 2007. "Is Segregation Robust?," MPRA Paper 8774, University Library of Munich, Germany.
    9. Rinku, 2023. "Linkage of Cultural and Gender Diversity with Productivity in Chikankari Industry of Lucknow," Journal of Development Policy and Practice, , vol. 8(1), pages 43-54, January.
    10. David C. Maré & Jacques Poot, 2019. "Valuing cultural diversity of cities," Motu Working Papers 19_05, Motu Economic and Public Policy Research.
    11. Stefania Vitali & Mauro Napoletano & Giorgio Fagiolo, 2013. "Spatial Localization in Manufacturing: A Cross-Country Analysis," Regional Studies, Taylor & Francis Journals, vol. 47(9), pages 1534-1554, October.
    12. Robert Bifulco & Helen F. Ladd & Stephen Ross, 2007. "Public School Choice and Integration: Evidence from Durham, North Carolina," Working papers 2007-41, University of Connecticut, Department of Economics, revised Jun 2008.
    13. Fabien Candau, 2008. "Entrepreneurs' Location Choice And Public Policies: A Survey Of The New Economic Geography," Journal of Economic Surveys, Wiley Blackwell, vol. 22(5), pages 909-952, December.
    14. Devereux, Michael P. & Griffith, Rachel & Simpson, Helen, 2007. "Firm location decisions, regional grants and agglomeration externalities," Journal of Public Economics, Elsevier, vol. 91(3-4), pages 413-435, April.
    15. Tubadji, Annie & Nijkamp, Peter, 2016. "Impact of Intangible Cultural Capital on Regional Economic Development: A Study on Culture-Based Development in Greece," Journal of Regional Analysis and Policy, Mid-Continent Regional Science Association, vol. 46(01).
    16. Mare, David C. & Coleman, Andrew, 2011. "Estimating the determinants of population location in Auckland," Motu Working Papers 291434, Motu Economic and Public Policy Research.
    17. Miguel Angel Quiroga Suazo, 2002. "Agglomeration economies: influence on the distribution of foreign investment in Chile," Estudios de Economia, University of Chile, Department of Economics, vol. 29(1 Year 20), pages 139-163, June.
    18. Patrick Bayer & Robert McMillan, 2005. "Racial Sorting and Neighborhood Quality," NBER Working Papers 11813, National Bureau of Economic Research, Inc.
    19. Maria Dav? & Isidora Barbaccia, 2015. "Measuring agglomeration by spatial effects: a proposal," RIVISTA DI ECONOMIA E STATISTICA DEL TERRITORIO, FrancoAngeli Editore, vol. 2015(1), pages 44-70.
    20. Frank Bickenbach & Eckhardt Bode, 2008. "Disproportionality Measures of Concentration, Specialization, and Localization," International Regional Science Review, , vol. 31(4), pages 359-388, October.

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:sae:envira:v:48:y:2016:i:10:p:2046-2066. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: SAGE Publications (email available below). General contact details of provider: .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.