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Spatial Analysis Of Employment And Population Density: The Case Of The Agglomeration Of Dijon, 1999

Author

Listed:
  • Catherine Baumont

    (LATEC)

  • Cem Ertur

    (LATEC)

  • Julie Le Gallo

    (IERSO)

Abstract

The aim of this paper is to analyze the intra-urban spatial distributions of population and employment in the agglomeration of Dijon (regional capital of Burgundy, France). We study whether this agglomeration has followed the general tendency of job decentralization observed in most urban areas or whether it is still characterized by a monocentric pattern. In that purpose, we use a sample of 136 observations at the communal and at the IRIS (infra-urban statistical area) levels with 1999 census data and the employment database SIRENE (INSEE). First, we study the spatial pattern of total employment and employment density using exploratory spatial data analysis. Apart from the CBD, few IRIS are found to be statistically significant, a result contrasting with those found using standard methods of subcenter identification with employment cut-offs. Next, in order to examine the spatial distribution of residential population density, we estimate and compare different specifications: exponential negative, spline- exponential and multicentric density functions. Moreover, spatial autocorrelation, spatial heterogeneity and outliers are controlled for by using the appropriate maximum likelihood, generalized method of moments and Bayesian spatial econometric techniques. Our results highlight again the monocentric character of the agglomeration of Dijon.

Suggested Citation

  • Catherine Baumont & Cem Ertur & Julie Le Gallo, 2003. "Spatial Analysis Of Employment And Population Density: The Case Of The Agglomeration Of Dijon, 1999," Urban/Regional 0310003, University Library of Munich, Germany.
    • Handle: RePEc:wpa:wuwpur:0310003
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    Cited by:

    1. Karsten Rusche, 2010. "Quality of life in the regions: an exploratory spatial data analysis for West German labor markets," Review of Regional Research: Jahrbuch für Regionalwissenschaft, Springer;Gesellschaft für Regionalforschung (GfR), vol. 30(1), pages 1-22, February.
    2. Miquel-Àngel García-López, 2010. "The Accessibility City. When Transport Infrastructure Matters in Urban Spatial Structure," Working Papers XREAP2010-01, Xarxa de Referència en Economia Aplicada (XREAP), revised Feb 2010.
    3. Rafael Henrique Moraes Pereira & Vanessa Nadalin & Leonardo Monasterio & Pedro Henrique Melo Albuquerque, 2012. "Quantifying Urban Centrality: A Simple Index Proposal and International Comparison," Discussion Papers 1675a, Instituto de Pesquisa Econômica Aplicada - IPEA.
    4. Rachel Guillain & Julie Le Gallo & Céline Boiteux-Orain, 2004. "The evolution of the spatial and sectoral patterns in Ile-de-France over 1978-1997," ERSA conference papers ersa04p59, European Regional Science Association.
    5. Jaume Masip Tresserra, 2012. "Does Employment Density death? Towards a new integrated methodology to identify and characterize Sub-Centres," ERSA conference papers ersa12p71, European Regional Science Association.
    6. Karsten Rusche & Uwe Kies & Andreas Schulte, 2011. "Measuring spatial co-agglomeration patterns by extending ESDA techniques," Review of Regional Research: Jahrbuch für Regionalwissenschaft, Springer;Gesellschaft für Regionalforschung (GfR), vol. 31(1), pages 11-25, June.
    7. Nica, M., 2010. "Small Business Clusters in Oklahoma: MAR or Jacobs Effects?," Regional and Sectoral Economic Studies, Euro-American Association of Economic Development, vol. 10(2).
    8. Jaume Masip Tresserra, 2012. "Identifying the Employment and Population Centers at regional and metropolitan scale: The Case of Catalonia and Barcelona," ERSA conference papers ersa12p70, European Regional Science Association.
    9. Arauzo Carod, Josep Maria, 2015. "Agglomeration vs. dispersion of economic activities in the districts of Paris," Working Papers 2072/246965, Universitat Rovira i Virgili, Department of Economics.
    10. Ivan Muñiz & Miguel-Àngel García-López, 2012. "Chaos and order in the contemporary city. The impact of urban spatial structure on population density and commuting distance in Barcelona, 1986-2001," Working Papers wpdea1207, Department of Applied Economics at Universitat Autonoma of Barcelona.
    11. Genevieve Giuliano & Christian Redfearn, 2005. "Not all sprawl - Evolution of employment centers in Los Angeles, 1980 - 2000," ERSA conference papers ersa05p686, European Regional Science Association.
    12. Genevieve Giuliano & Christian Redfearn & Ajay Agarwal & Chen Li & Duan Zhuang, 2005. "Not All Sprawl: Evolution of Employment Concentrations in Los Angeles, 1980-2000," Working Paper 8589, USC Lusk Center for Real Estate.
    13. Marie-Hélène Vandersmissen & Anne-Marie Séguin & Marius Thériault & Christophe Claramunt, 2009. "Modeling propensity to move after job change using event history analysis and temporal GIS," Journal of Geographical Systems, Springer, vol. 11(1), pages 37-65, March.
    14. Yena Song & Keumsook Lee & William Anderson & T. Lakshmanan, 2012. "Industrial agglomeration and transport accessibility in metropolitan Seoul," Journal of Geographical Systems, Springer, vol. 14(3), pages 299-318, July.
    15. Paolo VENERI, 2010. "The Identification of Sub-centres in Two Italian Metropolitan Areas: a Functional Approach," Working Papers 343, Universita' Politecnica delle Marche (I), Dipartimento di Scienze Economiche e Sociali.
    16. Claude LACOUR & Sylvette PUISSANT, 2008. "Medium-Sized Cities and the Dynamics of Creative Services," Cahiers du GREThA (2007-2019) 2008-08, Groupe de Recherche en Economie Théorique et Appliquée (GREThA).

    More about this item

    Keywords

    Bayesian spatial econometrics; exploratory spatial data analysis; outliers; population density; spatial autocorrelation; spatial heterogeneity; employment subcenters;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • R12 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Size and Spatial Distributions of Regional Economic Activity; Interregional Trade (economic geography)
    • R14 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Land Use Patterns

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