SPATIAL ANALYSIS OF EMPLOYMENT AND POPULATION DENSITY: THE CASE OF THE AGGLOMERATION OF DIJON, 1999
Catherine Baumont,
Cem Ertur and
Julie Le Gallo
Urban/Regional from University Library of Munich, Germany
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.
Keywords: Bayesian spatial econometrics; exploratory spatial data analysis; outliers; population density; spatial autocorrelation; spatial heterogeneity; employment subcenters (search for similar items in EconPapers)
JEL-codes: C11 C21 C52 R12 R14 (search for similar items in EconPapers)
Date: 2003-10-07
New Economics Papers: this item is included in nep-geo and nep-ure
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Persistent link: https://EconPapers.repec.org/RePEc:wpa:wuwpur:0310003
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