Julie Le Gallo

Evaluating the Temporal and Spatial Heterogeneity of the European Convergence Process, 1980-1999

In this paper, we suggest a general framework that allows testing simultaneously for temporal heterogeneity, spatial heterogeneity and spatial autocorrelation in beta-convergence models. Based on a sample of 145 European regions over the 1980-1999 period, we estimate a Seemingly Unrelated Regression model with spatial regimes and spatial autocorrelation for two sub-periods: 1980-1989 and 1989-1999. The assumption of temporal independence between the two periods is rejected and the estimation results highlight the presence of spatial error autocorrelation in both sub-periods and spatial instability in the second sub-period, indicating the formation of a convergence club between the peripheral regions of the European Union.

Spatial Analysis of Employment and Population Density: The Case of the Agglomeration of Dijon 1999

The aim of this paper is to analyze the intraurban 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. To that purpose, we use a sample of 136 observations at the communal and at the IRIS (infraurban 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 identiÞcation 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.

On the property of diffusion in the spatial error model

The aim of this paper is to illustrate the property of global spillover effects in the first-order spatial autoregressive error model and the associated diffusion process of spatial shocks. An application is provided on a sample of 145 regions over 1989–1999 and highlights the most influential regions.

Employment Density in Ile-de-France: Evidence from Local Regressions

In recent decades, cities have experienced a particularly intense phase of urban sprawl. Urban growth has been characterized by the spatial concentration of population in urban areas and the concomitant extension of those urban areas (Nechyba and Walsh 2004). Urban sprawl has also been accompanied by major reorganizations of urban areas with regard to the location choices of households and firms. More specifically, most cities in developed countries have experienced several waves of suburbanization of economic activities: “an economic definition of suburbanization is a reduction in the fraction of a metropolitan area’s population or employment that is located in the central city (corresponding to increased activity in surrounding suburbs)” (Mills 1999). Suburbanization of economic activities has an impact on urban structure: cities are not exclusively organized with a Central Business District (CBD) around which land values, employment, and population densities decrease with distance. On the contrary, they are more and more characterized by a polycentric organization: employment is concentrated in several centers within urban areas. Strategic activities (headquarters and high-order producer services) play a major role in this process by locating themselves selectively in these various centers. The development of peripheral employment centers – where a significant proportion of these activities are located, reproducing the functions of the CBD – is accordingly viewed as the decline of the CBD (Stanback 1991).

Progress in Spatial Analysis: Introduction

With its roots in geography and regional science spatial analysis has experienced remarkable growth in recent years in terms of theory, methods, and applications. The series of books, that in the past decade have collected research in spatial analysis and econometrics, provide both documented evidence and a powerful platform to further this upwards trend. Among the collections that have done so stand those compiled by Anselin and Florax (New Directions in Spatial Econometrics, 1994), Fischer and Getis (Recent Developments in Spatial Analysis, 1997), and Anselin, Florax and Rey (Advances in Spatial Econometrics, 2004). In the spirit of this series of volumes, the present book aims at promoting the development and use of methods for the analysis of spatial data and processes. Traditionally, the core audience for the spatial analysis literature has been found in the Quantitative Geography and Regional Science communities, but also increasingly within the allied disciplines of Spatial and Regional Economics, Urban and Regional Planning and Development, Civil Engineering, Real Estate Studies, and Epidemiology, among others. Previous edited volumes, in particular the two spatial econometrics collections cited above, tended to emphasize, in addition to theoretical and methodological developments, economics and regional economics applications. In this book, we have made an attempt to capture a broader cross-section of themes, to include fields where spatial analysis has represented in recent years a boon for applications, which have in turn encouraged further technical developments. Besides the disciplines represented in previous collections of papers, up-and-coming areas that are seen to be making more extensive use of spatial analytical tools include transportation and land use analysis, political and economic geography, and the analysis of population and health issues. In order to provide a faithful picture of the current state of spatial analysis it is also our wish to present recent theoretical and methodological developments. Together, this collection of theoretical and methodological papers, and thematic applications, will project, we hope, the image of a thriving and dynamic field, with wide-ranging intellectually stimulating challenges, and rich opportunities for applied research that promises to promote and advance data analysis in a variety of fields.