Transport infrastructures and employment growth in the Paris metropolitan margins
Introduction
The role of transport in local employment growth has been widely discussed in recent decades (Blumenberg and Ong, 2001, Boarnet, 1995, de Vor and de Groot, 2010, Giuliano et al., 2011, Giuliano et al., 2007, Hoogstra and van Dijk, 2004, Redfearn and Giuliano, 2008, Zhang and Guldmann, 2010). Jobs have become more decentralised, cities have undergone a polycentric-based expansion rather than a random sprawling, with face-to-face contacts and agglomeration externalities remaining predominant. Beyond some main determinants such as specialisation (Henderson, 2003, Marshall, 1920) and diversity (Glaeser, 1999, Jacobs, 1969), the role played by transport infrastructures has remained controversial, largely because it raises problems of endogeneity in urban areas (Chandra and Thompson, 2000, Turner, 2009). Endogeneity is a major concern when a predictor (like the existence of an infrastructure) is a consequence of the phenomenon it is supposed to explain.
This debate, however, does not affect metropolitan margins, which have been rather overlooked by the research community. Most metropolitan jobs are usually located in the major centres, and the most common concern of metropolitan authorities is not to let employment scatter in sparsely populated areas. Yet there are several reasons to focus on this subject, even though small numbers of jobs are involved. First, understanding employment growth in metropolitan margins may allow for a better knowledge of the suburbanisation process, and for more adequate decisions in terms of local economic development (Baum-Snow, 2007). Second, it is useful to know whether the existing infrastructure (motorways, regional express trains, airports) provides opportunities for job creation in unlikely geographical areas. On this matter, a lively debate has emerged recently in Paris about the location of the future bypass mass rapid transit. The future stations might partly be built in almost empty areas: the main opposing arguments have focused on the possible creation of new real estate opportunities or, conversely, to the futility of stations located in “potatoes fields”.1 However, the debate has remained fairly ideological and poorly informed by scientific findings. Third, metropolitan margins are an excellent study area to clarify the role of transport infrastructures in an environment where endogeneity cannot be highlighted, for infrastructure is usually received as an exogenous event (Chandra and Thompson, 2000), rather than a response to local previous growth. Moreover, externalities related to the concentration of activities, to their diversity or to specialisation are not likely to be explanatory factors, since few firms (if any) are located there. As such, measuring the benefits of transport infrastructures in places where urban advantages are missing may provide a clearer view on specific transport effects. A fourth and specifically European reason involves the diversity of existing transport modes: while the North-American literature focuses largely on motorways (Baum-Snow, 2007, Boarnet, 1995, Boarnet and Haughwout, 2000, Ewing, 2008a, Rothenberg, 2009, Ryan, 2005), it is worth questioning the role of regional rail networks that have been highly developed in European conurbations.
Focusing on peripheral areas with small numbers of jobs, this paper aims to test the assumption that the areas located near transportation infrastructures were more likely to undergo employment growth over a 15-year period (1993–2008). Section 2 presents a brief literature review on this issue. Section 3 includes a presentation of data and method. Results are shown in Section 4. Section 5 concludes.
Section snippets
Linking transport infrastructures to employment growth
Transport cost is at the heart of all location theories (Glaeser and Kohlhase, 2004, Krugman, 1991b, McCann and Shefer, 2004, Rietveld and Vickerman, 2004). It is a convergence point of Weberian theory (McCann and van Oort, 2009, Weber, 1909), the neo-classical approach (Boarnet and Haughwout, 2000), and New Geographical Economics that emphasise the role of resource pooling in firm agglomeration (Fujita and Thisse, 2002, Krugman, 1991a, Krugman, 1991b, Polèse and Shearmur, 2009). Among a large
Unistatis database and study area
In order to analyse the role of transport infrastructure in local employment growth in urban margins, a municipal-level annual inventory of private sector jobs and establishments (not firms) in the Île-de-France region was used. Called Unistatis, it does not include public employment, which represents about 1.5 million jobs. Our analysis was therefore confined to the so-called productive sectors, which accounted for 74% of regional employment in 2008 (INSEE data). This was not problematic,
Results on municipal employment growth
Estimation results are shown in Table 5. It is worth mentioning first that the logit model fits the data well. All chi-square statistics are significant and the values for Nagelkerke’s R2 are always higher than 0.233 (except for one group), which is a reasonable percentage in logistic regression. All the models show a high concordance percentage, at least equal to 72.7%. Multicollinearity was evaluated using a multiple regression procedure that included a variance inflation option (VIF).
Estimation results across industries
As a second step, within each jobs category we ran the logistic regression model for sub-groups of the data set as classified by industry. Several areas did not have any jobs in a given industry during the whole period. It would therefore have made no sense to include them in the model. In order to ensure that all municipalities included in the models had a non-zero number of jobs in all industries in 1993, only 10% of the municipalities (those with the highest total employment growth) were
Conclusion
Among the abundant literature on transportation infrastructures and local employment growth, metropolitan areas have received considerable attention, but less attention has been paid to metropolitan margins. Based on a logistic regression model, our main objective was thus to assess the role of transportation infrastructures in dramatic employment growth in the small communities located there. Overall, the impact of infrastructures differed highly across industries, job categories and types of
Acknowledgements
This research was funded by Île-de-France Region under R2DS programme (R2DS-AAP-2010). It was led by Laboratoire Ville, Mobilité, Transports (LVMT), UMR T-9403 (École des Ponts ParisTech, IFSTTAR, Université Paris-Est) and by SAREL (Spatial Analysis and Regional Economics Laboratory), INRS, Centre Urbanisation, Culture et Société, Montréal (QC), Canada.
I thank Marie-Hélène Massot (LVMT), Richard Shearmur (SAREL), and Laurent Terral (LVMT), for their assistance with the overall project, and the
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