Ruiz Mejia, Celia (2021) Essays in Urban, Labor and Transport Economics. Toulouse School of Economics (Toulouse).

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Abstract

This paper measures the role of spatial mismatch within Metropolitan France. We take advantage of a rich data infrastructure combining individual registrations in unemployment with a sector - and location - specific job accessibility measure, as well as socioeconomic, demographic and municipality characteristics. We identify the effect of local accessibility to job opportunities on the probability to find a job for the population of French job-seekers registering in unemployment during the first quarter of 2015, who we follow until 2019. Our results give credence to the spatial mismatch hypothesis. We find that moving from a municipality in the 10th percentile of the accessibility distribution to one in the 90th percentile, increases the individual probability of finding a job by 5.2%. Further, we document that this impact is significantly different across education and qualification groups, where low educated and low qualified job-seekers are significantly more affected than their educated and qualified counterparts. We descriptively show that this gap can possibly be explained by the higher ability of high educated and/or qualified to move across labor markets. The Toulouse metropolitan area (TMA) have experienced major changes in the recent years: a relative decentralization of population and employment from the Central Business District (CBD) towards subcenters, an increase of employment concentrations outside the CBD, and a steeper wage growth of out-CBD areas. Therefore, this paper aims at investigating the role of transport infrastructure and agglomeration externalities on these observed patterns. Firstly, I explore the influence of multi-modal transportation infrastructure on the spatial distribution and growth of population and employment for distinct employment categories- sectors and occupations- and for areas close to subcenters. Secondly, I analyze the role of agglomeration economies on the emerging development of wages in out-CBD areas. With this objective, I estimate for the first time in the literature, the heterogeneity of agglomeration externalities crosswise the TMA, and across the sectors and occupations within them. In both investigations, I deal with endogeneity concerns by using an instrumental variable approach based on historical instruments. The most important results suggest that, firstly, transport infrastructure significantly impacts the location of employment and population. Secondly, transport infrastructure foster employment growth, especially in the proximity of employment subcenters. This implies that infrastructure promote the decentralization of employment. However, I cannot conclude the same for population. Instead, population growth is only affected by transport in the short-term and in the vicinity of infrastructure. Finally, agglomeration externalities only exist within IRIS codes close to employment centers, and the highest externalities are found around subcenters. This suggests that the emergence of agglomeration externalities plays a crucial role in the economic development of subcenters. The objective of this paper is to estimate the extent of agglomeration externalities taking into account the direct and indirect impacts of transport exposure on productivity. To do so, we take advantage of a rich data infrastructure that combines very fine georeferenced infra-municipality data on more than one million employees with detailed data on the public-transport and road networks of a typical European metropolitan area, namely the Toulouse Metropolitan Area (TMA). We recover the productivity effects of agglomeration and transport measures by the implementation and estimation of a wage determination model in two stages. The first stage assesses the importance of industrial concentration and employees’ characteristics against true productivity differences across zones on the average of local industrial wages. […]

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