This thesis investigates the impact of interregional connectivity on the development and dynamics of regions. Connectivity can manifest in various forms, including physical transport infrastructure and the capacity to forge connections rooted in cultural similarities, shared history, and common economic activities. These connections facilitate the movement of people and goods across different distances, thereby shaping economic interactions between territories and their economic conditions. The thesis focuses on three main dimensions of interregional interactions: trade, innovation collaborations, and commuting patterns of workers.
Chapter 1: Market Proximity and Regional Development
The first chapter examines the significance of market access in explaining intranational disparities in regional development. An accessibility index is constructed to represent the trade potential of each subnational region across countries globally. This index incorporates the consumption capacities of regions, their transport costs to others, as estimated by physical proximity and geographical constraints, as well as cultural and economic proximity. The findings reveal that greater proximity between regions enhances trade, which subsequently influences their level of development. Additionally, the study evaluates the varying effects of proximity on core versus peripheral regions.
Chapter 2: High-Speed Rail and Innovation Collaborations
The second chapter explores the consequences of improved regional connectivity, specifically through the introduction of high-speed rail (HSR) lines that have markedly reduced travel times between cities. The objective is to assess how these changes affect innovation collaborations among inventors in mainland France. To accomplish this, a database documenting the evolution of train travel times in France since 1980—prior to the first HSR line—is compiled. Furthermore, a database of French patents is used to identify collaborative efforts among inventors. The results indicate that reduced travel times stimulate both the quantity and quality of innovations, expanding the scope of interregional collaborations. However, these effects are concentrated, as star inventors and the most developed regions benefit the most.
Chapter 3: Methodology for Train Travel Time Data
Extending the analysis from Chapter 2, Chapter 3 presents the methodology for constructing a dataset of train travel times in France from 1980 to 2017. We combine current SNCF schedules with the opening dates of HSR lines and econometrically estimate train speeds by technology. For railways not yet served by HSR in a given year, we assume normal interregional train speeds. Using the Dijkstra algorithm, we then calculate the shortest travel times between cities for each year, from before the first HSR line opened to after the last. A validation exercise confirms the reliability of the resulting dataset.
Chapter 4: Worker Mobility and Commuting Patterns
The fourth chapter investigates worker mobility by focusing on commuting patterns in mainland France. The main goal is to evaluate the effect of reduced travel times on commuting behavior. This analysis employs the train travel time database from Chapter 3, along with data from the "Panel Tous Salariés" of INSEE, to measure interregional worker mobility related to employment. It also explores key factors influencing commutes and examines the combined influence of telecommuting feasibility. The findings highlight an increase in long-distance commutes, enabled by reduced train travel times. This effect is further amplified by improvements in internet coverage within residential departments, illustrating the complementarity between telecommuting and the HSR network and explaining the growth in long-distance commuting.