| Summary: | Whereas no prior contribution has focused on the case of a medium-sized city in a developing country, such as Mexico, to explore how urban structure and its expansion has affected the spatial distribution of employment, three distinct, but related papers were developed, which combine urban economics literature and spatial sciences techniques to fill this gap and provide new evidence. The first paper, entitled "Spatial Distribution of Employment in Hermosillo, 1999 and 2004" identifies where employment subcenters are. Testing the presence of spatial effects, it concludes that an incipient process of employment suburbanization has taken place; however, the city still exhibits a monocentric structure. As a complement, a second paper, "Employment Density in Hermosillo, 1999-2004: A Spatial Econometric Approach of Local Parameters" tests if the Central Business District (CBD), despite suburbanization, maintains the traditional attributes of attracting activities and influencing the organization of employment around it. The CBD is still attractive, but its influence varies across space and economic sector, conclusions that were masked by global estimations. Thirdly, a study was essential to uncover how important is the urban structure and the suburbanization of jobs in explaining the dispersion resulting of households and workplaces (commuting). The paper entitled "Commuting in a Developing City: The Case of Ciudad Obregon, Mexico" examines this issue. To take advantage of the commuting information available, the study area was switched. In general, the results are consistent with those suggested by urban economics; moreover, the inclusion of workplace characteristics was a novelty to model commuting behavior and proves that space matters. Additionally, new evidence was provided to the field of spatial science through the applications of techniques able to expose the spatial effects associated with the distribution of employment, more specifically, the Exploratory Spatial Data Analysis(ESDA), Geographically Weighted Regression (GWR) with spatial effects, as well as the generalized multilevel hierarchical linear model (GMHL) were used. The new findings produced for this dissertation provide a more comprehensive understanding of urban dynamics and could help to improve the planning process. It is hoped that this dissertation will contribute to that development as well as stimulate further research.
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