Serrano, Francisco Antonio
City competitiveness and attractiveness: a new approach to evaluate economic development in Mexican cities.
PhD thesis, University of Glasgow.
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This research attempts to build a model to evaluate the economic development level of cities using a set of factors associated to the concepts of competitiveness and attractiveness. Traditionally competitiveness has only been related to rankings with a very limited contribution to regional and urban economics. At the same time, the concept of attractiveness is gaining more attention from economists who now define it in terms of competition for capital, people and government resources. Attractiveness is now linked to stages of economic growth to provide a broader framework to analyse the process in which cities are immersed to reach a higher standards of quality of life for their inhabitants.
It is claimed that cities do compete with each not just for resources or people, but also for great events, resources from international organisations and institutions, prizes, infrastructure of high calibre, and even for an image among the public. On the other, attracting investment is not just reduced to companies from any economic sector. The theory suggests that making the city more attractive implies a competitive process to create the appropriate conditions for business to work in a stable environment. “Redefining” the cities’ image is useless if it is not accompanied by a total reengineering of the government’s activities, where support for business plays an important role.
The empirical analysis begins with the presentation of the economic asymmetries among the sample of 40 Mexican cities. It is concluded that the economic policies of the central government in the last ten years have benefited those places which were already rich. Evidence is presented using the factors and variables of competitiveness and attractiveness with secondary data in order to illustrate the magnitude of the asymmetries among cities.
In the second part of the analysis, two econometric models are presented. The first one intends to “capture” the variance of the 72 variables used in the experiment. The objective is to build an equation portraying urban economic development. However, as it was expected, the high statistical correlation among the variables led to a model including only 9, very few if the model is intended for simulating the impacts of decisions made by local authorities. The second model is constructed using all the factors and variables with the idea of being able to simulate as many as possible urban policies in a dynamic context. The results provided by the model are consistent with the results presented in the first part of the empirical analysis and seem to fit well the data for the sample selected.
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