French creative clusters: An exploratory spatial data analysis - Chantelot Sébastien (European Regional Science Association (ERSA), 2010)
Since Florida (2002b) revealed the importance of creative skills on economic growth, the notion of "creative class" has been deepened to analyze factors that shape the geography of talent of creative people. In spite of some strong correlations between artistic or cultural vibrancy, Third places, diversity, and the presence of huge constellations of creative people in cities (Chantelot, 2009), urban size and economic opportunities appears to be the real reasons that encourage its mobility in Europe (Andersen and Lorenzen, 2009 ; Hansen and al., 2009 ; Grossetti, 2009). However, if a bulk of literature emerged in Northern Europe on these questions, the geography of the creative class in France really needs to be investigated. That's why we propose here an original approach lying on Exploratory Spatial Data Analysis. This paper analyses the agglomeration patterns for creative class in France in 1999 and 2006. We adopt a methodology allowing the measurement of the degree of spatial agglomeration and the identification of location patterns (Guillain and Le Gallo, 2008) of creative people. First, we compute the locational Gini coefficient and Moran's I statistics of global spatial autocorrelation. We show that these measures provide different but complementary information about the spatial agglomeration of the creative class. Second, we use the tools of Exploratory Spatial Data Analysis. Moran scatterplots and LISA statistics allow us to shed light on clusters of French creative cities and to see how the different groups of creative people (bohemians - creative pro - creative core) affect the cluster's structures. First, we find that creative class is highly concentrated in French cities, more than employment and population. Second, we identify and analyze several clusters of French creative cities that show virtuous path of creative people accumulation since 1990.
Keywords: C12; O18; R23; 330; Creative class; ESDA; location patterns; spatial autocorrelation; French districts