EDA Journal Vol 12. No.1 Autumn 2019 | Page 10

ECONOMIC DEVELOPMENT QUARTERLY SKETCHING AUSTRALIA’S ARTISTIC LANDSCAPE ASHTON DE SILVA, SVETA ANGELOPOULOS AND JONATHAN BOYMAL Planners and policy makers worldwide have long been focussed on the concept of creativity and its contributions to local economic development. It is widely accepted that creativity is a driver of innovation and entrepreneurship. Notably, creative activity (of which Artistic production is one special type) is believed to contribute to more than just economic output; providing valuable social benefits resulting, in part, from its role in establishing local identity and character. Recently, we set about to sketch the Australian artistic landscape, in particular, we set ourselves the task to unveil the distribution of artists across the nation 1 . We used 2016 census data to identify each person who declared themselves as working in one of eleven types of artistic occupations as defined in the 2016 census: 1. Actors, Dancers and Other Entertainers 2. Music Professionals 3. Photographers 4. Visual Arts and Crafts Professionals 5. Art Directors, Media Producers & Presenters 6. Film, TV, Radio & Stage Directors 7. Authors, Book & Script Editors 8. Journalists & Other Writers 9. Fashion, Industrial & Jewellery Designers 10. Graphic, Web Designers, & Illustrators 11. Interior Designers This analysis provides insight into the character of the distribution artists residential choices (as a proxy for artistic human capital) at the local government level (LGA), beyond the traditionally known hubs of creative economic activity. WHY IS THIS IMPORTANT? Many academic studies indicate that the presence of creative human capital impacts local prosperity, promotes community cohesion, wellbeing, and has the potential to attract industries of all types. To get an in depth understanding of the distribution and density of creative capacity in Australia we require specificity and attention to the uniqueness of the type of art and the place itself which can shed light on common assumptions about artistic location patterns. This analysis helps inform arts policy makers about the appropriate mix between targeted place-specific programs and broader initiatives. CLUSTER ANALYSIS AND STRATIFICATION To do this we first employed a well-known statistical grouping procedure called Hierarchical Cluster Analysis where LGAs were grouped together according to the degree of their similarity. The process essentially forms groups by collecting together LGAs that are most similar (in terms of artists living in the area) whilst simultaneously maximising the differences between groups. Interestingly this procedure did not identify patterns of artists concentrating together across regions. In other words no conclusive results emerged in this stage. The results however did lead us to construct our own grouping algorithm. In contrast to the formal clustering approach which attempted to group LGAs according to the type of artist, we constructed a simple mathematical stratification classification system based on the presence of the relative extent to which the number of types of artists residing in an area. The analysis, in both applications were performed on what economists refer to as location quotients – these can be defined as the share residing artists in an area relative to the national average. Our constructed stratification of LGAs are based on five classifications: 1. No residing artists 2. Negligible levels of residing artists 3. Some types of artists residing en masse in the local community. 4. A majority number of types of artists are residing in the local community. 5. All artist types on mass are residing in the local community VOL.12 NO.1 2019 | 10