4. The geographic dimension

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This section examines whether patterns of employment for culture workers differ across the urban-rural spectrum. We hypothesize that culture workers are more likely to be employed by non-culture industries in large urban areas compared to rural settings. This expectation is rooted in the fact that many culture occupations are highly specialized. For example, architects and other design professionals often require years of post-secondary training. In general, it is easier for workers with very specialized skill-sets and knowledge to find employment in cities, where a large variety of employers are located. Thus, both culture workers and their employers benefit from being in urban areas, and especially larger urban centres. Hence, this section extends the national analysis by investigating how culture employment patterns in urban areas differ from rural regions.

To do this, we divided Canada into three regional groups: large cities (Census Metropolitan Areas), which have a population greater than 100,000; small cities (Census Agglomerations), which have a population greater than 10,000 but typically less than 100,000; and rural areas. Culture employment patterns in each of these regional groups were examined and compared. Table 6 reveals that culture workers are employed to the greatest extent in large cities, less in small cities and least in rural areas, as expected. The difference in the share of culture workers is particularly pronounced between large cities and smaller cities. Moreover, the share of culture workers out of the total workforce in large cities increased during the 1990s and particularly after 1996, a trend not seen for the other two geographic classes. This suggests that the creative knowledge and skills that culture workers possess are more applicable within large urban economies.

Table 6
Culture employment in the non-culture sector

There are two broad explanations for why large cities might have higher shares of culture workers compared to CAs and rural areas. The first is that CMAs, CAs and rural areas in general are very different in terms of the industries located in them. Large cities tend to have far more diversified economies while the economies of rural areas and small cities are more specialized.9 Thus the particular mix of industries present in large urban areas compared to smaller centres is potentially an important determinant of culture employment levels, especially in light of evidence in the previous section that culture workers are employed in great numbers in only certain Divisions. This effect is referred to as an "industry mix effect".

A second potential explanation is that firms and public agencies that are located in large cities might tend to hire more culture workers compared to similar employers in smaller cities and rural areas. This reflects the possibility that methods of producing goods and services, or the "production functions" for firms and public agencies, differ across the urban-rural spectrum, even within the same industry. Put another way, employment practices with regard to culture workers may differ between city and country. This second explanation is referred to as a "region effect" since it considers the influence of the region itself on employer behavior.

To determine the relative importance of the industry mix effect and the region effect, culture employment shares for CMAs, CAs and rural areas were decomposed for 1991 and 2001. The decomposition takes the following mathematical form:

The "s" terms are culture employment shares. The "Iij" term is a weight that measures the proportion of employment in a particular major group in a region (CMA, CA or rural) out of total employment in that region. The "i" term indexes each of the 74 non-culture major groups, and the "j" term indexes the particular region. The dot (•) indicates that the variable has been aggregated over that dimension. If the dot replaces "j", it means the variable has been aggregated across all regions and if it replaces an "i", all major groups are being aggregated. Hence, sj refers to the aggregate culture employment share across all major groups in region j.

The left-hand side of the equation measures the extent that the share of culture workers in the non-culture sector in region j deviates from the national average. The first term on the right hand side is the industry mix effect, and it will be positive if a particular region contains a mix of major groups in which culture workers happen to be employed to a greater extent than the particular mix of major groups across the entire national economy. The second term measures the region effect. It will be positive if employers utilize culture workers to a greater extent when they are located in a particular region relative to the national pattern. Table 7 presents the results of the decomposition.

The industry mix effect and the region effect are positive for CMAs but both are negative for CAs and rural areas in 1991 and 2001.10Hence, both effects contribute to the relatively lower numbers of culture workers seen in the non-culture sectors of small cities and rural areas. For CAs, the region effect is much greater than the industry mix effect, indicating that it is more important. Hence, the production functions for firms and public agencies differ between large and small cities concerning the use of culture occupations. In contrast, for rural areas, the region effect and the industry mix effect are roughly equal in importance; both effects are similar in magnitude in 1991 and 2001.

Table 7
Industry mix and region effects for culture employment shares in the non-culture sector

The results obtained for the region effect in the decomposition demonstrate that non-culture employers within the same major groups are more likely to rely on the skill-sets embodied in culture occupations when located in large cities rather than smaller regions. As hypothesized above, this result may reflect the greater availability of culture workers, many of which have highly specialized skills and knowledge, in large cities. Hence, the region effect is consistent with the notion that culture workers, along with the firms that employ them, benefit from being in large cities. Employers in rural settings and small cities, in contrast, would possibly have little choice but to outsource culture-related work (design work for example) to firms in cities due to the small culture workforce located outside of CMAs. This possibility could be investigated in future research.

The industry mix effect shows that the industrial structure in large urban settings is weighted towards those major groups that employ relatively larger numbers of culture workers compared to rural areas and small cities. This result would partially reflect the fact that high-end design work often occurs in cities and especially large cities. For example, it is advantageous for architectural firms, design firms and marketing firms to locate in large cities, close to a large number of potential clients. Also, manufacturing industries employ a significant number of culture workers, primarily in visual arts and design occupations. Since manufacturing plants tend to cluster in large cities, this would contribute to higher shares in CMAs relative to the other two geography classes. Finally, natural resource industries, which employ few culture workers, tend to be more prominent in rural and small urban economies. Thus, the positive industry mix effect seen for large cities and the negative effect for small cities and rural areas is intuitive. Also, the fact that the negative industry mix effect strengthens from small cities to rural areas further suggests that size matters; that is, the smaller an area's population, the less likely it will have an industry structure that supports large concentrations of culture workers.