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Arctic Yearbook 2014
Creative Capital and Economic Development in the Arctic: Evidence
The centrality of creative capital (CC) in regional reinvention in the periphery appears to be
especially important in respect to breaking with path-dependency and facilitating regional breakthrough. Community-level research conducted in peripheral areas, mostly outside the Arctic,
squarely points to a pivotal role of creativity (spanning beyond education, experience or technical
expertise or any other “traditional” attributes of human capital) in local economic success. For
example, the study of local innovation in northern Scandinavia stressed “the importance of key local
actors in innovative processes that take place in remote regions”. The authors concluded, “almost
every innovation has had a clear core agent to manage the process. Very often this agent, initiator
and ‘engine’ of the process has been a local person, who has committed him/herself to the
development of a new idea” (Aarsæther 2004: 244). Similar evidence has been cited in other
marginal regions (e.g. Hayter et al. 1994; Stohr 2000; Petrov 2011), where members of the creative
class, particularly entrepreneurs and inventors, have been credited with revitalizing economies in
their communities. All these suggest that the creative class is an important and organic ingredient of
local development in the periphery.
Figure 1 presents Talent Index, Leadership Index and Bohemia Index maps for the circumpolar region.
The indices are calculated at the regional level. First of all, it is evident that most Arctic regions have
relatively weak CC. At the same time, there are areas that have high TI, LI and BI. In particular,
Yukon, certain parts of Russia (e.g., Murmansk and Yamal-Nenets regions) and northern
Scandinavia demonstrate levels of TI near or exceeding 1.0 (i.e. respective national averages). In fact,
Yamal-Nenets Okrug and Kamchatka Oblast’ were ranked 9th and 10th among top Russian regions
in 2002. In contrast, many areas with a majority or significant proportion of Indigenous population
tend to exhibit lower levels of TI, pointing to a persistent education gap between the two groups of
Arctic residents (see a more in-depth overview of this in Hirshberg & Petrov 2014). At the same
time, some Arctic regions register a remarkably high LI [a pattern observed in other studies (e.g.,
Petrov & Cavin 2013)]. The highest indices are associated either with larger urban and administrative
centers or with very remote and sparsely populated regions. The geographic distribution of BI
largely reflects the prevalence of Indigenous population. Most Arctic regions exceed national
baselines in relative proportion of residents with occupations in arts and culture suggesting a
presence of cultural capital and a considerable potential of Arctic cultural economy. In Russia,
Taimyr, Koryak, Chukotka Okrugs and Republic of Yakutia ranked among top 10 regions in terms
of BI in 2002.
If CC metrics are well documented at the regional level, data constraints limit our ability to measure
CC at the municipal level. The educational attainment data required for computing Talent Index are
mostly accessible. TI is also the most directly comparable indicator (as it is not based on occupation
classifications). At the same time, occupational characteristics of population are available only
fragmentarily. As a result, the city-level analysis focuses on TI. It includes Arctic cities selected
based on population (generally exceeding 20,000) and “regional importance” (all regional capitals, if
available, are included).
Petrov