‘Creative Industries’ – An Incubator for Jobs
and Growth?
Empirical evidence from a case study for Vienna
Peter Mayerhofer, Peter Huber
Paper presented at the 14th International Conference of the ACEI,
Vienna, 6-9 July 2006
Abstract
The paper deals with job effects and firm dynamics in Vienna's Creative Industries. The
analysis is based on a large individual longitudinal matched employer-employee data set for
Austria, which allows tracking the job careers of 2.4 Mio employees in 400,000 firms over a
decade. We analyse employment evolutions in the different parts of the value added chain
in Vienna's CI and document the heterogeneity of the sector in terms of job and worker flows,
firm growth as well as entry/exit. The results confirm the function of Creative Industries as
incubator for firms and jobs, but question the notion of a homogeneous "cluster" Creative
Industries in Vienna.
– 2 –
1.
Background
Creative industries as the heterogeneous part of the economy that mass-produces goods
and services with artistic content (Towse, 2003) have shifted into the focus of interest of
cultural and economic policy in recent decades. Enabled by technological advances
(sound recording, film/video, internet, digitalisation), forms of mass (re)production and
commercialisation of artistic/cultural content were at first assessed sceptically in cultural
policy discourse (e.g. Adorno – Horkheimer, 1977). Since the early nineties at the latest, the
cultural pessimists’ postulation of a contrast between advanced and popular culture as well
as art and commerce has increasingly been questioned and synergies between art
production proper and downstream areas of distribution and reproduction started being
identified. Authors such as Towse (2001, 2003) or Cowen (1998) consider market mechanisms
as allies for art production and distribution.
From an economic perspective the importance of Creative Industries (in the following
referred to as CI) is substantiated on the one hand by the function of creativity and new
ideas as production factors in the information society. Similarly to technological innovations,
creative outputs (as information goods and services) are seen as important locational factors
of highly advanced knowledge societies. A region’s creative potential is considered of
decisive importance for the competitiveness of new activities (Howkins, 2001) or entire regions
(Florida, 2002). In addition, positive effects of investments in creative areas on quality of life,
identity building and attractiveness in international tourism markets are mentioned (European
Commission, 1998).
More importantly, economic policy hopes are pinned in particular on the supposedly high
growth and employment potentials of CI, which are assumed for the following reasons
(European Commission, 1998; UNCTAD, 2004):

On the final demand side, with incomes increasing, the high income elasticity of
products with cultural content fosters a favourable development of CI. Changes in
consumper preferences towards “experience” and “convenience” also promote
sales. Further, with increasing (voluntary and involuntary) free time, expenditure on
leisure, entertainment and culture increases. Changes in the age structure of the
population and increasingly better education have a similar effect.

As for intermediate consumption, the necessity of increased product differentiation
resulting from saturated markets creates demand for creative products. Further, with
the tertiary sector increasingly applying essential elements of the CI’s output (such as
– 3 –
design, advertising, marketing), the increasing service orientation of developed
economies supports the demand for relevant products and services.

On the supply side the dynamics of CI is promoted by technological innovations (such
as digital storage of sounds and images as computer files, their copying and
reproduction on the computer and their distribution via the internet), as they enable
new forms of product sales and reduce the costs of distribution networks.
It was in the late nineties and early two-thousands in particular that all these influences
contributed to the remarkable growth dynamics of creative industries at national and
international level1). For the next years, recent studies (PriceWaterhouseCoopers, 2003,
quoted in UNCTAD, 2004) forecast an annual growth of global value added of around 10
percent in relevant areas.
Against this background and considering that the activities pertaining to creative industries
benefit to a particularly high degree from locational advantages of urban areas and are
therefore concentrated in large cities (Pratt, 1997; DCMS, 2001; Wu, 2004), Vienna’s
economic policy endeavours to promote the development of creative industries as a cluster
of the regional economy (City of Vienna, 2004). In view of considerable challenges in the
regional labour market (Huber – Mayerhofer, 2005)2 the focus of interest is on the contribution
of CI to employment dynamics.
The present paper deals with the question whether CI really played their supposed role as a
job incubator for Vienna during the past decade. On the basis of a highly disaggregated
data set on dependent employment relationships in Vienna, the employment dynamics in
Viennese CI since Austria’s EU accession in the mid-90s is reconstructed. In the course of this,
the traditional analysis of employment stocks is extended by a detailed identification of flow
data in the relevant labour market.
1)
According to an analysis established by the European Economic and Social Committee (quoted in Unctad, 2004)
CI have shown growth rates of 5 to 20 percent in the OECD countries in recent years. In Austria the number of firms in
the core area of CI increased by a third in 1995-2000 and the number of dependent employees rose by 29 percent.
Value added increased by 41 percent in the same period (KMU-Forschung Austria – IKM, 2003).
2)
Vienna’s economic growth, which is perfectly satisfactory in comparison with other European cities, goes hand in
hand with increased requirements for modernisation and rationalisation at firm level. The requirements result from
Vienna’s geographical location at “Europe’s economic dividing line” to new competitors with considerable cost
advantages and are reflected by fast structural change and high productivity growth. Though favourable in terms of
competition, this productivity gain has its drawback in a low employment intensity of regional economic growth.
Thus, employment in Vienna has hardly increased since 1995 despite a markedly growing economy. Vienna has
meanwhile largely lost its excellent labour market position compared with other European cities (unemployment rate
2003: 7.7 percent, EU15: 8.1 percent).
– 4 –
2.
Framework of analysis and data set
There is no analytically deduced and generally accepted definition to serve as a basis of
statistical analyses of CI3). Empirical works supplement the narrow concept of “cultural
industries” by individual affirmative fields of technology (multimedia, software etc.), align the
considered sectors around the (of course more vague) concept of “creativity” as main input
factor (e.g. DCMS, 1998) or solve the problem of definition by referring to the importance of
“intellectual property” or “copyright” (e.g. Howkins, 2001).
The present analysis is based on the “Vienna definition” of creative industries developed by
Ratzenböck et al. (2004)4, which tries to comprehensively represent the entire value added
chain of creative industries, including both the creative core areas as well as upstream and
downstream sectors. Based on this and on contributions by Pratt (1997, 2004) CI are
understood as an interconnected production system, with activities of artistic creation
interacting with activities of reproduction and mass distribution and, in the ideal case,
stimulating each other. Thereby a highly complex and heterogeneous network of activities is
depicted, which is nevertheless considered as an entity in view of assumed interconnections
and common development logics. A subdivision of the entire area by the sectors involved
(architecture, the audiovisual sector, fine arts etc.) and by the position in the value added
chain (content origination, reproduction, exchange) allows for analyses also in view of
production logics.
A considerable problem in implementing such an approach, which is essentially “transversal”
to the sector categories of administrative statistics, is the construction of a convincing data
set. The necessity to clearly draw the lines between the individual activities within the CI value
added chain requires working at a highly disaggregated sector level. Sources of current
production statistics in manufacturing and services as well as the bulk of periodical general
censuses are excluded for reasons of survey methods and/or data protection. Therefore, our
analysis is based on the individual data set of the Federation of Austrian Social Security
Institutions, which has been available in an anonymised form for the years since 1995. Entries
in this data set are based on the obligatory registration of employment relationships upon the
start of employment. Along with the fact of employment and the point of time of its
beginning and end, a series of characteristics of the employment relationship and the
employee and employer involved are registered. This enables an analysis by income and
social security arrangements pertaining to the employment relationship, the employee’s age
and gender and the sector and size of the employer’s firm. The sectoral classification of the
latter is reliably coded down to the 4-digit level of NACE. As a result, a clear delineation of CI
according to the “Vienna definition” (Ratzenböck et al., 2004) is possible.
3)
For the development of the term CI cf. Towse (2001,2003), Brecknock (2004); Ratzenböck et al. (2004) or Hromatka
(2005).
4)
For the sectoral categorisation in this definition cf. table A1 in the annex.
– 5 –
The extent of the information content – that allows, after all, tracking the job careers of
around 2.4 million employees in some 400,000 firms annually over almost a decade – makes
this data set rather resource-intensive in handling and evaluation. In addition, on account of
its being a primarily administrative (and not a statistical) instrument of information it requires
laborious preparation (for details, see Huber – Mayerhofer, 2005). However, the workload is
justified by the results it can provide. For example, the data set allows for a highly
disaggregated view of the development of dependent employment in CI. In addition, the
possibility to combine employer-related information (e.g. firm size or sector) with personrelated information at an individual level reveals information on the relations between the
specific labour market of CI and its regional firm population.
However, despite its size, the data set applied does not allow a complete registration of all
persons working in the CI sector in Vienna. It takes into account all dependent employment
relationships (full-time and part-time), including those below the marginal earnings threshold,
and free services contracts and work contracts that are subject to registration with social
security. The data set lacks sufficient detailed information on the employment relationships of
civil servants and railway employees, making a complete representation of dependent
employment impossible. On account of this, some few areas (e.g. museums, libraries) are
under-reported, which influences the overall results only slightly, though. An essential
restriction, however, is the analysis’ exclusive focus on dependent employment relationships,
while omitting the self-employed and the free professions. Thus, types of independent,
project-related work and freelancing in a “grey area” (i.e. without social security) are not
registered5. Based on information from census data, this should result in an under-reporting of
the entire CI employment amounting to about one fifth (Mayerhofer – Huber, 2005).
Overall, therefore, our data set does not, despite its size, completely depict all types of
employment in Vienna’s CI. For dependent employment, however, which continues to be
the prevailing employment form and main target of employment policy, it is a unique source
of information and can therefore serve as a basis for a general, data-supported estimation of
the role of CI as job incubator.
3.
The importance of creative industries in Vienna’s employment system:
Regional strengths in all areas
A count of the employment relationships registered with the Federation of Austrian Social
Security Institutions gives an idea of the CI’s importance as a regional employer (table 1).
5)
However, the bulk of freelance work should be included in the data set through the consideration of free service
contracts and work contracts.
– 6 –
Table 1:
Dependent employment in Vienna’s creative industries
Total
Standard employment
Employment below
marginal earnings threshold
Free service contracts, work
contracts
Free service contracts and
work contracts below
marginal earnings treshold
Content
Origination
Reproduction
Exchange
Creative
Industries total
Absolute
38,186
19,281
49,481
106,949
Shares of Vienna in %
5.5
2.8
7.2
15.5
Absolute
32,189
18,598
43,086
93,872
Shares of Vienna in %
5.2
3.0
7.0
15.2
Absolute
2,542
388
3,796
6,726
Shares of Vienna in %
5.5
0.8
8.2
14.5
Absolute
1,981
223
1,129
3,332
Shares of Vienna in %
18.6
2.1
10.6
31.2
Absolute
1,475
72
1,471
3,018
Shares of Vienna in %
11.2
0.5
11.2
22.9
Source: Federation of Austrian Social Security Institutions; own calculations.
According to the latter, about 107,000 dependently employed persons belong to the
Viennese CI’s “production system” – as broadly outlined by the “Vienna definition” – in 2003,
representing about 15.5 percent of all employment relationships subject to social security
contributions in Vienna. Of these, almost 93,900 (87.8 percent) are full- or part-time
employments requiring full social insurance and thereby offer comprehensive coverage by
social security. “Atypical” employment relationships in Viennese CI are only slightly overrepresented. This is not least due to the comparably small importance of employment
relationships below the marginal earnings threshold in the reproducing areas of CI
(reproduction), where standard employment relationships are clearly prevailing. Free service
contracts and work contracts, in contrast, are comparably frequent in CI: Slightly less than
one third of this kind of employment in Vienna can be found in CI, in particular in content
origination and exchange.
In the value added chain, activities of distribution of artistic/creative content (exchange, 42.2
percent) and content production proper (content, 35,3 percent) play a decisively greater
role than reproduction in Vienna’s regional employment (figure 1). This can be interpreted as
a sign of the frequently deplored weakness of the processing of art- and culture-like output.
This weakness, in turn, has been attributed to the predominance of small-scale, undercapitalised businesses as well as to deficits in the processing know-how in many areas (above
all light music, film business, literature and publishing, fine arts, fashion, graphic arts and
design) (Ratzenböck et al., 2004). The unbalanced distribution of value added stages can be
attributed not least to the scarcity of locational advantages for industrial production in large
– 7 –
cities, a fact that has led to a marked tertiarisation of Vienna’s employment structure in
recent decades (Huber – Mayerhofer, 2005).
Figure 1: Composition of Vienna’s creative industries
Employment shares in percent, 2003
By sector
Software,
multimedia,
internet
19,3%
Advertising
5,2%
By value added stage
Architecture
7,6%
Audivisual
sector
19,1%
Fine arts
2,3%
Music
7,8%
Museums,
libraries
6,3%
Literature,
publishing, print
media
14,4%
Content
Origination
35,3%
Exchange
42,2%
Performing arts
and
entertainment
3,1%
Graphic arts,
fashion, design,
photography
14,8%
Reproduction
22,5%
Source: Federation of Austrian Social Security Institutions; own calculations
Still, the range of sectors within Vienna’s CI is dominated by technology-oriented areas, with
software/multimedia/internet and the audiovisual sector together responsible for almost 40
percent of jobs in Viennese CI. Along with these, the fields of literature/publishing/print media
and graphic arts/fashion/design, each making up about 14 percent of CI jobs, are important
employers in the city economy. The remaining groups are comparably small, with shares
between 2 percent (fine and performing arts) and 8 percent (music, architecture).
From a regional perspective, the data clearly confirm Vienna’s central role in Austria’s
creative industries: While in Vienna approximately 15.5 percent of all dependently employed
persons and 15.2 percent of all those in standard employment work in the CI sector, the
corresponding Austria-wide percentage is only 8.6 percent. This can partly be explained by
the regional concentration of relevant institutions in Vienna as the capital of Austria, but also
suggests that Vienna as “city of culture” has a particularly high creative potential in a
nationwide comparison. What strikes in this context is that Vienna’s (national) specialisation
on activities of creative industries can be seen both at all stages of the value added chain as
well as practically all related sectors, as the location quotient reveals (figure 2).
The location quotient for the total of creative industries has been calculated to be 175.8. This
means that in relative terms employees in creative industries can be found about ¾ more
often in Vienna than in Austria. High regional concentrations can be observed in particular in
– 8 –
the audiovisual sector, museums/libraries, software/multimedia/internet and fine arts. Their
concentration in Vienna is twice as high as Austria-wide. Just as in the fields of music,
performing arts, advertising and architecture, relevant concentrations can be observed at all
value added stages there. Graphic arts/fashion/design is the only field without a regional
specialisation in Vienna. Although there are considerable regional strengths in the
artistic/creative core (content LQ 224.2) of the sector, reproduction (LQ 59.8) is characterised
by labour-intensive activities (particularly in the production of clothes, shoes and ceramic
household articles), which are, for cost-saving reasons, rather located in the (national and
international) outskirts.
Figure 2: Vienna’s specialisation within creative industries
Location quotient based on employment1), A = 100, 2003
CI total
175,8
Architecture
125,7
Audivisual sector
272,1
Fine arts
216,3
Performing arts and entertainment
170,1
Graphic arts, fashion, design, photography
101,6
Literature, publishing, print media
159,8
Museums, libraries
274,0
Music
159,2
Software, multimedia, internet
246,0
Advertising
182,5
Content Origination
192,9
Reproduction
166,0
Exchange
168,9
0
50
100
150
200
250
300
Source: Federation of Austrian Social Security Institutions; own calculations.– The location quotient is defined as
BW j
BGj
with B = employment; j = sector and stage at the VA chain resp., W = Vienna und G =
LQW j 
n
B
j 1
Wj
:
n
B
j 1
*100
Gj
Austria. Assuming the same values as for Austria as a whole, the LQ has a value of 100. Values below 100 indicate a
lower, values above 100 a higher employment concentration in the given sector in Vienna.
Overall, however, Vienna shows regional strength even in the field of reproduction in an
Austria-wide comparison (LQ 166.0), which is, a priori, surprising in view of Vienna’s meanwhile
minor importance as an industry location. The strength is primarily due to the audiovisual
sector, with producers of telecommunication devices and radio/TV sets being highly
concentrated in the metropolitan area of Vienna. Overall, cluster initiatives in Viennese CI
can therefore be based on remarkable “critical masses” that have applied (at least until
today) to all areas of the value added chain.
– 9 –
4.
Employment dynamics: Large differences in the value added chain
In how far this clustering really creates the expected job effects depends on the employment
dynamics in the individual areas forming the network. Our analysis observes this for the period
1995-2003 and thus over a complete economic cycle. Due to changes in legal provisions on
social security regarding atypical employment 6), we will consider both the development of
overall employment7) and that of standard employment (full- and part-time employment
subject to full social security contributions).
The results confirm the role of Viennese CI as a job incubator in the regional employment
system, but also point to their cyclical nature and marked differences between the
development paths of the different stages of the value added chain (figure 3).
Figure 3: Employment dynamics in Vienna’s creative industries by stages in the value added
chain
Employment relationships, 1995=100
Overall employment
Standard employment
150
140
Content
Origination
150
Exchange
130
130
140
120
120
Creative
Industries
110
100
Vienna total
Exchange
110
Creative
Industries
100
90
90
80
80
Vienna total
70
70
Reproduction
60
1995
Content
Origination
1996
1997
1998
1999
2000
2001
2002
2003
Reproduction
60
1995
1996
1997
1998
1999
2000
2001
2002
2003
Source: Federation of Austrian Social Security Institutions; own calculations.
During the boom of the late 1990s employment in Viennese CI grew remarkably regarding to
both definitions, but again slightly decreased after the economic turning point in autumn
2001 and after the breakdown of the boom of the New Economy. Nevertheless, over the
entire period, a positive growth differential of a remarkable +16 percent (+1.9 percent
annually) in overall employment and of +5 percent (+0.6 percent annually) in standard
employment was maintained, corroborating the importance of CI for the development of
6)
The legal framework regarding social insurance for free service contracts and work contracts was only established
in 1997, that pertaining to employment contracts below the marginal earnings threshold only in 1998. An observation
of overall employment (standard and atypical employment) therefore reflects also additional possibilities regarding
the choice of employment types.
7)Once
again, it has to be pointed out that the data set applied does not include self-employment. The expresssion
“overall employment” therefore refers exclusively to the totality of dependent employment relationships (standard
employment and atypical employment).
– 10 –
Vienna’s labour market: Without the positive employment contribution of Viennese CI, overall
employment in Vienna would not have increased by 1.9 percent, but decreased by 0.3
percent since the mid-1990s, and the decline in standard employment would have been 1.6
percentage points higher that it was actually.
However, the results also reveal that Viennese CI, measured against their development
conditions, do not constitute a homogeneous unit. An undifferentiated consideration of the
Viennese CI as job incubator can therefore hardly be maintained.
Along the value added chain, high, but rather cyclical employment gains in content
origination (1995-2003 total employment +41.3 percent, standard employment +24.2 percent)
and a lower, but sound job creation in exchange (+35.3 percent and +22.4 percent,
respectively) contrast with a clear erosion of areas of reproduction (–32.4 percent and –34.2
percent, respectively), which has become severely pronounced in the period of economic
downturn that started in 2001. Consequently, it is at best a sub - group of CI (pertaining to
content production and diffusion) that can be considered a job incubator. Employment in
reproduction, however, has developed markedly less favourably than overall employment in
Vienna since the mid-90s (growth differential -30 percentage points) and even lacked behind
the dynamics of total manufacturing (-5.1 percent annually compared with -4.5 percent
annually) in the period observed 8). As a result, de-industrialisation phenomena in the urban
economy are fully reflected in production-related areas of CI. Relevant advantages resulting
from the increased utilisation of artistic-creative content could, at least at employment level,
not be observed.
In view of the different importance of the respective stages of the value added chain in the
individual CI sectors, the latter show extremely heterogeneous development paths too (figure
4): The development of standard employment in 1995-2003 ranges from extreme growth in
areas that are influenced by special effects 9, namely museums/libraries (+403 percent or 22.4
percent annually!) and fine arts (+191 percent or +14.3 percent annually) as well as solid
growth in advertising (+38 percent; +4.1 percent annually) and software/multimedia/internet
(+38.3 percent; +4.1 percent annually) to substantial employment losses in graphic
arts/fashion/design (–25.8 percent; –3.7 percent annually) and the audio-visual sector (–19.6
percent; –2.7 percent annually).
8)
In the long term, the field of reproduction in Vienna’s CI has, however, shrunk to a lower degree than the overall
Viennese secondary sector (Hromatka – Resch, 2005).
9)
Here new offers (Museums Quarter, new central library), but also growth within the public sector resulting from
outsourcing have influenced the overall result.
– 11 –
Figure 4: Development of the sectors of creative industries
Level and dynamics of standard employment; 1995-2003
80
Museums, libraries
Employment growth 1995-2003 (%)
60
Advertising
40
Software
20
Performing arts
0
Architecture
Literature,
publishing
Music
-20
Audiovisual
sector
Graphic arts
-40
-60
-40
-20
0
20
40
60
Growth-differential to Vienna (%)
Source: Federation of Austrian Social Security Institutions; own calculations – Circle size represents number of
employees 1995.
The main growth pole in Viennese CI was the large group of software/multimedia/internet,
which posted high employment growth over the entire period, above all in content (software
houses, software consulting, other data processing related activities), while development of
exchange has been slightly weaker within the sector since 2001. On the other hand,
employment in the graphic arts/fashion/design and the audiovisual sector, which were the
two largest groups of CI still in 1995, has massively decreased in recent years despite
pronounced growth in their artistic/creative core areas10.
Overall, the positive employment contribution of Vienna’s CI therefore conceals extremely
heterogeneous developments. A diffusion of the partly strong dynamics in some areas of
content (particularly software, advertising) and exchange (in particular business services) into
production-oriented areas of the value added chain (reproduction) cannot be observed.
The “cluster” of Vienna’s CI might consequently lose its industrial basis before starting to
develop positive spill - overs on these production-related areas in the first place.
10)
While in the field of graphic arts/fashion/design this development is due to the erosion of Vienna’s clothing industry
(reproduction) and some related areas of trade (in particular clothing and shoe retail) and is of a largely continuous
character, the employment decline in the audiovisual sector concentrates on the years of economic downturn after
2001. Here the reason is the dramatic reduction of mostly large-scale, multinational-dominated structures of radio/TV
set and telecommunication equipment manufacturers due to cost-based relocation.
– 12 –
5.
Job creation and job destruction: Heterogeneous development at the
firm level, considerable job turnover
More recent methods of labour market research (cf., for example, Davis – Haltiwanger, 1999)
reveal information on the reasons of this unbalanced employment growth in Vienna’s CI.
They involve comparisons of stocks at the firm level and try to give insight in those gross job
flows that finally determine the (net) employment change observed. To this end, the following
indicators are established:

Firstly, all firms registering an increase in employment within one year are identified.
The sum of all employment changes in these firms is referred to, in compliance with
relevant literature, as “job creation”.

Similarly, all firms registering a decline in employment within one year are selected.
The sum of all jobs lost in these firms is referred to as “job destruction”.

The sum of “job destruction” and “job creation” finally forms the so-called “job
reallocation”. It indicates the gross job turnover and consequently the heterogeneity
of firm growth processes.
Applied to our individual data set, these calculations indicate that the moderate
employment dynamics of Vienna’s CI masks enormous gross flows (table 2).
Table 2:
Job creation and job destruction in Vienna's creative industries
Jobs created
Jobs lost
Net change
Content
Origination
Reproduction
Exchange
Creative
Industries
Vienna total
4,705
1,225
5,393
11,322
67,558
7.0
1.8
8.0
16.8
100.0
Absolute
3,921
2,435
4,406
10,762
71,578
Shares of Vienna in %
5.50
3.40
6.20
15.00
100.00
Absolute
784
–1.211
987
561
–4,020
Absolute
Shares of Vienna in %
Source: Federation of Austrian Social Security Institutions; own calculations.
Employment in Vienna’s CI increased on average by approx. 560 jobs per year in the
observation period. However, this (low) net change results from the creation of more than
11,300 jobs per year, with a simultaneous loss of 10,760 jobs. Overall, in the period 1996-2003,
almost 90,600 jobs were created in Vienna’s CI, while 86,100 were lost – a considerable
turbulence at the job level that hardly becomes apparent by analysing (net) employment
only. This indicates a considerable level of heterogeneity of growth processes at firm and
sector level: Even in growing CI sectors many companies shrink, while in declining parts of
creative industries successful enterprises create jobs. The analysis thus shows a permanent job
– 13 –
turnover in CI – a phenomenon that points to a speedy structural change at sector and firm
level alike.
Table 3:
Job creation and job destruction in Vienna’s creative industries
In percent of standard employment
Creative Industries in Vienna
Job creation
Job destruction
Vienna total
Job creation
Job destruction
1996
8.9
–11.5
9.3
– 8.5
1997
10.1
–10.6
9.5
–11.0
1998
10.9
– 9.6
10.5
–11.2
1999
12.7
–11.3
11.2
–11.0
2000
15.1
– 9.0
11.8
–11.3
2001
16.2
–14.0
13.7
–13.1
2002
11.6
–13.6
10.7
–13.2
2003
12.7
–14.2
11.7
–12.8
Average 1996-2003
12.4
–11.8
10.7
–11.3
Source: Federation of Austrian Social Security Institutions; own calculations.
In the years 1996-2003 between 9 and 16 percent of the jobs in Vienna’s CI were newly
created and a slightly smaller percentage of jobs were destroyed each year (table 3). Thus,
the rate of job creation exceeded the corresponding values for Vienna’s economy almost
continuously. For the rate of job destruction this applies at least for more recent years.
Against this background, job turnover (as the sum of job creation and job destruction) in
Vienna’s CI increased markedly over time and finally clearly exceeded that of Vienna’s
overall economy (figure 5). This is remarkable since Vienna’s overall economy – in line with
the expectations of regional economics for urban economies11) – is already characterised by
a significantly higher job turnover than Austria. Vienna's CI thereby contribute considerably to
the role of the city as an “incubator for firms and jobs”, but they are also responsible for the
considerable heterogeneity of firm growth processes in Vienna, just as for the high job
fluctuation in the region in general.
11)
Large, diversified cities create a high number of innovative new enterprises at the beginning of the product cycle
(Duranton – Puga, 2001). Therefore, more new jobs are created there than in other types of regions. Simultaneously,
more jobs are destroyed, since innovations are riskyl, but also because successful young enterprises (due to their
growth) demand a lot in terms of availability of estate and workforce, which results in a high probability of relocation.
– 14 –
Figure 5: Job turnover in Vienna’s creative industries
In percent of standard employment
35
30
25
20
Creative industries Vienna
15
Vienna
10
Austria
5
0
1996
1997
1998
1999
2000
2001
2002
2003
Source: Federation of Austrian Social Security Institutions; own calculations.
In line with the comparably “young” firm population in Vienna’s CI 12) the great turbulence in
the CI’s labour market is primarily due to micro-firms and small enterprises (table 4). Around
two thirds of the job turnover in Vienna’s CI can be attributed to enterprises with less than 50
employees and around 41 percent to firms with less than 10 employees, with both the
potential of job creation and the risk of job loss being high.
Table 4:
Job creation and job destruction in Vienna’s CI by firm size
Averages 1996-2003
Contribution by size category to
Job creation
Job
Job turnover
destruction
Extent of
Job creation
Job
destruction
share in %
In % of standard employment
1 to 9
40.4
41.3
40.9
25.8
–25.1
10 to 49
25.4
23.2
24.3
15.0
–13.0
50 to 99
8.4
7.9
8.2
12.1
–10.8
100 to 249
11.9
8.2
10.1
11.9
– 7.8
250 to 499
7.2
4.6
5.9
8.6
– 5.2
500 and more employees
6.7
14.8
10.6
2.9
100.0
100.0
100.0
total
12.4
– 6.2
– 11.8
Source: Federation of Austrian Social Security Institutions; own calculations.
In Vienna’s CI the number of jobs annually created in micro-firms with 9 or fewer employees
amounts to more than a quarter (!) of their existing staff. Simultaneously, however, nearly the
same percentage of jobs is lost in this size category, indicating that the stability of new jobs is
12)
Half of all firms in Viennese CI were set up in 1993 or later. The median software/multimedia/internet firm has
existed since 1997 (Ratzenböck et al., 2004).
– 15 –
quite low. Medium sized enterprises are therefore at least just as relevant for securing
employment, with lower job creation offset by lower job loss rates. The number of jobs
created in micro-enterprises (measured against the current staff size) hardly exceeds that of
jobs lost, while it clearly does in enterprises with 10-499 employees. The latter thus created a
relevant amount of jobs in the observation period.
The core problem of clustering, however, seems to be the weakness of large firms in the CI
sector: In the observation period, enterprises with more than 500 employees accounted for
14.8 percent of the jobs destructed, compared to only 6.7 percent of the jobs created in
Vienna’s CI. Thus, large enterprises are the only firm category posting a (net) jobs loss in CI in
1996-2003.
With large enterprises occurring above all at the processing levels of the production system of
CI, the weakness, which has already been mentioned in chapter 4, of the value added stage
reproduction or the sectors the latter dominates becomes clearly apparent also in gross job
flows (figure 6).
Figure 6: Contribution of individual areas to job creation and destruction in Vienna’s
creative industries
Jobs subject to full social security contributions, Ø 1996-2003
By sector
By value added stage
100%
100%
Advertising
80%
Software, multimedia, internet
80%
Music
Museums, libraries
60%
60%
Exchange
Literature, publishing, print media
Graphic arts, fashion, design,
photography
Performing arts and entertainment
40%
Reproduction
40%
Content Origination
Fine arts
Audivisual sector
20%
20%
Architecture
0%
0%
Job creation
Job destruction
Job creation
Job destruction
Source: Federation of Austrian Social Security Institutions; own calculations.
In 1996-2003, firms in the field of reproduction accounted for nearly 23 percent of all jobs
destructed in CI, compared with only 11 percent of jobs created. This imbalance continues at
the sectoral level in the fields that are dominated by this stage of the value added chain
(particularly the audiovisual sector, graphic arts/fashion/design; literature/ publishing/print).
At closer inspection, the remarkable erosion of net employment in this area turns out not to
be due to an over-proportional job destruction (around 10 percent of the employees, overall
CI 11.8 percent). Instead, lacking success in job creation is much more decisive here: Annual
– 16 –
job creation in the CI areas of reproduction corresponds to no more than 5.1 percent of
employees (CI overall: 12.4 percent)13).
6.
Firm dynamics: High start-up activity, but also growth in existing firms
Another important question in the context of job creation and job destruction is whether new
jobs in CI are primarily created in new companies and in this way as a result of business startups or rather as a result of the growth of existing firms. Conversely, for evaluating long-term
development potentials it is essential to know whether job destruction results above all from
downsizing or rather from the definite closure of firms.
Table 5:
Start-ups and closures in the different parts of CI
1996-2003; in percent of standard employment
Start-up rate
Closure rate
Architecture
5.6
5.9
Audio-visual sectors
1.8
1.5
18.2
8.5
Performing arts and entertainment
6.1
5.2
Graphic design, fashion, design, photography
4.6
5.8
Fine arts
Literature, publishing, print media
5.1
4.7
19.6
6.1
Music
5.7
4.1
Software, multimedia, internet
3.8
3.2
Advertising
8.4
6.7
Content Origination
6.5
5.5
Reproduction
1.7
1.9
Exchange
6.6
4.6
Creative Industries, total
5.3
4.2
Vienna
4.6
4.2
Museums, libraries
Source: Federation of Austrian Social Security Institutions; own calculations.
With regard to this, start-up and closure rates14) indicate that the high employment dynamics
in Vienna’s CI is (inter alia) due to relevant start-up activities (table 5). In newly set up
enterprises of the cluster around 38,600 jobs were created in the years 1996-2003,
13)
In general it is by no means the problematic areas that show particularly great turbulences at the job level. High
job turnover is rather characteristic of dynamic industry groups that create many jobs through products at the start of
the life cycle, but, due to their orientation towards innovation, act under risky conditions and thus incur a high rate of
failure.
14)
Start-up rates stand for the jobs created in newly founded firms during the first year, closure rates for the jobs that
are lost due to closures during this period.
– 17 –
corresponding to an annual 5.3 percent of the existing jobs. This means that the start-up rate
in Vienna’s CI clearly exceeds that of Vienna’s overall economy (4.6 percent).
Simultaneously, 30,700 jobs (or 4.2 percent of the existing ones) in Vienna’s CI were lost on
account of closures, with the closure rate exactly corresponding to that of Vienna’s overall
economy.
A positive firm dynamics (business start-ups/closures) therefore considerably contributes to a
more favourable job development in CI in Vienna, however helped by a comparably
dynamic stock of existing firms (figure 6). Overall, 42.6 percent of the new jobs in Vienna’s CI
resulted from newly set up firms in 1996-2003, while 57.4 percent were created by
employment growth in existing companies. This proportion is hardly different from that
observed for the totality of sectors in Vienna, which allows for drawing the conclusion that the
overall higher rate of job creation in Vienna’s CI can to a remarkable extent be attributed to
a comparably high job growth in existing firms.
Figure 7: Contribution of business start-ups and existing firms to job dynamics
1996-2003
Contribution to job creation
70
60
Contribution to job destruction
70
Creative Industries
Vienna
57,4
56,8
50
42,6
64,3
61,7
60
Creative Industries
Vienna
50
43,2
40
40
30
30
20
20
10
10
35,7
38,3
0
0
Business start-ups
Firm population
Firm population
Closures
Source: Federation of Austrian Social Security Institutions; own calculations.
On the “passive side”, a clearly lower share of job loss in Vienna’s CI results from business
closures. Job cuts thus result predominantly from an unfavourable development of existing
firms rather than from their definite failure.
Once again, when looking at company dynamics it becomes clear that Vienna’s creative
industries are not a homogeneous cluster (table 5). Both start-up and closure rates differ
considerably between sectors and stages of the value added chain, with differences in startup rates, varying between 19.6 percent (museums/libraries) and 1.8 percent (audiovisual
– 18 –
sector), being even more pronounced than those in closure rates. Firm dynamics in content
origination and exchange as well as in 8 of the 10 different CI industries makes a positive net
contribution to job creation in Vienna’s CI. At the reproduction stage and in the sectors of
graphic arts/fashion/design and (to a slightly lower degree) architecture, changes at the firm
level create (net) job losses.
In this context it has to be mentioned that at sectoral level high start-up rates tend to go
hand in hand with high closure rates, while low start-up activity is generally connected with
low closure rates (correlation coefficient –0.721). “Dynamic” CI sectors (fine arts or
museums/libraries and, to a slightly lesser extent, advertising and performing arts) are
characterised by a comparably high number of jobs in newly established businesses, which
are of course correspondingly risky and account for a high number of closures in these areas.
Once again, the field of software/multimedia/internet is an exception among the growing CI
sectors, with the bulk of newly created jobs resulting from the growth of existing firms.
Within the shrinking segment the audiovisual sector in particular shows the pattern of a hardly
dynamic industry group. Few new jobs are created through start-ups there. On the other
hand, comparably few firms are closed down, which means that the overall considerable job
reductions take predominantly place within (still) existing, but shrinking firms15). In contrast, the
sector graphic arts/fashion/design on the one hand contains a quite dynamic (content)
segment, where many jobs are created by start-ups. On the other hand, in the sector's
exchange segment firm population is shrinking markedly, in this way contributing considerably
to job losses.
7.
Persistence of firm growth: Higher “probability of survival” of new jobs in
Vienna’s CI
Long-term employment dynamics of Vienna’s CI is finally not only determined by the number
of jobs created and destructed each year. An important question in this context is to what
extent jobs, once created, are sustainable and whether job losses can be compensated over
time. To answer these questions, we established indicators of the sustainability (persistence) of
created and destructed jobs. To this end, we selected all firms that create (lose) jobs during a
year. Subsequently we determined how many of these jobs in these companies were again
lost (created) in subsequent years. The share of the “surviving” (permanently lost) jobs in all
jobs created (destructed) in the base year can be interpreted as an indicator of the
sustainability of job creation (destruction).
15)
This is certainly not least the case because the reproducing parts of the audiovisual sector are dominated by large
enterprises. Dramatic closures are rare here. Instead, redeployment between firm locations as well as outsourcing of
parts of production can be observed, while individual planning or distributive parts are maintained.
– 19 –
Table 6:
Sustainability of job creation and job destruction in creative industries
Share of remaining job losses (%)
after ...
Share of remaining “new” jobs (%) after ...
1 year
2 years
3 years
1 year
2 years
3 years
Creative Industries
1996
72.6
54.1
44.1
88.8
80.0
76.0
1997
71.0
54.4
41.5
93.3
82.6
76.7
1998
75.2
58.9
40.8
94.1
82.6
78.3
1999
75.8
54.3
38.3
93.9
85.4
81.0
2000
74.6
54.4
43.6
97.9
84.6
81.1
Average
74.1
55.2
41.6
93.4
83.0
78.6
1996
67.6
47.7
37.4
86.9
78.1
72.2
1997
67.3
49.6
38.4
90.2
84.1
80.4
1998
71.0
53.2
38.4
90.3
84.4
80.8
1999
71.2
51.4
38.5
90.6
85.6
82.5
2000
68.7
50.7
39.0
90.9
86.2
82.9
Average
69.2
50.6
38.4
89.9
84.0
80.1
Vienna (total)
Source: Federation of Austrian Social Security Institutions; own calculations.
The results of these calculations (table 6) clearly indicate that the high level of employment
growth in Viennese CI results, inter alia, from a comparably high sustainability (persistence) of
firm growth. An average of around three quarters of the newly created Viennese CI jobs
survived the first year in the observation period, while after three years 41.6 percent were still
existing. Lost jobs were comparably difficult to compensate for: After one year 93 percent,
and after 3 years almost 79 percent of all lost jobs remained unoccupied. Notwithstanding,
jobs in Viennese CI are still more sustainable than all jobs in Vienna, and lost jobs are replaced
faster in the CI cluster.
Differences in sustainability again follow the findings regarding strong and weak parts of
Viennese CI (table 7): The value added stages content origination and exchange are
responsible for the higher persistence of firm growth, while jobs in the reproduction stage of
the value added chain are less persistent and – once lost – less frequently replaced than in
the city economy in total.
Table 7:
Sustainability of job creation and job destruction in the different parts of CI
Shares after 3 years in percent; averages 1996-2000
remaining newly created
jobs
remaining destroyed
jobs
Architecture
41.1
76.5
Audiovisual sector
36.5
79.3
– 20 –
Fine arts
37.9
80.3
Performing arts and entertainment
46.2
75.6
Graphic arts, fashion, design, photography
37.1
81.1
Literature, publishing, print media
40.1
79.9
Museums, libraries
44.6
77.5
Music
40.5
79.0
Software, multimedia, internet
50.0
75.6
Advertising
36.3
73.7
Content Origination
40.7
76.2
Reproduction
36.5
83.9
Exchange
44.0
78.0
Creative Industries, total
41.6
78.6
Vienna
38.4
80.1
Source: Federation of Austrian Social Security Institutions; own calculations.
Also at a sectoral level, new jobs have comparably little persistence particularly in the
“problem areas” (audiovisual sector, graphic arts/fashion/design, and, to a smaller extent,
the fields of literature/publishing/print and music), while job losses are more sustainable than
in the cluster average. In the dynamic areas, in turn, new jobs are more persistent, with
software/multimedia/internet strikingly continuing to have the highest job stability within CI
despite the recession of the New Economy in the early 2000s.
8.
Summary and Conclusions
In many cities, creative industries are the focus of cluster initiatives of urban economic policy.
This is justified, on the one hand, by the increasing importance of creativity and new ideas as
locational and production factor in the knowledge-based economy. On the other hand, the
interest can be put down to the supposedly high growth and employment potentials
attributed to this area. Based on a case study for Vienna, we deal with the question whether
CI are able to live up to the role as job incubator that was assigned to them. We do this by
analysing job effects and firm dynamics on the basis of a large individual longitudinal
matched employer-employee data set for dependent employment and the period 19952003. Looking at Vienna, our case study analyses an urban area that has considerable
“critical masses” for relevant clustering: After all, around 15 percent of regional employment
in Vienna can be attributed to CI as a broadly defined production system. Specialisation
compared with the national average can be found in all parts of the value added chain and
almost all sectors defined as parts of CI.
– 21 –
The results confirm the function of creative industries as an incubator for firms and jobs, but
also show a high degree of heterogeneity of firm growth in the cluster as well as a remarkable
amount of turbulence at the job level:

Overall, total (dependent) employment in Viennese CI has increased by 1.9 percent
annually since the mid-1990s, exceeding total employment growth in Vienna (+0.2
percent) by far. Without the CI’s positive contribution to employment, total
(dependent) employment in Vienna would not have increased by almost 2 percent
since 1995, but decreased by 0.3 percent.

This positive employment development masks enormous gross flows of jobs created
and destructed, indicating phenomena of structural change at firm and sectoral
levels. In Viennese CI almost 90,300 new jobs were created and 86,100 were lost in
1996-2003. Job turnover in the cluster, therefore, is high and increases over time.

The higher employment dynamics in Viennese CI was due to a comparably high
degree of firm dynamics (as the balance of business start-ups and closures) and a
favourable development of existing firms. In addition, newly created jobs in Vienna's
CI are more persistent than in the city economy in total.
Aside from all the positive evidence, the analysis also points to weak spots that might possibly
be relevant to cluster initiatives in other cities too:
For Vienna it has been shown that although in small and young CI firms many new jobs are
created, the latter lack sustainability: In CI firms with less than 10 employees the number of
jobs created per year corresponds to more than a quarter (!) of the existing stock of jobs, but
simultaneously nearly the same percentage is lost again. This reflects highly different growth
paths at the firm level, which in turn indicate a high degree of heterogeneity in the skills of the
manager-proprietors here. Therefore, relevant measures should place emphasis on consulting
and training to support people starting up a business and in this way contribute to the
stabilisation of jobs in the cluster.
However, the main problem at the corporate level, at least in Vienna’s CI, lies in the field of
large enterprises, which can be found almost exclusively at the processing stages of the CI
production system (reproduction). Today, large enterprises constitute the only size category in
Vienna's CI experiencing a (net) job loss. Here, phenomena of de-industrialisation and
(partial) outsourcing, which generally characterise large industrial structures in metropolitan
areas, come into play. CI-specific measures would consequently have to be accompanied
by general industrial policy measures in cluster initiatives. Corresponding to the highly
heterogeneous developments at the sectoral level, the focus has to be on differentiated
policy measures that are tailored to the conditions of the different parts of CI.
This would also take account of the fact that creative industries, at least in Vienna, do not
form a homogeneous cluster: The value added chain in CI is made up of sub-segments with
completely different development paths. A diffusion of the strong dynamics in content
– 22 –
origination proper (1995-2003 overall employment: +41.3 percent, standard employment
+24.2 percent) and, to a smaller extent, in the distribution of artistic/creative content
(exchange +35.3 percent and +22.4 percent, respectively) to more production-oriented
stages of the value added chain (reproduction –32.4 percent and –34.2 percent,
respectively) cannot be observed. Apparently, the latter have not benefited to a relevant
extent from an increased utilisation of artistic/creative content so far. Instead, their decline (–
5.1 percent annually) exceeded that of manufacturing in total (–4.5 percent annually) in the
period observed.
Against this background, measures have to be taken to counteract a further thinning out of
downstream production stages of the value added chain in regional CI by further linking up
content and application-oriented activities. (Appropriate and necessary) promotion activities
within the artistic/creative core should therefore be supplemented by mediating and
coordinating activities between the heterogeneous segments of the value added chain.
Considering the location logics of large industrial firms, it cannot of course be assumed that
positive spill-over effects from the artistic/creative core completely prevent a further erosion
of application-oriented areas, even if the aforementioned measures are pursued resolutely.
The increasing functional division of labour between core cities (as optimum locations of
highly technological and human-resource intensive sub-productions) and the broader
surroundings with their advantages regarding to availability of land and production costs will
undoubtedly continue in the future. Hence, it seems reasonable to reconsider the mostly
narrow geographical focus of cluster initiatives in creative industries and to search for points
of contact also in complementary reproducing sectors in the broader urban surroundings. A
cluster of creative industries that relies on the locational advantages of the city for the
artistic/creative and distributive parts of the value added chain, while benefiting from the
attractiveness of the wider agglomeration in the fields of reproduction, would certainly have
the best chances to accumulate relevant competitive advantages.
– 23 –
Table A1: Vienna Definition of creative industries classified by sectors and value added chain
segments
Manufacturing and
Reproduction
Exchange
74.20
Architecture
Audiovisual sector
(film, video, television, radio)
Content
Origination
24.65 (33.3%)
92.11
92.13
32.20
92.20
52.45 (40%)
32.30 (50%)
92.72 (50%)
22.32
92.12
71.40 (50%)
92.31 (25%)
Fine arts
52.50 (33.3%)
52.63 (50%)
74.84 (12.5%)
Performing arts and entertainment
92.31 (25%)
55.40 (50%)
92.33
92.32 (50%)
92.34
92.72 (50%)
Graphic
arts/fashion/design/photography
18.10
36.22
52.42
18.22
36.61
52.43
18.24
74.81
52.44
19.30
74.84 (12.5%)
26.21
52.50 (33.3%)
52.48 (20%)
33.40
Literature/publishing/print media
22.21
22.11 (50%)
52.47
22.22
22.12
71.40 (50%)
22.23
22.13
74.84 (12.5%)
22.24
22.15
22.25
92.31 (25%)
92.40
Music
24.65 (33.3%)
22.14
55.40 (50%)
32.30 (50%)
92.31 (25%)
92.32 (50%)
36.30
22.11 (50%)
52.45 (60%)
22.31
74.84 (12.5%)
52.50 (33.3%)
Museums/libraries
74.84 (50%)
92.51
92.52
92.53
Software/multimedia/internet
24.65 (33.3%)
36.50
52.48 (20%)
22.33
72.20
64.20
72.40
72.60
Advertising
74.40
Source: Ratzenböck et al. (2004). NACE-classes that pertain to several analysed fields simultaneously are allocated in
percentages based on structure information from Austrian general censuses.
– 24 –
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