Discussion Papers 2007.
Social Inequalities in Urban Areas and Globalization.
The Case of Central Europe. 51-76. p.
a core-periphery model of dual social structure where the traditional model
of socially high-ranked centrre with and low-ranked periphery has been
extended by another scheme of low-ranked centre and high-ranked periph-
ery. All these processes have created a new type of socio-spatial unit.
The Austrian case study – Social Inequalities
in the Vienna Metropolitan Region
Preface
A spatial analysis of social inequalities tackles one of the major issues of modern
human geography: How equal or unequal is society and its spatial distribution?
The answers range from one extreme, a totally equal distribution representing a
homogeneous social area, to the other, a distinctly unequal distribution as a char-
acteristic feature of a society that is socially as well as spatially highly diverse.
Equal distribution indicates that all spatial units share the same features, which
means that all units have the same proportion of affluent and poor residents, the
same proportion of qualified and unqualified employed persons and of large and
small apartments. Unequal distribution obviously refers to the complete opposite.
The highly qualified and well-off groups of population as well as the large apart-
ments concentrate in a very limited number of units, whereas low-income and
unskilled residents living in small apartments concentrate in a completely differ-
ent set of spatial units. What is not intended in this context, however, is an
evaluation of socio-spatial inequality, since the question whether an unequal spa-
tial distribution is to be interpreted as fair or unfair will always be a matter of
ideology. Therefore the focus of this paper will rather be put on an objective de-
scription.
The analysis itself is primarily based on data of the census 2001, which allows
a very detailed spatial differentiation. The first step includes the identification of
relevant indicators characterizing social inequality, the second step is aimed at
depicting their spatial distribution and, thirdly, the individual features are going to
be combined in order to establish basic dimensions of inequality. The smallest
spatial unit in this analysis is the community or municipality for the suburban
region of Vienna or the census tract for the City of Vienna itself. Together the
City of Vienna and its suburban region constitute the Vienna Metropolitan Region
that has been subject of the analysis.14
14In this context Ms D. Schönbichler is to be thanked for the translation into English as well as for
reviewing the draft.
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Heinz Fassamann - Gerhard Hatz : The Austrian Case Study – Social Inequalities in the Vienna Metropolitan Region.
In: Social Inequalities in Urban Areas and Globalization. The Case of Central Europe.
Pécs: Centre for Regional Studies, 2007. 51-76. p. Discussion Papers, Special
Theoretical background
The analysis of social and spatial inequality has evolved from two basic questions
of research: the Social Indicator Research of the 1970s and the Social Area
Analysis of urban space of the 1940s. In this paper both concepts will be dealt
with and for the first time combined to achieve an integrative approach. For this
purpose the two rather different concepts will be introduced briefly in the fol-
lowing chapters.
Social inequality and social indicator research
Social inequality is a relative measurement of the distribution of relevant indica-
tors within society. Social inequality is the expression of different access to
housing, health care, and education. It is inextricably linked to unequal distribu-
tion of income and wealth in society, which was again made the focus of attention
during the creation of the social welfare states in Europe. The question as to
which extent social inequalities can or even should be tolerated and which extent
makes public interference desirable or even necessary was becoming a crucial
issue. Therefore measuring social inequality by means of social indicators was
regarded as a fundamental task (see Fassmann, 1997).
The social indicator research of the 1970s was guided by a normative concep-
tion of an active social policy. This conception advocated state intervention with
the aim of bringing about change within society, by ensuring equality of possi-
bilities and by supporting selected groups. Social indicators were and still are a
necessary pre-condition in the field. Social policy is not feasible without prior
knowledge of the social situation and without identification of the marginal
groups of society. The question concerning which political measures should be
implemented on which population groups, remains impossible to answer without
the knowledge of the real and objective situation. With reference to an extensive
system of yearly economic statistics, the foundation for every national economic
policy, a similar system of social reports was conceived and carried out in an ex-
emplary manner. The functions of the system consisted of a statistical observation
of society, the gaining of information on specific problem groups and the supervi-
sion of the success of the socio-political measures.
Social indicator research was not based on a universal self-contained theory,
which settled the central dimensions of a modern industrial society and set up a
relationship with each other. The theory rather served the normative fixed dimen-
sions, which, on the basis of operationalized indicators, should have reproduced
the notion of „quality of life“. The theoretical argument, in terms of which socie-
tal dimensions were selected and through which indicators were operationalized,
took on more of a subordinate role. Empirical analyses of the individual indicators
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Heinz Fassamann - Gerhard Hatz : The Austrian Case Study – Social Inequalities in the Vienna Metropolitan Region.
In: Social Inequalities in Urban Areas and Globalization. The Case of Central Europe.
Pécs: Centre for Regional Studies, 2007. 51-76. p. Discussion Papers, Special
or the formation of synthetic indicators were and still are in the forefront of the
wide range of literature devoted to measuring quality of life, living conditions or
trends in the development of the social structure.15
Social area analysis
In the late 1940’s Eshref Shevky and Wendell Bell developed the Spatial Area
Analysis which heavily relies on the tradition of Social Ecology founded by the
Chicago School (see Shevky and Bell 1955). Spatial Area Analysis claims that
cities are divided into small, segregated ‘worlds’ which are referred to as ‘Natural
Areas’. They correspond to the ‘Neighborhoods’, the residential areas typical of
American metropolitan areas. Those neighborhoods provide a high potential of
identification for the residents who deliberately separate themselves from the
outside and insist on social control mechanisms within the boundaries of their
neighborhoods. Consequently, ‘Natural Areas’ or ‘Neighborhoods’ are ‘natural’
units of the city, just like biotopes can be seen as ‘natural’ units of nature.
Social Area Analysis regards the city as a mosaic consisting of numerous
individual neighborhoods. It is the goal of Social Area Analysis to distinguish
these neighborhoods from each other and to describe the structure of the
neighborhoods by using different indicators. Who is living together? Which
groups of population constitute a common social entity of its own? How can the
social-spatial patterns of a city be described and explained?
The Social Area Analysis did not have any normative objective. It was not
aimed at any specific measures of planning or policy and it did not claim to even
out inequalities. Its goal was rather to identify the social morphology of a city, the
extent of segregation and, most of all, the crucial variables responsible for the
differentiation. In time two different approaches developed: firstly an inductive
approach with the concept of collecting as many variables as possible in order to
determine the primary dimensions in the formation of neighborhoods by means of
factor analysis (factorial ecology) and, secondly, a deductive approach in which
the selection of variables influencing the socio-spatial differentiation of a city is
based on theoretical considerations (e.g. modernization theory). Both notions
have advantages and disadvantages and have clearly contributed to explaining
15In Germany for instance, the SPES-Project (socio-political decision and indicator system for the
Federal Republic of Germany) or in Austria, the project examining „social inequality“ were two
examples of this type of research dating back to the 1970’s. Evaluations of the societal
development as well as social transformation were carried out and published in manual form in
many European and non-European countries. The British Social Trends (published yearly since
1970), the French Donnees Sociales (1973), the American Social Indicators, the welfare surveys
and social reports in Northern Europe or the Austrian report pertaining to the population's social
situation should be mentioned here.
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Heinz Fassamann - Gerhard Hatz : The Austrian Case Study – Social Inequalities in the Vienna Metropolitan Region.
In: Social Inequalities in Urban Areas and Globalization. The Case of Central Europe.
Pécs: Centre for Regional Studies, 2007. 51-76. p. Discussion Papers, Special
socio-spatial differentiations. With regard to this analysis, however, it is not nec-
essary to dwell on these approaches any further.
In this analysis it is attempted to combine both approaches. The selection of
the indicators is based on the concept of social indicator research and they ought
to be able to define and validly measure social inequality. Therefore a profound
examination is necessary, because official statistics provide a large number of
indicators identifying physical, economic and demographic structures, which,
however, contribute hardly anything to a problem-centred delineation of social
inequalities. The path of analysis itself is determined by Social Area Analysis. It
leads to an understanding of the socio-ecological milieus of a society character-
ized by obvious social inequalities and imbalances and finally to an answer to the
basic question: how can the social morphology of the Vienna Metropolitan Re-
gion be described.
Relevant indicators
The social indicator research provides the background for the selection of indica-
tors: they certainly have to contribute to comprehending and explaining social
inequalities. This alone hardly gets you anywhere, however, because there are
numerous variables responsible for social inequalities. The decisive criterion is
the availability of data especially for a spatial differentiation. Therefore the data
required need to provide information related to social inequalities at the level of
communities and municipalities for the urban fringe and at the level of census
tracts for the City of Vienna. Both levels together constitute the Vienna Metro-
politan Region. In the following section every individual indicator and its specific
advantages and disadvantages will be defined and presented in a statistical and
cartographic overview.
Selection model
The first differentiation that can be ascertained concerns the difference between
subjective and objective indicators. Inequality and quality of life and welfare do
not only concern objective living conditions, but are also a matter of personal
perception. The same objectively evaluated living conditions can be perceived
differently from a subjective point of view. This occurs because either relevant
factors are left out or because the living conditions, which are evaluated at a spe-
cific time, sometimes are the result of a “recovery process“, and at other times
and places of a downward spiral. Both objective and subjective indicators are
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Heinz Fassamann - Gerhard Hatz : The Austrian Case Study – Social Inequalities in the Vienna Metropolitan Region.
In: Social Inequalities in Urban Areas and Globalization. The Case of Central Europe.
Pécs: Centre for Regional Studies, 2007. 51-76. p. Discussion Papers, Special
valuable in their own way, as the methodological difficulties in collecting and
comparing subjective indicators are well known (Table 1).
Table 1
Model of social inequality
Independent factors
Regional level
Local labor market conditions
Local housing market
Social infrastructure
Individual level
conditions
Active population and
Living space,
unemployment
homeownership
Qualification and labor
Income
market position
Working hours
School attendance rate, ages
15-19
Source: Author’s concept.
The present article concentrates on objective indicators that are available on a
detailed spatial level. The considerations are based on a model which forms
causal chains of variables and differentiates between independent and dependent
factors. Independent factors comprise indicators related to employment, whereas
income, standard of living and school attendance rate of teens between 15 and 19
can be understood as its consequence. At first there must be some kind of em-
ployment, only in that case income can be generated. The local labor market
conditions influence how much somebody earns, although this mainly depends on
the kind of employment.
Consequently, the level of income determines the living conditions, even
though the specific local situation has to be taken into account again (real estate
market, property prices, building costs, do-it-yourself (DIY) resp. mutual support
in tightly knit neighbourhoods). At last, the level of income but also the “social
background” influences the school attendance rate of the 15–19 year olds, who
have already completed their compulsory school attendance. High-income house-
holds with privileged positions on the labor market pass on the necessity of gain-
ing higher qualifications to the next generation. In this context local conditions
seem to be of a certain relevance again. A dense network of educational infra-
structure appears to be reflected by a high school attendance rate of 15–19 year
olds.
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Heinz Fassamann - Gerhard Hatz : The Austrian Case Study – Social Inequalities in the Vienna Metropolitan Region.
In: Social Inequalities in Urban Areas and Globalization. The Case of Central Europe.
Pécs: Centre for Regional Studies, 2007. 51-76. p. Discussion Papers, Special
Thus, social inequality is operationalized as a phenomenon which is first of all
based on employment leading to different levels of income. These incomes permit
the purchase of goods, especially living space as a central indicator of social ine-
quality. Eventually, local infrastructure and public facilities (e.g. schools) are
indirectly perceived as a part of social inequality.
Statistical Overview
After testing several variables if they are significant and reliable 12 variables have
been included in the analysis. These variables characterize the local employment
opportunities defined by the general employment rate, unemployment, the quality
of jobs and working hours as well as the dependent dimensions income, quality of
housing and the proportion of high school students as indicators of the local infra-
structure and predominant social values.
The following table mainly shows the respective means as well as the coeffi-
cients of variation, which illustrate the extent of socio-spatial inequality16 (Table
2).
Table 2 Mean, standard deviation and variation coefficient of the indicators
of social inequality
Indicator
City of Vienna
Suburban Region Metropolitan Region
mean var.coeff.
mean var.coeff. mean var.coeff.
Income per capita
12.8
11.0
12.2
6.2
12.5
9.6
Active labor force
82.4
4.3
82.6
3.5
82.5
4.0
Unemployed
9.9
41.4
5.0
33.6
7.8
52.6
Self-employed
8.8
57.6
10.8
38.0
9.6
49.6
Highly qualified labor force
13.8
28.1
7.4
62.2
11.1
47.4
Unskilled workers
17.9
44.6
16.8
36.9
17.4
41.8
Full-timers
75.0
5.2
79.6
3.0
77.0
5.2
Part-timers
10.4
15.7
11.8
17.3
11.0
17.7
Marginal part-timers
4.1
34.3
3.0
40.0
3.6
39.1
Living space per capita
37.6
18.8
43.6
7.0
40.1
16.0
Homeownership
25.0
76.6
73.5
17.7
45.6
64.3
High school students
43.2
30.9
42.4
22.4
42.9
27.7
Number of spatial units
245
181
426
Source: Statistik Austria: Census 2001, author’s calculation.
16Coefficient variation can be understood as the variation with regard to the mean in %. A small
value indicates a very equal spatial distribution, a high coefficient of variation, however, indicates
an unequal distributionof variation: Standard deviation divided by mean (multiplied by 100).
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Heinz Fassamann - Gerhard Hatz : The Austrian Case Study – Social Inequalities in the Vienna Metropolitan Region.
In: Social Inequalities in Urban Areas and Globalization. The Case of Central Europe.
Pécs: Centre for Regional Studies, 2007. 51-76. p. Discussion Papers, Special
The spatial level of reference is provided by 245 Viennese census tracts and
181 communities and municipalities of the Viennese suburban fringe. All in all, a
total of 426 spatial units have been included.
Employment and Qualifications
Social inequalities are triggered by an unequal distribution of income and income
will mostly be allocated by employment. Somebody who has been unemployed
over a long period of time usually has a hard time reintegrating into the labor
market and is not only in danger of dropping below the poverty line, but also
loses some part of his identification in society. A job does not only provide eco-
nomic security but also fulfils important social and psychological functions. Not
only is income distributed through a position in the labor market, but holding a
job gives life structure and meaning. Indicators pertaining to the employment
situation and to unemployment are therefore regarded as the central issues in each
social report. For the analysis eight indicators that characterize the employment
situation as well as the estimated income are selected.
The first indicator characterizes the percentage of the active labor force de-
fined as the economically active population between ages 20–60 as a percentage
of the total population of the same age group (Figure 19). A high rate of active
labor force indicates the economic need of making a living by holding a job on
the one hand and the opportunity of being attached to the local labor market. The
distribution of that variable shows a less significant variation. The population in
the Vienna Metropolitan Region is integrated in the labor market with a similar
intensity in all spatial units and the range varies only from around 70% to 85%.
The variation coefficient is one of the lowest compared to other variables and the
spatial variation shows no clear pattern.
In contrast to this “homogeneous” spatial distribution of the rate of active la-
bor force, with a coefficient of variation of 52.6 the distribution of unemployment
is rather unequal (Figure 20). Joblessness concentrates on the City of Vienna and
amounts to almost 10%, whereas it is only half of that in the surrounding region.
Even there it is not distributed equally, but there seem to be some “hot spots”
whose labor markets face serious problems. The southern part of the Vienna Ba-
sin with its old industries can be counted among these “hot spots”. In addition,
there are also some communities in rather rural areas which make workers redun-
dant as a result of rationalization and concentration in agriculture.
The high unemployment rates in Vienna are a relatively new phenomenon, for
which there is not just one single explanation. Even though the city was the region
with the highest employment rates and the lowest unemployment rates until re-
cently, this pattern is changing dramatically. The factors relevant in this process
are the exodus of maufacturing, trade and retail to the suburbs.
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Heinz Fassamann - Gerhard Hatz : The Austrian Case Study – Social Inequalities in the Vienna Metropolitan Region.
In: Social Inequalities in Urban Areas and Globalization. The Case of Central Europe.
Pécs: Centre for Regional Studies, 2007. 51-76. p. Discussion Papers, Special
Figure 19
Active labor force, Vienna Metropolitan Region 2001
Figure 20
Unemployed, Vienna Metropolitan Region 2001
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Heinz Fassamann - Gerhard Hatz : The Austrian Case Study – Social Inequalities in the Vienna Metropolitan Region.
In: Social Inequalities in Urban Areas and Globalization. The Case of Central Europe.
Pécs: Centre for Regional Studies, 2007. 51-76. p. Discussion Papers, Special
The establishment of shopping centres as well as the relocation of manufacturing
to the outskirts result in a loss of jobs in the city. Due to limited space many in-
dustries did not see any chance of expansion in the city and have consequently
moved their production sites to the urban fringe. In addition, the inner city is get-
ting less and less accessible for trucks and lorries, which is, however, extremely
important in an era of “just in time production”. The city has lost jobs in produc-
tion, supply and distribution and due to suburbanization it simultaneously has to
face a loss of younger high- and middle income households with children. The
groups remaining in the city are those at a greater risk of being made redundant:
immigrants, unskilled workers and elderly people still in employment.
The city undeniably provides protection and anonymity for those who regard
joblessness as a stigma. In rural or suburban areas unemployment is more visible,
because people who are out of work do not leave the house in the morning and
return at the end of the working day. The social environment pays attention and
observes. People having to cope with a long-term “labor-market exclusion” find
cheaper housing in the city, together with an environment without intensive social
control. In addition, joblessness is something that has to be admitted. If in a spe-
cific environment a larger number of unemployed people are open about the
struggle they have in common, it is easier for the individual to reveal the personal
situation and turn to the labor exchange.
Another important indicator is the percentage of self-employed among the
economically active population (Figure 21). This indicator defines a group that
generally has a higher income as well as a higher prestige. The category “self-
employed” includes entrepreneurs, doctors, lawyers, architects, notaries, trades-
men, and the group of “new self-employed” people as well. The group of self-
employed can certainly not be regarded as homogenous, yet it rather marks the
top of society, especially as the number of self-employed people providing jobs in
industrial businesses and service industries (small tradesmen) has declined. All in
all, in 2001 an average of 8.4% of the labor force in Vienna is self-employed, but
10.8% in the suburban zone around the city. As the variation coefficient and the
respective spatial distribution clearly demonstrate, the proportion of self-em-
ployed is rather unequally than equally distributed. The variation coefficients of
57.6 within the city and of 38.0 in the urban fringe rate among the highest, ob-
served in the indicators analysed in the course of the study.
Self-employed are concentrated in the city center (1st district), its neighboring
districts and in the outlying districts in the west of the city. Especially in the out-
skirts of the districts 13–19 and 23 with their attractive locations at the slopes of
the Vienna Woods the proportions of self-employed people are above average.
But also in the more rural communities with a higher proportion of farmers and
wine makers in the north and east of the Vienna Metropolitan Region, the per-
centage of self-employed is above average. Further steps of analysis therefore
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Heinz Fassamann - Gerhard Hatz : The Austrian Case Study – Social Inequalities in the Vienna Metropolitan Region.
In: Social Inequalities in Urban Areas and Globalization. The Case of Central Europe.
Pécs: Centre for Regional Studies, 2007. 51-76. p. Discussion Papers, Special
have to prove if in those spatial units with high proportions of self-employed the
“dependent” social indicators such as income, living space per capita and the rate
of high school attendance show positive correlations. In that case it can clearly be
argued that the proportion of self-employed people characterizes the spatial pat-
tern of social inequality.
Figure 21
Self-employed, Vienna Metropolitan Region 2001
Social inequality in the Vienna Metropolitan Region is even more clearly and
precisely reflected by the distribution of highly qualified labor force than by the
share of self-employed (Figure 22). The indicator comprises employees with a
university degree in relation to the economically active population. The spatial
pattern reveals that the City of Vienna is still the prime residential area for highly
qualified labor force. On average 14% of the economically active population liv-
ing within the city boundaries hold a university degree, while the respective value
drops to half the amount in the suburban region.
What is also significant is the difference of coefficients of variation in the city
proper and the suburban region. While the indicator shows a relatively homoge-
nous distribution in the City of Vienna and suggests that – with the exception of
the typical working class districts of Favoriten, Simmering in the southeast, Flo-
ridsdorf in the northeast of the city as well as in the census tracts along the Gürtel,
the second ringroad around the inner districts 1–9, a considerable number of uni-
versity graduates lives in nearly all districts, the complete opposite can be noticed
in the suburban regions where this indicator is extremely unequally distributed. In
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Heinz Fassamann - Gerhard Hatz : The Austrian Case Study – Social Inequalities in the Vienna Metropolitan Region.
In: Social Inequalities in Urban Areas and Globalization. The Case of Central Europe.
Pécs: Centre for Regional Studies, 2007. 51-76. p. Discussion Papers, Special
a small number of communities beyond the city limits, especially in the south,
west and northwest of the city along the Danube, up to 25% of the population
hold a university degree. Communities and municipalities such as Klosterneub-
urg, Kaltenleutgeben, Mödling or Perchtoldsdorf are the “strongholds” of univer-
sity graduates in the metropolitan region. The coefficient of variation of a total of
62.2 in the suburban region is the highest among all indicators.
Figure 22
Highly qualified labor force, Vienna Metropolitan Region 2001
The distribution of university graduates is in total opposition to the distribution
of unskilled workers (Figure 23). This group constitutes on average 17.4% of the
entire economically active population, with only a slight difference between city
(17.9%) and suburban region (16.8%). Similarly, the coefficients of variation
hardly differ. Unskilled workers are highly segregated in the city as well as in the
outskirts. They live in environments that provide affordable housing and their
pattern of distribution points out a marked contrast to the distribution of the
highly qualified labor force.
In Vienna a high percentage of unskilled workers can be found in the working
class districts along the Gürtel, moreover in parts of Favoriten and Simmering in
the south-eastern and Floridsdorf in the north-eastern section of the city. The
south-western sector of the suburban region can be neglected in this respect,
whereas the percentages in the southeast and east along the Danube are above
average. This is mainly the result of property prices, because due to their limited
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Heinz Fassamann - Gerhard Hatz : The Austrian Case Study – Social Inequalities in the Vienna Metropolitan Region.
In: Social Inequalities in Urban Areas and Globalization. The Case of Central Europe.
Pécs: Centre for Regional Studies, 2007. 51-76. p. Discussion Papers, Special
income, unskilled workers are forced to move to neighbourhoods where they can
find affordable housing, either to buy or to rent. These are predominantly com-
munities in the eastern parts of the suburban region, which is fertile and produc-
tive farmland, though not considered as an attractive or idyllic location. In addi-
tion, some locations are dominated by the effects of specific functions or facili-
ties, like the refinery, the airport or the food plants in Schwechat, southeast of
Vienna, or traditional industrial cities in the south of the Vienna Basin going back
to the 19th century, like Wiener Neustadt.
Figure 23
Unskilled workers, Vienna Metropolitan Region 2001
The third combination of variables in the field of employment deals with
working hours. This category is split into three subcategories: the percentage of
full-timers (Figure 24), part-timers and marginal part-timers, reflecting the trend
to new flexible, untypical and precarious jobs.
In the Vienna Metropolitan Region regular full-time jobs are still the norm. On
average about three quarters of the active labor force in the city and almost 80%
in the suburban region hold jobs requiring approximately 40 hours per week. De-
pending on the sector, it can be slightly more or less, but 40 hours a week are
generally regarded as the official norm. This type of employment is still domi-
nating manufacturing, trade and a lot of service industries. In the census of 2001
those members of labor force working more than 32 hours weekly were labelled
as full-timers.
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Heinz Fassamann - Gerhard Hatz : The Austrian Case Study – Social Inequalities in the Vienna Metropolitan Region.
In: Social Inequalities in Urban Areas and Globalization. The Case of Central Europe.
Pécs: Centre for Regional Studies, 2007. 51-76. p. Discussion Papers, Special
The low values of the coefficient of variation (5.2 in the city and 3.0 in the sur-
rounding region) indicate that full-timers are equally distributed in the entire met-
ropolitan region. Although the spatial distribution shows that the percentages of
full-timers is higher in the more industrialized and agricultural communities in the
southeast, east and north of the city than in the south, southwest and the City of
Vienna itself, there are hardly any variations with regard to the means. Just like
the distribution of employment itself, the distribution of full-timers is similarly
equal.
Figure 24
Full-timers, Vienna Metropolitan Region 2001
The distribution of the part-timers, however, results in a different pattern (Fig-
ure 25). They amount to an average 10.4% in the city and 11.8% in the suburban
region. Part-time jobs are basically female, concentrate in few sectors like retail,
light industry, but also in private and public service industries, and are character-
ized by working-hours which are far less than the norm of 40. In the census of
2001 part-timers were considered as the active population working at least 12 up
to a maximum of 31 hours weekly. In many respects part-time work matches the
intentions of women who want to have their own income and combine job and
child care. Especially for women who live in the outskirts and have to cope with a
considerable amount of commuting a regular 40-hour-job can be very stressful.
Correspondingly, in the suburban region the percentage of female part-timers,
hardly any males, is considerably higher than in areas further away or in the city
itself. Yet, the specific local situation must not be overlooked, such as the influ-
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Heinz Fassamann - Gerhard Hatz : The Austrian Case Study – Social Inequalities in the Vienna Metropolitan Region.
In: Social Inequalities in Urban Areas and Globalization. The Case of Central Europe.
Pécs: Centre for Regional Studies, 2007. 51-76. p. Discussion Papers, Special
ence of shopping malls. This is why the communities in the vicinity of Shopping
City Süd, Shopping Center Nord or the Factory Outlet Center in Parndorf are
characterized by higher percentages of part-timers.
Figure 25
Part-timers, Vienna Metropolitan Region 2001
Finally, there is a third indicator called marginal part-timers (Figure 26).
These are members of the labor force who work part-time in what could be called
“mini jobs”. According to the census of 2001 marginal part-timer comprise active
labor force working up to 11 hours per week.
Marginal employment represents new forms of labor which can react to ex-
pectations of the labor market even more flexibly than traditional part-time work.
Again it is mainly women who accept marginal jobs either to supplement the
family income or to take on specific jobs in their husbands’ company, office or
surgery without having to bother about contributions to social security. These
types of employment have been created as a reaction to economic deregulation
and liberalization, and they probably do not point to social inequalities, but rather
to a total transformation of labor. It seems to be characteristic that these marginal
part-timers can be found in all the neighbourhoods with high percentages of self-
employed and university graduates. Respectively, these neighbourhoods are
mainly situated within the city proper, in the upscale districts in the west
(Döbling, Währing and Hietzing) and, beyond the city limits, in the south-western
segment of the suburban region and in Klosterneuburg in the north.
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In: Social Inequalities in Urban Areas and Globalization. The Case of Central Europe.
Pécs: Centre for Regional Studies, 2007. 51-76. p. Discussion Papers, Special
Figure 26 Marginal part-timers, Vienna Metropolitan Region 2001
Income
In most cases income will be allocated by employment and income is the main
source for all forms of social inequalities. Due to a certain level of income, spe-
cific parts of the city and the suburban region can be afforded and others cannot
(Figure 27). Therefore spatial inequalities can only be explained in a satisfactory
way when the income distribution is considered. Those who own available capital
can afford specific neighbourhoods, those who do not are displaced and forced to
move to less attractive locations.
Unfortunately, the census does not offer any direct data on the income
situation. Therefore the spatial income distribution was estimated by combining
two variables. The census provides very detailed information of the occupational
structure of the population in each of the census tracts and communities. The
second source of the income distribution for each of the occupational categories,
but without any spatial information, was the microcensus. The estimated income
per capita was calculated by multiplying the occupational distribution by the
average income for each of the occupational categories. It can be assumed that the
income per capita in each of the communities and census tracts is mainly linked to
the occupational structure and the spatial effect can be neglected. Shift and share
analyses show that this assumption is not perfectly true, even though the effect of
the occupational structure is much more important than the spatial effect.
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Heinz Fassamann - Gerhard Hatz : The Austrian Case Study – Social Inequalities in the Vienna Metropolitan Region.
In: Social Inequalities in Urban Areas and Globalization. The Case of Central Europe.
Pécs: Centre for Regional Studies, 2007. 51-76. p. Discussion Papers, Special
Figure 27
Income per capita, Vienna Metropolitan Region 2001
The average income per capita and per working hour varies from 10.0 € to
16.8 €. In individual cases the income difference can be higher but on average it is
around 1 to 1.7. The spatial distribution shows a very clear differentiation into
sectors. Within the city limits the districts in the western part (Döbling, Währing,
Hietzing) show a significantly higher income than that of the districts in the
southeast (Favoriten, Simmering) and the northeast (Floridsdorf, Donaustadt).
This sector of high income units reaches far beyond the city limits. In the subur-
ban communities in the north, west and southwest high income groups are living
and contrast to the more agrarian and low income sectors in the east and the
southeast. The more elaborate and socio-ecologically relevant analysis is aimed at
finding out which social structures are prevalent in the high-income neighbor-
hoods.
Housing and living conditions are directly linked to the economic position
which, respectively, depends on the integration in the labor market. The real es-
tate market, however, is also influenced by local conditions which can definitely
change this chain of cause and effect. Especially in rural areas relatively cheap
land and a good deal of neighborly help can compensate for lower incomes.
A key to social inequalities is homeownership (Figure 28). Owning or not
owning property was and maybe still is the most important feature of social dif-
ferentiation which further results in specific cultural and political attitudes. Those
owning a house or an apartment might think and act differently under certain cir-
cumstances than others. On the whole a little less than half of all households in
66
Heinz Fassamann - Gerhard Hatz : The Austrian Case Study – Social Inequalities in the Vienna Metropolitan Region.
In: Social Inequalities in Urban Areas and Globalization. The Case of Central Europe.
Pécs: Centre for Regional Studies, 2007. 51-76. p. Discussion Papers, Special
the metropolitan region own a house or an apartment, but it is three quarters in the
suburban region and only a quarter in the city itself. Whereas homeownership
practically occurs in the entire suburban region and there are hardly any differ-
ences between the individual sectors, homeownership within the city proper re-
veals a spatial concentration. The coefficient of variation amounts to 76.6, which
is the highest of all indicators in the city. Homeownership can only rarely be
found in the inner districts, whereas in the newly developed areas at the fringe of
the city it is by far more common.
Figure 28
Home ownership, Vienna Metropolitan Region 2001
The second indicator with regard to housing defines the available living space
per capita (Figure 29). Again it is not surprising that living space can be a meas-
ure for social inequality, in this case even in two ways: On the one hand vast liv-
ing space indicates that individuals or households have sufficient means of buy-
ing, renting or maintaining it. On the other hand the living space available has an
enormous impact on an individual’s quality of life, which, in turn, correlates with
social equality or social inequality.
On the whole an average of 40.1 m2 living space per capita is available to the
population of the entire Vienna Metropolitan Region, in the city itself it is 37.6
m2 and in the suburban region it goes up to 45.6 m2. The spatial distribution
shows a positive correlation with other indicators of social differentiation: in-
come, percentage of self-employed and university graduates. In the City of
Vienna the upper-class districts Döbling, Währing and Hietzing as well as the city
67
Heinz Fassamann - Gerhard Hatz : The Austrian Case Study – Social Inequalities in the Vienna Metropolitan Region.
In: Social Inequalities in Urban Areas and Globalization. The Case of Central Europe.
Pécs: Centre for Regional Studies, 2007. 51-76. p. Discussion Papers, Special
center itself are characterized by extensive living space per capita. The most
striking phenomena in the surroundings are the affluent south-western sector and
the agrarian communities in the north, east and southeast of the city. In these
communities it is the farms and the DIY-houses that are responsible for the in-
crease in the average living space.
Figure 29 Living space per capita, Vienna Metropolitan Region 2001
School attendance rate
In addition to employment, income and housing conditions, the school attendance
rate is also used as a variable determining social inequality (Figure 30). In this
context two aspects should be taken into consideration: on the one hand parents’
and teenagers’ pattern of behaviour deciding either to remain in the educational
system as long as possible or to drop out in order to be financially independent as
soon as possible. This decision is certainly heavily influenced by the cultural and
social background adults and teens are exposed to. As it is widely-known, social
inequality may also be passed on from one generation to the next. On the other
hand this variable points to the infrastructure of the communities or census tracts,
which can also be interpreted as spatial context of social inequalities. Spatial units
lacking infrastructure put the inhabitants at a disadvantage, whereas top infra-
structure means that the residents are in a privileged position.
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Heinz Fassamann - Gerhard Hatz : The Austrian Case Study – Social Inequalities in the Vienna Metropolitan Region.
In: Social Inequalities in Urban Areas and Globalization. The Case of Central Europe.
Pécs: Centre for Regional Studies, 2007. 51-76. p. Discussion Papers, Special
The school attendance rate of the 15- to 19-year-olds averages 42.9% in the
entire Vienna Metropolitan Region and there are only slight variations between
city itself (43.2%) and the surrounding areas (42.4%). The coefficients of varia-
tion hint at a “medium” inequality, which matches the variables income, univer-
sity graduates and living space per capita. Vienna’s upper-class districts as well as
the affluent south-western sector in the suburban region stand out with distinctly
higher attendance rates.
Figure 30 High school students, Vienna Metropolitan Region 2001
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Heinz Fassamann - Gerhard Hatz : The Austrian Case Study – Social Inequalities in the Vienna Metropolitan Region.
In: Social Inequalities in Urban Areas and Globalization. The Case of Central Europe.
Pécs: Centre for Regional Studies, 2007. 51-76. p. Discussion Papers, Special
Dimensions of social inequality
After the descriptive analyses of the variables, their spatial distribution and the
extent of segregation, the bivariate correlations and dependencies between the
variables has to be examined. In the course of this procedure this set of correla-
tions is going to be simplified and basic underlying factors of social inequality
and its spatial dimensions which cannot be determined a priori are extracted from
this larger set.
Bivariate correlations
At the beginning of the article the selection of variables was thoroughly dis-
cussed. It was assumed that employment was an important factor to explain social
inequality. Employment determines the level of income which, in turn, influences
the material and financial aspects of living standard and quality of life. Living
space and homeownership are equally dependent on the available income, the
same is true of other goods which, due to a lack of statistics, cannot be measured
(car ownership, household equipment, extensive and frequent long distance vaca-
tions, etc.). Finally, the school attendance rate of the 15-to 19-year-olds was in-
cluded in the analysis, which seems to depend on the financial background of the
parents, but which also reflects the existing infrastructure of the residential
neighborhoods.
In order to test these assumptions statistically, bivariate correlations based on
spatial units were calculated. All in all, this analysis, which can also be referred to
as ecological analysis, clearly proves the whole set of assumptions. Employment
determines the income. The higher the percentage of self-employed and especially
highly qualified labor force in a particular unit (census tract or community), the
higher the (estimated) income. The bivariate correlation between the percentage
of highly qualified labor force and income is about +0.7, which again emphasises
the importance of this indicator. None of the other indicators succeeds in marking
the extent of social and cultural inequality in the city and the suburban region in
the same way as the proportion of highly qualified labor force. It is also true the
other way round: the higher the percentage of unskilled workers, the lower the
income.
What is amazing is the correlation of the marginal part-timers with the local
level of income, which might indicate that wives are employed in the companies,
offices or surgeries of their husbands for a few hours per week, but it could also
be concluded that high income groups and new service industries available to
them exist side by side (Table 3).
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In: Social Inequalities in Urban Areas and Globalization. The Case of Central Europe.
Pécs: Centre for Regional Studies, 2007. 51-76. p. Discussion Papers, Special
Table 3
Correlation Coefficients, Vienna Metropolitan Region 2001
Nr. Indicator
1
2
3
4
5
6
7
8
9
10
11
1 Income per capita
x
2 Active labor force
-0.44
x
3 Highly qualified
0.70
*
x
labor force
4 Full-timers
*
* -0.25
x
5 Part-timers
0.31
*
*
*
x
6 Marginal part-timers 0.68 -0.45 0.55 -0.48
*
x
7 Unemployed
-0.26
*
* -0.72 -0.56
*
x
8 Self-employed
0.58 -0.24
* 0.26 0.39 0.35 -0.60
x
9 Unskilled workers
-0.75 0.30 -0.57 -0.23 -0.31 -0.44 0.53 -0.52
x
10 Living space per
0.61 -0.32
* 0.34 0.46 0.25 -0.70 0.79 -0.64
x
capita
11 Homeownership
*
* -0.41 0.54 0.41 -0.22 -0.73 0.44 -0.26 0.61
x
12 High school
0.80 -0.27 0.57
* 0.42 0.53 -0.41 0.58 -0.76 0.62
*
students
Source: Statistik Austria: Census 2001; author’s calculation.
By examining the variables associated with „housing“, income shows a posi-
tive correlation regarding living space per capita. The higher the average income
in a spatial unit, the more living space is available for the residents in this unit.
Vice versa, the higher the rate of unemployed or unskilled workers, the more
available living space per capita is declining.
Finally, there is convincing evidence that the assumed correlation between the
variable “high school students” and the socio-economic indicators as well as the
local infrastructure actually exists. The higher the income in a spatial unit – to-
gether with the percentage of self-employed and highly qualified labor force, that
refers to university graduates, – the more teenagers between 15 and 19 remain in
the educational system. Vice versa, the school attendance rate is declining in a
specific unit, if the percentage of unemployed or unskilled workers is high. Social
inequality is therefore something that can be inherited, and social inequalities also
continue in the next generation as a result of discrimination in education.
Multivariate Factor Extraction
Based on the analysis of bivariate correlations it might be assumed that the spatial
structure of social inequality is defined by only one differentiation: income which
is the result of qualification and labor market position. If this refers to the real
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Heinz Fassamann - Gerhard Hatz : The Austrian Case Study – Social Inequalities in the Vienna Metropolitan Region.
In: Social Inequalities in Urban Areas and Globalization. The Case of Central Europe.
Pécs: Centre for Regional Studies, 2007. 51-76. p. Discussion Papers, Special
situation, it can be revealed by Factor Analysis. It analyses the direct bivariate
effects, examines the input of more independent variables and suggests a
reduction of bivariate correlations to a few principal dimensions (factors). These
factors are artificial features which are results of mathematical and statistical
procedures and which cannot be measured directly.
The technique chosen for factor extraction involves primary components and,
subsequently, oblique rotation. Factors have been selected according to the
criteria of eigenvalues. The matrix of loadings presents an interesting, plausible
and not at all trivial explanation of the socio-economic structure and its related
spatial dimensions of social inequality in the Vienna Metropolitan Region. It
indicates that is not sufficient to emphasize just one dimension of social
inequality – for example income –, because the matter is much more complex
(Table 4).
Table 4
Factor loadings – oblique rotated factor matrix
Nr. Indicator
Factor 1
Factor 2
Factor 3
1 Income per capita (estimated)
0.905
-0.337
-0.540
2 Active labor force
-0.252
0.202
0.800
3 Highly qualified labor force
0.887
*
-0.225
4 Full-timers
*
-0.633
0.594
5 Part-timers
0.245
-0.590
*
6 Marginal part-timers
0.661
*
-0.770
7 Unemployed
*
0.925
-0.200
8 Self-employed
0.417
-0.746
-0.402
9 Unskilled workers
-0.837
0.546
0.202
10 Living space per capita
0.436
-0.865
-0.296
11 Homeownership
*
-0.838
*
12 High school students (aged 15–19 years)
0.859
-0.475
-0.326
Explained Variance (in %)
35.0
30.4
13.9
Annotation: Loadings between .200 and -.200 are represented by ‘*’. The technique chosen for
factor extraction involves primary components and, subsequently, oblique rotation; factors have
been selected according to the criteria of eigenvalues.
Source: Statistik Austria: Census 2001; author’s calculation.
The first factor describes the effect of position on the labor market and income
on the spatial pattern of social inequality. The first factor is certainly the most
important one and explains 35% of total variance of all input variables. It shows
high loadings with regard to the percentage of the highly qualified labor force, to
the level of income and the school attendance rate as indicated by the share of
high school students aged 15–19 years, and – interestingly, to the marginal-
employed part-timers.
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In: Social Inequalities in Urban Areas and Globalization. The Case of Central Europe.
Pécs: Centre for Regional Studies, 2007. 51-76. p. Discussion Papers, Special
The spatial pattern of this factor is clear (Figure 31). Its significance is obvi-
ous in the Vienna city center and in the upper-class districts in the west of the
city. It continues throughout the privileged south-western sector of the suburban
region along the slopes of the Vienna Woods as far as the fringe of the Vienna
Basin, and it also spreads to the suburban districts in the north. The factor load-
ings decrease with a growing distance to the city. This means: the further one
moves from the city limits, the lower the average income and the more distinct is
the decline in the percentages of highly qualified labor force and in the school
attendance rate of the 15- to 19-year-olds. Middle and upper classes are replaced
by a social structure dominated by lower and middle classes.
Figure 31 Dimension of income, Vienna Metropolitan Region 2001
The second factor basically resulting from unemployment und indicators re-
lated to housing turns out to be independent of the social stratification. High un-
employment rates in a specific spatial unit, combined with a low rate of home-
ownership and limited living space per capita cannot simply be matched with a
very basic social model of “top-bottom”. This factor contributes with a value of
30% to the explanation of the total variance of the analyzed variables and there-
fore has to be regarded as very important for the set of data and for the entire Vi-
enna Metropolitan Region.
Unemployment together with a low standard of housing is a typical
phenomenon of the City of Vienna and a small number of selected communities
in the southern part of the suburban region which are dominated by old industries
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In: Social Inequalities in Urban Areas and Globalization. The Case of Central Europe.
Pécs: Centre for Regional Studies, 2007. 51-76. p. Discussion Papers, Special
(Figure 32). Within the city proper all census tracts along the Gürtel, but also a
few in the east, in the districts of Floridsdorf and Donaustadt are characterized by
this combination of variables. It can be assumed that even more variables which
are not included in this analysis correlate with this factor: the proportion of late–
19th century working class apartment blocks, the proportion of low-standard
apartments lacking up-to-date sanitation and the proportion of immigrants not
holding Austrian citizenship.
Häussermann and Siebel (1987) quite drastically referred to this structure as
the marginalized city of peripheral groups, the excluded, the jobless without any
chance of work, the immigrants. The two authors regarded the typical neighbor-
hoods inhabited by these groups as mentally segregated, the complete opposite to
the globalized or international city of the affluent, educated and highly-qualified
population.
Figure 32
Dimension of marginalization, Vienna Metropolitan Region 2001
At last a third factor which characterizes social inequality but cannot be linked
to the other two factors has to be considered. Explaining 14% of the total variance
of all indicators selected for the analysis, this third factor is not so significant, but
it cannot be totally ignored. It is constituted by a high percentage of members of
the active labor force, full-timers and low rates of marginal part-timers. This fac-
tor refers to the traditional world of labor, which can either be influenced by agri-
culture, industry or trade and which cannot unquestioningly be assigned to the
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Heinz Fassamann - Gerhard Hatz : The Austrian Case Study – Social Inequalities in the Vienna Metropolitan Region.
In: Social Inequalities in Urban Areas and Globalization. The Case of Central Europe.
Pécs: Centre for Regional Studies, 2007. 51-76. p. Discussion Papers, Special
“top” or to the “bottom”. What is meant in this context is the “normal” city pro-
viding work, supplies and housing (see Häussermann and Siebel 1987), which is
neither marginalized nor particularly chic, modern, fashionable or trendy. In Vi-
enna this applies to some parts of the working class districts like Ottakring along
the Gürtel in the western section of the city, but also the newly-developed housing
estates in the south, close to the city limits (parts of the districts Liesing and Fa-
voriten). In addition, most of the communities in the southeast, east and north of
the city can be counted among the “normal”, ordinary ones, which are neither
particularly upscale nor extremely marginalized (Figure 33).
Figure 33
Dimension of the middle class, Vienna Metropolitan Region 2001
Conclusion
Social inequality always has a spatial dimension, which is the main focus of the
present article. At first, it has proven the spatial dimensions by means of simple
univariate statistics and, in a next step, by means of factor analysis. The empirical
analysis comes to the same conclusion as Häussermann and Siebel, who already
introduced the idea of a city divided into three sectors in 1987.
This type of a city is characterized by three separate social milieus, which are
segregated from each other and whose development is due to completely different
processes. The first sector is the city of the rich and educated who benefit from
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In: Social Inequalities in Urban Areas and Globalization. The Case of Central Europe.
Pécs: Centre for Regional Studies, 2007. 51-76. p. Discussion Papers, Special
the globalized economy. They live in the city center, the upper-class neighbour-
hoods and the “affluent” suburbia. They use the airport, cultural facilities in the
city and high-quality services. These provisions determine their scope of action.
In this paper the second city refers to the city of the marginalized groups, con-
sisting of the unemployed, an underclass dealing with multiple social problems
like poverty, homelessness and drug abuse, and, finally, specific groups of immi-
grants. Their city is made up of small units and they live in rather distressed
neighbourhoods providing cheap housing. They do not have any contact to the
globalized economy and their actions are restricted to their immediate neighbor-
hood or a few intersections of public transport.
Last but not least, the third city has to be mentioned, the “normal” city pro-
viding work, supplies and housing. Its population consists of “ordinary” people,
neither particularly affluent and well-educated nor extremely poor or marginal-
ized. It is the city of the middle class, making up the largest part of the entire Vi-
enna Metropolitan Region. It comprises the “working-class” districts of the city
itself, reaches far beyond the city limits and can be found in all areas with attrac-
tive property prices. The inhabitants rarely use the airport, the high-class cultural
facilities and the globalized service industries in the city. Their actions concen-
trate on where they live and work and on a limited number of cultural and sports
facilities. The third city is not directly influenced by globalization, but by local
and national political and planning decisions.
This city that is divided into three parts and the suburban region cannot be in-
terpreted statically, but is undergoing continuous transformation. The first city
can expand into sectors of the third city, the second city can relocate its small-
scale centres. The dynamics of this development has not been topic of this analy-
sis and therefore predicting the future can rather be understood as clairvoyance
than as a result of a profound analysis. But it can be assumed that due to global-
ization and internationalization on the one hand and the ongoing transformation of
the welfare system on the other hand the polarization of social inequality and,
thus, the division of the city in three parts will rather be increasing than decreas-
ing. Especially the first city will be the “powerhorse” of the economic develop-
ment and, at the same time, the marginalized city will be growing, due to a social
network that nowadays is not as tightly knit as it used to be. Polarizations will be
more characteristic of the social reality in a city than a homogeneous structure.
76