Dynamics of unemployment and low-wage jobs – a longitudinal perspective

A recent longitudinal study sheds light on the dynamics of unemployment, atypical employment and low-wage jobs in Austria. As the stability of European labour markets has decreased over the past 30 years, longitudinal studies have increasingly become more important than conventional ‘snapshot’ forms of labour market analysis. They capture the dynamics of labour market processes by revealing a more detailed picture of workers’ long-term employment history.

About the study

A longitudinal study, The structure and dynamics of unemployment, atypical employment and low-wage jobs’ (in German, 2.49 KB PDF), was carried out by the Austrian Institute of Economic Research (WIFO). It is based on the statistical analysis of social security data (provided by the Main Association of Austrian Social Security Institutions) linked with data from the Public Employment Service (AMS).

The analysis focuses on data about the Austrian population of working age over a period of 10 years, between 2000 and 2010. To identify low-wage jobs, the study uses the common definition that sets the low-wage threshold at less than three-thirds of the median national income for full-time employment.

The analysis consists of three parts. It first deals with the structure of unemployment, low-wage jobs, part-time work and temporary employment for the period covered, 2000–2010, to identify groups particularly at risk. Then it draws attention to different patterns of heterogeneous employment histories within the 10-year period. Finally, the study tries to extrapolate upward and downward mobility patterns, and to identify specific labour market positions in which there is little or no movement, such as unemployment and low-wage work.

Key findings

Structure of unemployment

Beginning with the groups most affected by unemployment and low-wage jobs, the longitudinal data indicate a clear concentration of unemployment over time within a relatively small group of people, and this means that the same group also has a high risk of social exclusion. This risk is particularly high among low-skilled workers and foreign nationals.

Researchers analysed the composition of particular groups of workers, focusing first on the 5% who had accumulated most days of unemployment during the 10-year period studied.

Among foreign nationals, workers of Turkish nationality were overrepresented in this group, accounting for close to one-fifth (17.9%) of these workers (Figure 1), far above the average for the whole labour force. A logistic regression analysis shows a Turkish national’s risk of belonging to this group is three times higher than that for Austrian nationals. Also overrepresented were poorly skilled workers (8.4%), older workers (8.5% of those aged 45–65) and workers with a secondary school diploma (6.1%).

Figure 1: Composition of 5% of labour force that accumulated most days’ unemployment, 1999–2010 (%)

Figure 1: Composition of 5% of labour force that accumulated most days’ unemployment, 1999–2010 (%)

Source: WIFO (2013); Social security data/data from Public Employment Service, 1999–2010

Structure of low-wage jobs

Between 2000 and 2010, 60% of the working age population had never been in a low-wage job, and a further 5% had only spent very limited periods in such jobs (up to 17 days). The study reveals that 15% had considerable experience of low-wage jobs. Of these, 5% were in low-wage jobs for 1,147 days, or an average of three years, a further 5% for 4.7 years and the remaining 5% for eight years. The study’s analysis of the composition of these groups provides a similar picture to that for the structure of unemployment. There is a sizeable group (15%) within the low-wage group that is affected by low-wage jobs to a significantly higher degree than the rest, indicating a persistence in their situation, and a high risk of reduced opportunities for social participation.

The study shows that low-wage jobs do have a clear gender bias. During the period covered, nearly every second female worker (48%) was affected by low-wage employment, compared to only every fourth male worker (25.9%).

For women, the risk of being among the 5% who spent most days in low-wage jobs during the period studied was three times higher than for men (Figure 2). The risk was 2.5 times higher for workers from the former Yugoslavia than for Austrian nationals. Being in this group is a further indicator for considerable long-term persistence in low-wage employment.

Figure 2: Composition of the 5% of the labour force that spent more days than any other group in low-wage jobs, 1990–2010 (%)

Figure 2: Composition of the 5% of the labour force that spent more days than any other group in low-wage jobs, 1990–2010 (%)

Source: WIFO (2013); Social security data/data from Public Employment Service, 1999–2010

Persistence in low-wage work showed a strong female bias. Every fifth female worker who was in a low-wage job in 1999–2000 was also found to be in low-wage employment in 2009–2010. While 69% of men had managed to get out of low-wage work during this period, only 35% of women had managed to move on to better-paid work. The study showed that women were much more likely to move from low-wage jobs into atypical employment (33%).

However, the study also reveals that a large proportion of workers succeeded in getting out of low-wage jobs, particularly younger workers and those with higher educational certificates.

Employment history patterns

The study extracted typical employment histories from the longitudinal data. This was done in three steps. The authors first divided the whole period into phases of two years, and for each individual determined a dominant labour market position for this period. Next, they identified employment history patterns connecting six two-year periods. Finally, the frequency and the structure of these patterns were described according to social categories.

The study differentiates between seven labour market positions:

  • standard employment;
  • atypical employment (part-time work, temporary agency work, service contracts, marginal employment);
  • low-wage work (full time);
  • unemployment;
  • out of labour force;
  • hybrid trajectories;
  • retirement/death.

Within a two-year period, spending 50% or more of that period (or 25%–50% if this is the highest score) in one of the six labour market positions is defined as an individual’s dominant labour market position.

Table: Typical employment history patterns, 1999–2010 (%)




Dominant standard employment




Dominantly out of labour force




Dominant atypical employment




Dominant low-wage work




Hybrid trajectories




Dominant unemployment








Source: WIFO (2013); Social security data/data from Public Employment Service, 1999–2010

The table shows the average of all six two-year periods, indicating that 40% of Austria’s working age population can be described as being in ‘dominant standard employment’ (men, 54.5%, women, 24.9%), and this is still the dominant pattern of all employment histories. About 19% of the population belong to the ‘dominant atypical employment’ pattern and another 5% to ‘dominant low-wage work’ pattern. Just over 3% show an employment history dominated by unemployment and another 6% could not be related to any kind of dominant labour market status. A considerable proportion of the working population as it was in 1999–2000 is either ‘dominantly out of the labour force’ (16.3%) or ‘retired/dead’ (19.5%).

Segmentation of the labour market

The study tried a further step of data aggregation, building three patterns out of the former seven categories of labour market position, looking at different levels of labour market integration.

The results suggest that about a quarter (25.3%) of Austria’s working age population is constantly in stable full-time jobs with incomes above the low-wage threshold. Nearly another quarter (22.3%) have employment histories mainly characterised by standard employment relationships. These two patterns are agglomerated to an overall pattern that researchers describe as ‘well-integrated into paid employment’, and including about half of the working age population (48.2%). Men (80%), those of Austrian origin and those with higher occupational certificates are overrepresented in this pattern, while women, migrant and poorly skilled workers are underrepresented.

By contrast, the study identifies just short of one in five workers (18.9%) who have longer phases of low-wage employment or unemployment. This pattern is called ‘employment histories with some phases of exclusion’. Female workers, younger workers, those with a migration background and those with apprenticeship certificates and a secondary-school diploma (Matura) are overrepresented in this pattern.

Within this pattern, the authors differentiate between ‘employment histories with minor exclusion’, which affects 12.4% of the population, and ‘employment histories with major or durable exclusion’ (6.5%). This second segment has a much higher percentage of women (69%) than the first (51%). Foreign nationals are also overrepresented in the second segment. In about a third of the employment histories (32.9%), a clear pattern could not be distinguished.


The study offers a very interesting glimpse into the long-term dynamics of employment histories. The longitudinal perspective, following the labour market trajectories of individuals over a 10-year period, allows a much deeper understanding of processes of integration into paid employment and the circumstances that lead to social exclusion. The study reveals considerable segmentation of the Austrian labour market, showing that certain groups of workers face employment histories dominated by unemployment or low-wage jobs even over a 10-year perspective. Although these groups still form a minority in Austria, the results indicate a high risk of persistent social exclusion for these groups.


WIFO (2013), The structure and dynamics of unemployment, atypical employment and low-wage jobs – A longitudinal analysis 2000–2010 (in German, 2.49 KB PDF), Austrian Institute of Economic Research, Vienna.

Manfred Krenn, FORBA

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