Changes in the returns to education at entry into the labour market in West Germany

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  • 1 University of Bern, , Switzerland
  • | 2 Otto Friedrich University Bamberg, , Germany
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This article studies to what extent societal processes such as educational expansion, economic modernisation and business cycles have affected the returns to educational certificates of women and men entering the labour market in West Germany. Using longitudinal data, long-term changes in cohort- and period-specific effects on socio-economic status attainment at entry into the labour market are investigated between 1945 and 2008. Analyses demonstrate that the entrants’ average socio-economic prestige scores have clearly risen in the process of modernisation. Despite educational expansion, increasing skill demands for highly qualified graduates resulted in rising rates of returns for the most highly educated entrants across birth cohorts. While educational expansion and economic modernisation have boosted socio-economic returns at entry into the labour market for women from all educational levels, it has not been the case for men with the lowest levels of education. Both educational expansion and rising skill requirements of occupations led to an increasing polarisation of inequality between tertiary educated labour-market entrants and less-qualified school leavers. Educational expansion in West Germany has therefore never exceeded the occupational skill demands at entry into the labour market.

Abstract

This article studies to what extent societal processes such as educational expansion, economic modernisation and business cycles have affected the returns to educational certificates of women and men entering the labour market in West Germany. Using longitudinal data, long-term changes in cohort- and period-specific effects on socio-economic status attainment at entry into the labour market are investigated between 1945 and 2008. Analyses demonstrate that the entrants’ average socio-economic prestige scores have clearly risen in the process of modernisation. Despite educational expansion, increasing skill demands for highly qualified graduates resulted in rising rates of returns for the most highly educated entrants across birth cohorts. While educational expansion and economic modernisation have boosted socio-economic returns at entry into the labour market for women from all educational levels, it has not been the case for men with the lowest levels of education. Both educational expansion and rising skill requirements of occupations led to an increasing polarisation of inequality between tertiary educated labour-market entrants and less-qualified school leavers. Educational expansion in West Germany has therefore never exceeded the occupational skill demands at entry into the labour market.

Key messages

  • Due to the upgrading of the occupational job structure, human capital investments have not become devalued in the course of rapid educational expansion across cohorts in Germany.

  • The opposite in true: young people who have attained higher education, intermediate general or vocational education in Germany have received even higher job returns to their educational investments at labour-market entry and during their later job career.

  • In particular, young qualified German women have benefited from the interrelated changes of educational expansion, sectoral tertiarisation and occupational upgrading.

  • German males who have left the school system without any educational certificate or certified vocational training might be called the losers of educational expansion and occupational upgrading. Their job opportunities have worsened drastically in the recent period.

Introduction

Since the seminal work by Goldin and Katz (1998; 2007; 2009) on the ‘race between education and technology’ (Acemoglu, 2002; Autor et al, 2006; Acemoglu and Autor, 2012), the interest in returns to education in the course of educational expansion and the change of the occupational structure has greatly increased among economists and social scientists (see, for example, Hannan et al, 1990; Beaudry and Green, 2003; Boockmann and Steiner, 2006; Okazawa, 2013; Hirsch-Kreinsen, 2016; Reinhold and Thomsen, 2017). First of all, neoclassical growth theory claims that there is a close relationship between investments in education and economic growth, as better educated people have a higher productivity, which results in higher economic output and better standards of living both at individual and societal level (Tinbergen, 1972). According to this view, ‘rapid technological change would increase the demand for more educated workers at all levels. With increased demand for their services, the earnings of the more educated would rise relative to the less educated’ (Goldin and Katz, 2009: 2). A recent study on West German men indeed demonstrated that the returns to education have increased rather than declined at labour-market entry and during the subsequent career in times of educational expansion (Becker and Blossfeld, 2017).

Since German women have caught up with men in terms of educational attainment across birth cohorts in the course of educational expansion and have even surpassed men regarding higher-education entrance qualifications as well as university degrees among the younger cohorts, the goal of the present study is to reveal for both genders how the race between educational expansion and the long-term modernisation process affects the returns to education in the labour market. We exclusively study the changes at entry into the labour market, because women’s career profiles are still hard to compare with men’s: after childbirth, great proportions of West German women still interrupt their employment or work only part-time. Therefore, the labour-market entry is the only point in time at which the gender differences in returns to education can be analysed without gender-specific life courses biasing the comparison.1

In contrast to previous labour-market studies mostly employing only aggregated time series data, the present study includes both individual-level data and aggregated time series data in regression analyses. With those models, it is therefore possible to estimate and compare the effects of technological change on the rates of return to education for young women and men more explicitly. Covering a rather long historical period in West Germany (1945–2008), the focus is on a broader measurement of the returns to education. We use socio-economic scores based on the Magnitude Prestige Scale (Wegener, 1988) as a measure of the ‘goodness’ or ‘desirability’ of graduates’ first significant jobs reflecting not only material but also non-material rewards, such as job responsibilities, job satisfaction, reputation or authority (Goldthorpe and Hope, 1972; for critics, see: Hauser and Warren, 1997). The remarkable stability of occupational status rankings across time is a first advantage of measuring returns by this socio-economic scale. Additionally, these socio-economic scores describe women’s labour-market situation in the service sector better than alternative indicators (Warren et al, 1998; Manzoni et al, 2014: 1291).

The article is organised as follows: the next section shortly describes the processes of educational expansion, economic modernisation and the ups and downs of the business cycle in West Germany between 1945 and 2010. Then, based on economic and sociological labour market theories, hypotheses for the multivariate analysis of the returns to education of women and men at labour-market entry are deduced. In the subsequent section, the data sets, variables and methods are described. The empirical evidence on gender differences is presented and, in the final section, the findings are summarised and discussed.

Historical developments and theoretical background

Educational expansion in West Germany – the gender reversal

In all industrial societies, education has expanded across the last five decades (Breen et al, 2009), in particular for women (DiPrete and Buchmann, 2013; Schoon and Eccles, 2014; Blossfeld et al, 2015; 2016). Hirsch (1977: 11) argues that economic growth and rising standards of living have not only broadened the demand for educational participation but have also decreased the social and economic hurdles that traditionally limited enrolment in higher education. Thus, in the process of modernisation there seems to be an inherent tendency towards the expansion of educational attainment (Becker and Mayer, 2019). In West Germany, the share of the population attaining advanced school degrees, vocational education and training, as well as tertiary education has risen sharply over the last decades. Across cohorts, women surpassed men particularly in attaining the eligibility to study at academic universities (Universitäten) or universities of applied sciences (Fachhochschulen) (Figure 1).

Educational expansion: eligibility for education at traditional university (Abitur) or at university of applied sciences (Fachhochschulreife) in West Germany, 1950–2005. Educational expansion in West Germany across periods between 1950–2005. Indication of this trend by increase of percentage of women and men becoming eligible for training at universities. Increase of this share for women from 3 per cent in 1950 to 28 per cent in 2005 and for men from 6 per cent in 1950 to 21 percent in 2005.
Figure 1:

Educational expansion: eligibility for education at traditional university (Abitur) or at university of applied sciences (Fachhochschulreife) in West Germany, 1950–2005

Citation: Longitudinal and Life Course Studies 13, 1; 10.1332/175795921X16197756998006

Source: Köhler and Lundgreen, 2014; 2015; own compilation and presentation.

While in the early 1950s, only about 3% of women and 6% of men were eligible for university education, this gap turned around in the early 1980s. Since then, the ‘reversed gender gap’ has become a persistent and striking feature of the educational system in (West) Germany (Buchholz et al, 2015: 253). In 2005, 28% of women and 21% of males attained the eligibility for university training (Abitur, Fachabitur or Fachhochschulreife).

A similar development has taken place with regard to enrolment in university education (Figure 2). In West Germany, the total number of students enrolled at universities has risen impressively, from 111,000 students in 1952 to 1.8 million in 2008. After German unification in 1990, 1.7 million students were enrolled in Germany and about 2 million in 2008. In 2017, this enrolment in tertiary education rose even further to 2.8 million students. In 1950, at the age of 22, about 4% of men and 1% of women started their university education while 12% of women and 17% of men became freshmen in 1984. Five years after German unification, this age-related enrolment was similar for both genders (27.5%). In the years up to 2008, the enrolment has remained at a rather high but stable level and women have surpassed men (women: 41%; men: 40%) (Blossfeld, 2017).

Educational expansion: freshmen in universities (percentages, 19–23) in Western Germany (1952–1993) and in unified Germany (1994–2008) as well as absolute numbers of students (in 100,000). Educational expansion in West Germany across periods between 1950–2008. Indication of this trend by percentage of university freshmen in age 19-23 as well as absolute numbers of students (in 100,000). Increase of percentage from 1 per cent for women and 3 per cent for men in 1952 to 41 per cent for both genders in 2008. Increase of absolute numbers of students from 100,000 in 1952 to 2 Million in 2008.
Figure 2:

Educational expansion: freshmen in universities (percentages, 19–23) in Western Germany (1952–1993) and in unified Germany (1994–2008) as well as absolute numbers of students (in 100,000)

Citation: Longitudinal and Life Course Studies 13, 1; 10.1332/175795921X16197756998006

Sources: (a) 1952–1984 (enrolment at age 22): Köhler, 1978; 2008; (b) 1985–2008 (first enrolment): Nationaler Bildungsbericht, 2006–2016; (c) Number of students in 100,000: German Federal Office of Statistics, 2018; own compilation and presentation.

In the same period, between 1971 and 2005, there has been a decline in the number of school leavers without any vocational training certificate (Figure 3). In this context, it is worth stressing that educational expansion resulted in a decreasing proportion of school leavers with a lower secondary school qualification (Hauptschulabschluss) or without any certificate at all across birth cohorts. In particular, the share of females with the lowest educational level has sharply decreased as women have profited more than their male counterparts from the expansion of the upper secondary school. Whereas in 1971, 21% of men and 17% of women left school without any training degree, by 2005 these percentages had decreased to about 10% for men and 6% for women.

Educational expansion: women and men without any school graduation or without vocational education or training in West Germany, 1971–2005. Decrease of share of graduates without any educational certificates or lower secondary school certificates across the periods between 1971–2005.
Figure 3:

Educational expansion: women and men without any school graduation or without vocational education or training in West Germany, 1971–2005

Citation: Longitudinal and Life Course Studies 13, 1; 10.1332/175795921X16197756998006

Notes: missing values in the time series were interpolated – own calculation and presentation.Sources: (a) Köhler and Lundgreen, 2014 for female and male graduates without any school certificate; (b) Standing Conference of the Ministers of Education and Cultural Affairs, 2018 for population and female share without any school certificate as well as population and female share with lower secondary school certificate; (c) Federal Ministry of Education and Research, 2018 for population and female share without any school certificate as well as population and female share with lower secondary school certificate and the development of attainment of vocational education and training degrees.

In summary, there has been an impressive long-term expansion of education in (West) Germany from the end of the Second World War until today. Women’s aspirations and attainment in higher education might have been initialised – among other emancipative reasons such as striving for economic independence and reaching an autonomous life course (DiPrete and Buchmann, 2013) – by several social changes, including the expansion of public employment, the growing demand for highly qualified female workers in the welfare and service sectors, and the improved opportunities for combining family and work outside the home (Becker, 2014). The question therefore arises whether the fact that educational credentials have become higher for each successive young cohort of women and men has also changed the value of higher certificates at entry into the labour market (see also Manzoni et al, 2014). The extent to which the expansion of education affects the value of education in the labour market across cohorts is, of course, also dependent on the changing skill demands in the occupational structure in the same historical period.

Economic modernisation and business cycles in West Germany: trend towards qualified (female) service jobs

For advanced societies, empirical evidence based on employment statistics shows with an impressive regularity that the greatest rises in non-manual employment since the 1970s have occurred not in relatively low-level clerical, sales and personal service grades, but rather in professional, administrative and managerial occupations (Blossfeld and Hofmeister, 2006; Manzoni et al, 2014); and that expansion of public sector employment has played an important role in this process (Buchholz and Kurz, 2008: 58). In addition, in manual employment the major declines have occurred in the less skilled rather than the more skilled job categories (Erikson and Goldthorpe, 1992; DiPrete et al, 1997; Oesch, 2013; Manzoni et al, 2014). Finally, the latest comparative OECD studies demonstrate that the most recent technological advancements of automation, robotisation and digitalisation have systematically led to an upgrading and not a downgrading of the skill structure of jobs in modern knowledge societies (Arntz et al, 2016).

For West Germany in particular, it is well documented that the process of economic modernisation, in terms of technological advance and sectoral change, has resulted in an increasing demand for a more qualified and highly qualified workforce as well as in the change of occupational structure towards service jobs (Schmid, 2000) – especially for women (Blossfeld, 2017; Buchholz and Grunow, 2008: 64; Figure 4). This trend in the occupational structure has been dominated by a process of cohort replacement, that is, the labour-market entry of younger cohorts who benefited from educational expansion. The expansion of the education system itself, the expansion of skilled welfare services, and the creation of new entry jobs with advanced skill requirements have mainly attracted highly qualified female employment (Buchholz et al, 2015).

Trend of female and male employment in West Germany (1945–2010). Process of tertiarization of occupations and jobs in West Germany (1945–2010). Linear increase of female employment in the after-war period. Higher degree of tertiarization for women compared to men.
Figure 4:

Trend of female and male employment in West Germany (1945–2010)*

Citation: Longitudinal and Life Course Studies 13, 1; 10.1332/175795921X16197756998006

Sources: Destatis (German Federal Statistical Office) – own compilation and presentation. https://www-genesis.destatis.de/genesis/online

By 2010, almost three quarters of the workforce were employed in the (skilled and highly skilled) service sector, one quarter in industry and only 2% in agriculture or forestry (Figure 4). In Germany, the development of labour-force participation has been different for women and men: males’ labour-force participation (at age 15–65) has actually decreased from 94% to 82% in the years 1950–2010 due to increasing educational participation and early retirement. Women (in the same age span), however, have increased their labour force participation from 44% to 69% due to decreasing family-related job interruptions (Rahlf, 2015; 2016). Thus, for West Germany, it is important to stress that the level of female labour-force participation (1950: 31%; 2010: 45%) has strongly converged with that of males (1950: 64%; 2010: 56%) while gender segregation related to employment in the tertiary sector has remained fairly constant until the recent periods (Figure 4). However, one has to note that the impressive expansion of female labour-force participation in West Germany has been largely based on the expansion of the service sector and of part-time employment (Blossfeld and Hakim, 1997).

The development of the labour market from the early 1950s until today has not only been characterised by technological advances, but also by economic cycles. The unemployment rate, for example, was high in the immediate post-war period (11% in 1950), but then markedly declined until the end of the 1960s (0.7% in 1966). However, after the oil price shock in 1973, West Germany witnessed stepwise increases in unemployment rates from one economic cycle to the next. In 1975, for example, 4.7% of the labour force was unemployed and unemployment increased to 9.3% in 1985, 10.8% in 1997 and 10.2% in 2006.

Only recently has there been a decline in unemployment due to strong growth rates and labour-market reforms. In the context of the present study, it is important to note that in (West) Germany the unemployment rates have strongly varied with educational attainment: they have always been much higher for people with lower educational attainment levels. Thus, low-qualified and untrained employees have been hit by unemployment more directly.

Using ten time series on relevant aspects of the socio-economic development in West Germany from German official statistics for the years 1945–2010, two macro indicators have been extracted by factor analysis that appropriately describe the process of economic modernisation and the cyclical changing labour-market development in (West) Germany between 1945 and 2010 (Figure 5).2 The course of these indicators reflects the post-war economic history of the Federal Republic of Germany in terms of the modernisation trend and the labour-market conditions affected by the business cycles. Figure 5 shows the phases of economic boom (for instance, the German economic miracle in the 1950s and 1960s, or the economic upswing after German unification in 1990) and recessions (such as the economic crisis in 1967, oil price shocks in 1975 and 1982 and the recessions in 1993, 2003 and 2009) in West Germany. The German labour market is linked with increasing skill requirements and a cyclical pattern of demand and supply of workers (for example, the shortage of labour in the post-war era or unemployment during periods of recession). Figure 5 therefore demonstrates that each younger birth cohort entering the West German labour market experienced both (1) a monotonically increasing modernisation level of the occupational structure and (2) increasingly shorter and more dynamic business cycles.

Trend of modernisation and changing labour-market conditions in West Germany (1945–2010). Linear trend of economic modernisation in West Germany since 1945. Non-linear trend of labour market conditions following the economic cycles in the after-war periods.
Figure 5:

Trend of modernisation and changing labour-market conditions in West Germany (1945–2010)*

Citation: Longitudinal and Life Course Studies 13, 1; 10.1332/175795921X16197756998006

Note: * Modified factor scores (by adding the minima to the original factor scores).Source: Becker and Blossfeld (2017: 120).

Theoretical background and hypotheses about changes in returns to men’s and women’s education at entry into the labour market

In the following, we formulate six hypotheses that guide our empirical analyses. Based on labour-market theories and the concrete historical development in West Germany, we specify hypotheses regarding the (gender-specific) changes in the returns to human capital in the course of educational expansion, the modernisation process and the business cycles at entry into the labour market.

According to economic and sociological labour-market theories – such as the human capital approach (Mincer, 1974; Becker, 1975), the signal theory (Arrow, 1973; Spence, 1973; Stiglitz, 1975), the job competition theory (Thurow, 1975), as well as the theory of segmented labour markets (Doeringer and Piore, 1971; Blossfeld and Mayer, 1988) – formal general education, vocational training as well as university degrees, are expected to have strong positive effects on status attainment at entry into the labour market. In the German case, the link between educational attainment and socio-economic status should be exceptionally strong because the German educational system is not only highly stratified and standardised but has also a powerful vocational orientation due to the German dual system. Educational credentials in Germany should therefore matter greatly for occupational attainment right from the start of the job career (Manzoni et al, 2014). Thus, we expect that the higher the educational level of young occupational beginners, the higher their returns to education at first entry into the labour market (hypothesis 1).

Although this hypothesis has generally been confirmed in labour-market studies, there are few analyses that explicitly take the changes of the demand side of the labour market into account – namely the progressing modernisation process of the economy and the changing business cycle (Hannan et al, 1990). This article is unique in the sense that it analyses to what extent economic modernisation has an impact on men’s and women’s returns to education at labour-market entry. Across cohorts, we expect a rise of socio-economic rewards at entry into the labour market in the process of modernisation for both genders (hypothesis 2.1). Whether men or women get higher returns to their education attainment levels is an empirical question. Since the labour-market conditions have become increasingly cyclical since the end of the ‘German economic miracle’ in 1973, we anticipate that the socio-economic job rewards of first-time employees born after the mid-1960s will also reflect these ups and downs in their job rewards (hypothesis 2.2).

In sum, due to educational expansion, the continuous modernisation process in the economy and the increasingly cyclical labour-market conditions, the patterns of men’s and women’s labour-market entrance are expected to have become more dynamic across cohorts and the returns to education increasingly less predictable. However, based on traditional economic theory, we assume that the male and female beginners’ returns to education at entry into the labour market increase with the level of modernisation (hypothesis 3). In addition, we expect that more favourable labour-market conditions at labour-market entry are connected to higher rewards for men and women in terms of their first socio-economic position and vice versa (hypothesis 4).

Because advanced formal qualifications become a key factor in the modernisation process, we anticipate that the qualified and highly qualified young women and men entering the labour market get direct access to the newly created skilled jobs leading to higher returns to education. Conversely, the unskilled female and male job-starters are expected to be penalised by increasingly lower returns due to the accelerating disappearance of unskilled jobs in the modernisation process (hypothesis 5). Knowing that in periods of economic boom, during which jobs are created, unemployment declines and the rate of returns increase, we expect that even lower-educated beginners might receive an additional premium in terms of occupational status during these periods. Conversely, in periods of economic recession and the related unfavourable labour-market conditions, only the higher-qualified beginners will be able to realise premium returns in the competition process (hypothesis 6).

Data, variables, design and statistical procedure

Data sources

The present empirical analyses are based on two longitudinal data sets. The first is the German Life History Study (GLHS), collected by the Max Planck Institute for Human Development and Education in Berlin (Mayer, 2008; 2009; 2015). This data set provides information on the educational trajectories and occupational careers of German women and men born in 1929–31, 1939–41, 1949–51, 1954–56, 1959–61, 1964 and 1971.3 For all of these birth cohorts, it is possible to analyse the returns to education at labour-market entry in the historical period between 1945 and 1999. In order to include the changes of the historical period after 1999, the present analysis is additionally based on the event-history data set ‘Working and Learning in a Changing World’ (ALWA: Arbeiten und Lernen im Wandel), from the Institute for Employment Research in Nuremberg (Kleinert et al, 2011).4 This second data set comprises information on 10,404 individuals born between 1956 and 1988. Their educational trajectories and occupational careers are observed until 2008. From the ALWA study, the life histories of German citizens from the birth cohorts 1959–61, 1964–66, 1969–71 and 1974–76 were selected and merged with life histories obtained from the GLHS. The merged data set offers information on labour market entry for 8,813 West Germans (4,310 females and 4,503 males). Foreigners and migrants are excluded from the database since life histories from these groups were not collected in the first GLHS. In the present analysis, only those occupational beginners who were older than 14 years at the time of entry into the labour market and who reported at least one significant employment episode lasting longer than six months (‘real’ job) were included.

Statistical analysis, dependent and independent variables

The dependent variable is the socio-economic status at entry into the first significant job (which is defined as lasting more than six months). Socio-economic status is measured in terms of the Magnitude Prestige Scale (MPS) developed by Wegener (1988).5 The MPS is based on the International Standard Classification of Occupations (ISCO) codes of jobs and is a well-known, as well as frequently applied, standard measure in sociology to describe the ‘quality of jobs’ in an occupational hierarchy (Goldthorpe and Hope, 1972). Compared to income or wages, MPS scores are a much broader measure of the ‘quality of jobs’ and their benefits as they not only capture material aspects of earnings quality, but also aspects of labour-market security (economic security related to the risks of job losses in certain occupations) and the quality of the working environment (non-material aspects of jobs, including the nature and content of the work performed, workplace relationships, job satisfaction, reputation, prestige or authority).

The key independent variable in the analysis is respondents’ educational attainment (Edu). Based on the characteristics of the German educational system such as the tracked secondary school system, the strong role of the dual vocational training system or the tertiary education integrating traditional universities and universities of applied sciences (Allmendinger, 1989), we use a rank order for the educational attainment level indicating broad differences in an individual’s productivity, educational signal or trainability. With regard to secondary school qualification, the level of schooling was categorised into four levels: (1) no school graduation, (2) lower secondary school graduation (Volks- resp. Hauptschulabschluss), (3) intermediate secondary school graduation (Realschulabschluss resp. Mittlere Reife) and (4) higher education entrance qualification (eligibility for university training [Abitur] or training at a university of applied sciences [Fachhochschulreife]). With regard to vocational training and tertiary education, the following four levels were distinguished: (1) no training graduation, (2) general vocational education or training (Lehre, Fachschule), (3) advanced vocational training (for example, master, technician) and (4) university degree (diploma, PhD). Our educational attainment variable multiplicatively combines the levels of general schooling with work-oriented training or tertiary education, following the logic of the CASMIN scheme (Braun and Müller, 1997). A higher attainment level (Edu) in our analysis therefore indicates school-leavers’ higher level of educational investment, longer enrolment in the educational system, their greater productivity level and their better trainability: Edu = 1: no school and no training graduation; Edu = 2: Lower secondary school degree without any training degree; Edu = 3: intermediate secondary school degree without any training degree; Edu = 4: lower secondary school degree and vocational education and training degree; Edu = 6: intermediate secondary school degree and vocational education and training degree or lower secondary school degree and advanced vocational training (for example, master, technician); Edu = 8: upper secondary school degree and vocational education and training degree; Edu = 9: intermediate secondary school degree and advanced vocational training; Edu = 12: upper secondary school degree and vocational education and training degree and advanced vocational training; Edu = 16: academic university or university of applied sciences degree or PhD certificate or postdoctoral qualification. In addition to the individuals’ efforts in educational investment (such as the number of school years), our scheme also emphasises differences in the skill level and signal value at the same tenure of enrolment in the educational system until the achievements of schooling and training.

In our analysis, we explicitly include indicators of the modernisation process and the cyclical labour-market conditions in order to predict the socio-economic levels of men and women at labour-market entry. These two orthogonal indicators are based on time series from official statistics and the application of factor analysis. The construction of these two indicators is described in detail in a previous study by Becker and Blossfeld (2017). The factors explain 92% of the variance in the ten different time series. The level of modernisation (see Figure 5) indicates historical changes – initiated by technological change and affecting labour market and occupational structures as well as economic business cycles (that is, volume of labour force; labour-force participation rate; share of employees in the primary, secondary and tertiary sectors; gross domestic product (GDP); GDP per capita). Changes in labour-market conditions (see Figure 5) are based on the number of firms, the (negative) unemployment rate and the ratio of notified vacancies and workforce. They are added with their minima in order to have positive factor scores only. On the structural level, after the linkage with the individual data, the factor scores of modernisation have a minimum of about zero and a maximum of 4.8 and the mean is 3 (standard deviation: 0.8). The factor scores of labour-market situation range from about zero to 5 (mean: 2.95; std. dev.: 1).

The descriptive statistics of these variables are documented in Table A1 (in the Appendix) separately for each gender. They already reflect some of the interesting developments, which will be analysed in detail later in this paper. Due to the strong expansion of employment in the service sector and the decline in the industrial sector in the process of modernisation, the increase of the average socio-economic scores for women is higher than for men across cohorts. This increase in socio-economic rewards seems to be closely interrelated with the rising human capital investments across birth cohorts, where young women have indeed surpassed young men in the course of educational expansion. The interaction of educational attainment with the modernisation level across birth cohorts confirms this presumption.

In our analysis, we apply standard ordinary least squares (OLS) regression analysis. All the analyses are performed separately for women and men.

Empirical results

In a previous study, Becker and Blossfeld (2017) found a steady increase in the average socio-economic MPS scores of men across birth cohorts. In the regression models in Table 1, their finding can now be compared to the changes in women’s socio-economic positions at entry into the labour market (see models 1 and 3). These estimates show that women’s average socio-economic MPS scores at labour-market entry have increased more across cohorts than men’s. Thus, both genders, but particularly women, have gained in terms of average socio-economic MPS scores at entry into the labour market across birth cohorts. This result supports hypothesis 2.1, that in the course of technological advancement and innovation, socio-economic MPS scores at entry into the labour market increased in West Germany across consecutive birth cohorts. Apparently, women who are predominantly employed in skill-demanding service and public sector jobs benefited more than men from this development at entry into the labour market. However, for both women and men, hypothesis 2.2 with regard to the effect of business cycles on the cohort-specific returns at labour-market entry is not confirmed.

Table 1:

MPS socio-economic scores at entry into the labour market (first significant job) by education and across birth cohorts

ModelMenWomen
1234
Human capital Education3.104 (0.074)***3.020 (0.078)***
Cohorts Ref.: 1929–31
1939–414.204 (2.064)*2.801 (1.750)5.190 (2.132)*3.912 (1.837)*
1949–5111.390 (2.082)***6.686 (1.769)***12.469 (2.108)***8.329 (1.819)***
1954–5611.199 (1.895)***4.324 (1.615)**16.251 (1.951)***9.041 (1.691)***
1959–6112.437 (1.732)***1.667 (1.491)17.910 (1.779)***6.574 (1.561)***
1964–6612.035 (1.706)***1.004 (1.470)21.386 (1.760)***8.239 (1.554)***
1969–7111.330 (1.753)***1.321 (1.505)23.509 (1.809)***9.438 (1.600)***
1974–7617.547 (2.779)***2.646 (2.383)29.488 (2.611)***10.998 (2.300)***
Intercept47.940 (1.520)***33.429 (1.334)***45.901 (1.596)***34.846 (1.404)***
Adjusted R20.01920.29530.06950.3095
N4,5034,5034,3104,310

Notes: * p < .05; ** p < .01; *** p < .001; β-coefficients estimated by OLS regression.

Sources: GLHS and ALWA – own calculations.

If educational attainment levels (combining general education with vocational training and university education) of the first-time employees are included in the linear regression model, the cohort pattern for male entrants largely disappears (model 2 in Table 1). Thus, men’s change in the returns to education developed in parallel with the process of educational expansion. The strong role of education in relation to men’s socio-economic scores at job entry is also reflected in the steep increase in the R2 from model 1 to model 2. For women, the increase in the explained variance from model 3 to model 4 is also pronounced. However, their cohort pattern remained significant across cohorts, even after women’s educational attainment is controlled (model 4). Thus, for young women’s socio-economic scores, the changing demand side of the labour market (that is, the tertiarisation of jobs and the increase in public sector employment) had an additional (positive) impact on their rates of return. Overall, these results support hypothesis 1, that higher educational investments result in higher returns to education at labour-market entry regardless of gender. It is worth noting that the age at labour-force entry has increased across the birth cohorts due to the increased enrolment in the educational system; however, the gender differences are not significant.6

In order to predict the socio-economic MPS scores at labour-market entry, in the next step, the two orthogonal indicators from the factor analysis, namely the modernisation process and the cyclical labour-market conditions, are explicitly included in the estimation (Table 2). For both women and men, there are strong positive effects of the level of education (see models 1 and 4) and after the control for the macro indicators (in models 2 and 5). This finding is again in line with the hypothesis 1 on the human capital effect. Formal education in terms of general schooling, VET (vocational education and training) and university education is essential for the status attainment of first jobs in West Germany. The size of returns to education is similar for women and men when only main effects are taken into account.

Table 2:

MPS socio-economic scores at entry into the labour market (first job) in West Germany by individual and structural characteristics, 1945–2008

ModelMenWomen
123.13.2456
Individual characteristics Education3.074 (0.071)***2.967 (0.077)***0.150 (0.422)3.160 (0.073)***2.825 (0.083)***1.436 (0.435)***
University degree−10.092 (6.746)
Low level of education−6.804 (3.430)*
Structural characteristics Modernisation level1.843 (0.442)***−3.451 (0.759)***1.688 (0.800)*4.474 (0.465)***3.552 (0.705)***
Labour-market conditions0.630 (0.378)2.273 (0.695)**1.429 (0.647)*0.051 (0.368)−0.788 (0.627)
Interaction: Education and Modernisation level0.945 (0.109)***12.292 (1.717)***0.243 (0.110)*
−0.303 (1.016)
Labour-market conditions−0.192 (0.094)*−3.709 (1.371)**0.177 (0.092)
−0.485 (0.847)
Intercept35.764 (0.622)***28.600 (1.433)***41.887 (2.468)***47.449 (2.956)***41.391 (0.609)***28.681 (1.450)***34.383 (2.262)***
R20.29100.29620.30780.26370.30120.31950.3212
N4,5034,5034,5034,5034,3104,3104,310

Notes: * p < .05; ** p < .01; *** p < .001; β-coefficients estimated by OLS regression.

Sources: GLHS and ALWA – own calculations.

When time-varying macro structures are taken into account, the returns to education are quite similar for women and men (models 2 and 5). However, the effects of the cyclical labour-market conditions on the rewards to first jobs are statistically significant neither for women nor for men. This means that hypothesis 4 regarding the positive effect of favourable labour-market conditions on status gains at labour-market entry is not confirmed – at least not at this point of our analysis. This is also true for hypothesis 2.2 concerning the negative effects of worsening labour-market conditions after the end of the economic miracle in the 1970s.

The significant and strong main effect of modernisation on the returns for both genders supports hypothesis 3. The higher the modernisation level at the time of entry into the first job, the higher the attained socio-economic scores for each generation have been. It is important to note that the effect of modernisation is much higher for women than for their male counterparts. The educational upgrading in the course of educational expansion favouring women resulted in larger returns of female human capital investments at labour-market entry due to the increasing supply of jobs requiring higher skills in the tertiary sector. Thus, in (West) Germany it would be misleading to assume that the positional structure at entry into the labour market remains stationary across birth cohorts. Instead, the process of modernisation resulted in an increasing availability of skilled and highly skilled positions at entry into the labour market. Therefore, in particular for female beginners among the younger birth cohorts, modernisation has significantly increased the socio-economic status benefits of each younger generation at labour-market entry. This finding underlines the results of earlier studies that particularly young people of consecutive birth cohorts have been important carriers of occupational restructuring. Based on their up-to-date qualifications, they have been able to enter into the newly established, more demanding, skilled and highly skilled jobs created by the process of occupational change. Again, it is noteworthy that these increases in socio-economic status benefits (that are closely connected with the modernisation process) have been higher for young women than for young men.

For men, the results are also in line with hypothesis 5, assuming that qualified and highly qualified beginners have benefited from the modernisation process in terms of returns to education (see model 3.1). Only for men, in line with hypothesis 6, it is found that periods of economic boom are in favour of less-qualified job-starters. However, in times of less-favourable labour-market conditions, only highly qualified beginners are more likely to profit from premium returns. Based on this result, the effect of human capital is re-estimated by considering grouped level of educational degrees (see model 3.2). When controlling human capital, modernisation and labour-market conditions as well as its interaction with the beginners’ education, beginners with a low level of education receive significantly lower rewards compared to beginners with an intermediate level of education or a university degree. Thus, the advancing modernisation and favourable labour-market conditions result in an increase in returns to education at entry into the labour market. These findings are in line with hypotheses 1, 3 and 4. Thus, compared to unqualified beginners, male university graduates, especially, benefited from the modernisation process. This is partially in line with hypothesis 4, indicating that unskilled beginners are penalised by the economic modernisation process. Unskilled jobs, mainly in the production sector, are continuously disappearing in the course of modernisation. In line with hypothesis 6, the results show that, compared to highly qualified graduates, less-qualified workers benefit in times of economic boom at labour-market entry. However, in times of less-favourable labour-market conditions, only better-qualified beginners are more likely to realise premium returns than less-qualified job-starters.

These regression results are clearly reflected in Figure 6, which depicts the changes in average socio-economic MPS scores for women and men between 1945 and 2008 based on regression models 3.1 and 6 in Table 2. It is clear that men’s and women’s average socio-economic status at entry into the labour market has increased steadily over time. After the mid-1970s, however, men’s average socio-economic status levels tended to fall behind the average socio-economic status level of women. Men’s average socio-economic scores became more cyclical. Thus, the negative effect of the business cycle affected men in the production sector more than women in the service jobs. This is particularly true for low-qualified men. Men who generally rely more on (manual and industrial) production jobs seemed to be more affected in their socio-economic development by the economic ups and downs of business cycles. In comparison, women did not experience any statistically significant effect of the changing labour-market conditions in their service and administrative jobs. Their job opportunities have been much more influenced by the expansion of highly skilled service employment in areas such as the educational system, the health sector or other kinds of welfare state jobs. In sum, women have not only benefited more from educational expansion than men, but they have also gained more from the modernisation of the economy in terms of increased socio-economic status in their first jobs.

The effect of occupational beginners’ average educational level on their socio-economic score at entrance into their first job across periods (predicted values: models 3.1 [men] and 6 [women] in Table 2). Almost linear increase of prestige score in the first job across periods estimated by taking the education and modernization into account.
Figure 6:

The effect of occupational beginners’ average educational level on their socio-economic score at entrance into their first job across periods (predicted values: models 3.1 [men] and 6 [women] in Table 2)

Citation: Longitudinal and Life Course Studies 13, 1; 10.1332/175795921X16197756998006

Figure 7 shows a plot of the estimated returns (MPS socio-economic scores) for each level of educational attainment across historical time. The calculation is based on models 3.1 and 6 in Table 2. While all women and highly qualified men have been able to benefit from the interplay of educational expansion and modernisation, low-skilled male labour-market entrants have been increasingly penalised by the modernisation process (see model 3.1 in Table 2 and Edu ≤ 3 in Figure 4). Concerning young people with intermediate educational degrees (6 ≤ Edu ≤ 9), there has been basically no change in the returns to education across cohorts (for similar results across cohorts, see also: Brzinsky-Fay and Solga, 2016).

Trend of returns to education (in terms of MPS socio-economic score) at entry into the first job across periods, 1949–2008 (predicted values of the full model: model 3.1 in Table 2 for men and model 6 in Table 2 for women). Trends of returns to education, estimated separately for educational degrees and genders. Polarization of the returns to education for men in favour of highly educated beginners. Increase of the women’s returns to education for each of the educational certificates. Increasing dispersion of the men’s returns across periods and smooth dispersion of returns for women.
Figure 7:

Trend of returns to education (in terms of MPS socio-economic score) at entry into the first job across periods, 1949–2008 (predicted values of the full model: model 3.1 in Table 2 for men and model 6 in Table 2 for women)

Citation: Longitudinal and Life Course Studies 13, 1; 10.1332/175795921X16197756998006

Notes: Edu = 1: no school and no training graduation; Edu = 2: Lower secondary school degree without any training degree; Edu = 3: intermediate secondary school degree without any training degree; Edu = 4: lower secondary school degree and vocational education and training degree; Edu = 6: intermediate secondary school degree and vocational education and training degree or lower secondary school degree and advanced vocational training (for example, master, technician); Edu = 8: upper secondary school degree and vocational education and training degree; Edu = 9: intermediate secondary school degree and advanced vocational training; Edu = 12: upper secondary school degree and vocational education and training degree and advanced vocational training; Edu = 16: academic university or university of applied sciences degree or PhD certificate or postdoctoral qualification.

In summary, it can be concluded that low-educated men have received increasingly less socio-economic rewards in their first jobs across cohorts and may therefore be called the ‘losers of modernisation’. The ‘winners of modernisation’ are in particular women and men with a university degree (Edu = 16 in Figure 7). They have benefited remarkably in their socio-economic scores at the first job due to the interaction of educational expansion and technological advance. This means that the value of tertiary education has not decreased, as many sociologists have assumed, but has actually increased across cohorts in West Germany. Of course, this process also has contributed to an increasing polarisation of inequality between young people with academic education and mainly young men with low general education or without any training at all.

Conclusions

It is often assumed that the returns to higher educational attainments decline across cohorts as the number of school leavers who attain the same or higher educational levels rises in the process of educational expansion. However, the value of educational certificates at entry into the labour market is determined by a complex matching process of people to jobs and has to be modelled accordingly. Starting from the seminal work by Goldin and Katz (2009) on the race between education and technology, the aim of this study was to analyse how educational expansion, economic modernisation and the business cycle have affected the long-term socio-economic status development of women and men entering the labour market in West Germany (Mayer, 2004).

In our empirical analysis, the entrance patterns of women and men from successive birth cohorts have been reconstructed at the individual level and linked with the most important structural changes in the economy on the macro level. Our cohort analysis shows that the impact of both the skill-biased technology and the educational expansion are different for the birth cohorts. The multilevel analysis provides an advanced understanding of the way in which such long-term macroeconomic trends of modernisation have influenced the start of career mobility and changing inequality of status attainment in West Germany across generations.

The presented empirical analysis demonstrated that there has been an impressive expansion of education in (West) Germany in the historical period from the end of the Second World War until today. It also showed that in the course of technological advancement and sectoral change there has been a strong increase in the number of jobs with higher socio-economic levels at entry into the labour market in West Germany. Thus, the positional structure at entry into the labour market has not been stationary but rather has expanded towards skilled and highly skilled jobs. Therefore, human capital investments have not become devaluated in the course of educational expansion due to the rising supply of more highly qualified first-time employees. In particular, women in younger birth cohorts have benefited from the interrelated societal changes in terms of educational expansion, technological change, sectoral tertiarisation and occupational upgrading. However, unskilled school leavers in general and unskilled men in particular have been increasingly penalised by the modernisation process. The returns to males who leave school without any educational certificate or further vocational training have worsened drastically in the observation period. Thus, the interplay of sustainable educational expansion with structural changes in the labour market has led neither to an educational inflation nor to a devaluation of higher education in terms of decreasing rates of return. There are also no indications of erosion for individuals attaining intermediate general and vocational education at labour-market entry.

The empirical analysis teaches us that investments in human capital are – more than ever before – one of the most important decisions in individuals’ life courses, in order to prepare them for employment and life in a rapidly changing modern society. Of course, the reported results are limited as entry into the labour market was studied only in West Germany and in a specific, but quite long, historical period. Also, immigrants and refugees were not included in the presented analysis, which means that the results are likely to underestimate the degree of socio-economic inequality at entry into the labour market.

Notes

1

There are other reasons to look at the process of labour-market entry: labour-market entry has a long-term effect on the entire career in the life course, that is, occupational inequalities are largely set at labour-market entry, and remain rather constant thereafter (Manzoni et al, 2014: 1305) and also the general trend in the skill structure is first experienced by young people. First-time employees start their career not only with fresh and up-to-date qualifications compared to established workers, but they are also the main carriers of occupational restructuring in the economy. It is well known that a substantial change in the occupational structure is brought about by generational change when young qualified people enter newly created jobs and when obsolete occupations simultaneously disappear as old people retire (Manzoni et al, 2014). The present empirical study therefore focuses on successive birth cohorts who enter into their first jobs. Hereby, it is essential to model early career outcomes at the school-to-work transition – one of the most important transitions in young women’s and men’s life courses – not only as a function of individuals’ efforts and resources but including structural opportunities and constraints (Sørensen, 1975).

2

Modernisation and labour-market conditions are two uncorrelated factors extracted by confirmatory factor analysis (Becker and Blossfeld, 2017: 120). The time series used come from the German social indicators monitor (SIMon) hosted by GESIS (2018). The data were completed and updated based on the new statistical yearbooks published by the Federal Office of Statistics.

3

These data sets are available at GESIS, at: https://dbk.gesis.org/dbksearch/gdesc2.asp?no=0033&db=e. Please take notice of their digital object identifiers (doi:10.4232/1.2645; doi:10.4232/1.2646; doi:10.4232/1.2647; doi:10.4232/1.2648; doi:10.4232/1.3927).

4

This data set is available at the Research Data Centre of the German Federal Employment Agency (BA) at the Institute for Employment Research (IAB): https://fdz.iab.de/en/FDZ_Individual_Data/ALWA.aspx. Meanwhile, this data has been integrated into the Starting Cohort 6 of the National Educational Panel Study (NEPS) located at the Leibniz Institute for Educational Trajectories.

5

For the GLHS cohorts born between 1929 and 1961 and for the younger cohorts in GLHS and the ALWA study, the code for ISCO (International Standard Classification of Occupations; three digits) has been harmonised and converted to the MPS-86-classification. In detail, for the GLHS cohorts born between 1929 and 1961, the jobs were coded using ISCO-68 (International Standard Classification of Occupations) transferred to the MPS-86 classification. For the younger cohorts in GLHS and ALWA, the jobs have been coded according to the occupational classification developed by the Federal Employment Agency. Therefore, it was necessary to convert this special code to ISCO-68 (three digits). Through this approach and the updating to new and recent occupations, it was possible to use the MPS for all jobs of all the birth cohorts.

6

In the course of the educational expansion, the timing of labour-market entry in terms of age changed across the birth cohorts. For men born around 1930 or 1940, the median age at labour-market entry after May 1945 was 18 years and increased continuously across consecutive cohorts to 19 years for men born around 1950 or 1955. The median age of first-time employees born around 1960 and 1965 was about 20 years while for the two youngest cohorts the age was about 21 years. For women, age-related labour-market entry is very similar to the men’s cohort pattern. For women born around 1930, the median age at labour-market entry after May 1945 was 18 years while for the cohort 1940 the median age was 17 years. For the younger cohorts, the age at labour-market entry increased stepwise to age 21.

Acknowledgement

For helpful comments on earlier drafts, we wish to thank the anonymous reviewers and the editor of LLCS. The manuscript is dedicated to the warm memory of Götz Rohwer (1947–2021), a great social scientist, an advocate of the life course research, and our colleague and friend.

Data availability statement

The authors take responsibility for the integrity of the data and the accuracy of the analysis. The data are available at the GESIS as well as at the Research Data Centre of the German Federal Employment Agency (BA) at the Institute for Employment Research (IAB). For details please see the notes 2, 3 and 4.

Conflict of interest

The authors declare that there is no conflict of interest.

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  • Sørensen, A.B. (1975) The structure of intragenerational mobility, American Sociological Review, 40(4): 45671.

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  • Stiglitz, J.E. (1975) The theory of ‘screening’, education, and the distribution of income, American Economic Review, 65(3): 283300.

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  • Thurow, L.C. (1975) Generating Inequality, New York: Basic Books.

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  • Warren, J.R., Sheridan, J.T. and Hauser, R.M. (1998) Choosing a measure of occupational standing: how useful are composite measures in analysis of gender inequality in occupational attainment?, Sociological Methods and Research, 27(1): 376. doi: 10.1177/0049124198027001001

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  • Wegener, B. (1988) Kritik des Prestiges, Opladen: Westdeutscher Verlag.

Appendix

Table A1:

Descriptive statistics

Structural characteristics (linked with individuals)
MeanStd. Dev.Min.Max.
Structural characteristics
Modernisation level3.330.840.244.78
Labour-market conditions2.950.960.285.32
Individual characteristics
Men (N = 4,503)Women (N = 4,310)
MeanStd. Dev.Min.Max.MeanStd. Dev.Min.Max.
Individual characteristics
MPS socio-economic scores58.5725.9320.0186.863.6925.2320.0186.8
Thereof: Cohort (Men/Women)
1929–31 (n = 286/233)47.9418.5520.0167.045.9020.9020.0167.0
1939–41 (n = 339/297)52.1420.3620.0186.751.0921.2320.0186.7
1949–51 (n = 326/313)59.3324.8420.0186.758.3621.8920.0154.5
1954–56 (n = 516/471)59.1424.4120.0186.862.1521.8420.0186.8
1959–61 (n = 956/959)60.3826.2520.0186.863.8123.8220.0186.8
1964–66 (n = 1,097/1,078)59.9728.2120.0186.867.2826.1920.0186.8
1969–71 (n = 864/820)59.2726.2720.0186.869.4025.0720.0186.8
1974–76 (n = 122/139)65.4828.5320.0163.375.3932.6120.0186.8
Education (general, vocational)7.424.551167.054.38116
Thereof: Cohort (Men/Women)
1929–31 (n = 286/233)4.673.231163.663.05116
1939–41 (n = 339/297)5.123.301164.083.31116
1949–51 (n = 326/313)6.194.181165.033.93116
1954–56 (n = 516/471)6.884.461166.044.38116
1959–61 (n = 956/959)8.144.841167.414.33116
1964–66 (n = 1,097/1,078)8.224.611168.014.05116
1969–71 (n = 864/820)7.894.252168.324.14216
1974–76 (n = 122/139)9.474.694169.784.77216
Structural characteristics
Modernisation level3.310.850.234.783.330.820.234.78
Labour-market conditions2.930.950.285.322.960.960.285.32
Interaction: Education and Modernisation level25.9118.560.2374.0724.9817.890.2376.53
Thereof: Cohort (Men/Women)
1929–31 (n = 286/233)4.396.710.2343.973.515.900.2352.52
1939–41 (n = 339/297)12.3310.331.1054.899.7410.391.3954.89
1949–51 (n = 326/313)19.9314.362.7456.7215.9913.372.7456.72
1954–56 (n = 516/471)22.9614.973.1558.2920.3614.953.2860.85
1959–61 (n = 956/959)28.1417.223.2369.5225.4415.263.1574.07
1964–66 (n = 1,097/1,078)29.7318.913.3273.3428.5816.323.3171.71
1969–71 (n = 864/820)32.8618.297.2874.0734.4417.847.2974.07
1974–76 (n = 122/139)41.2521.2416.2174.0742.6721.668.4576.53
Labour-market conditions21.5314.210.2885.1420.4013.220.2885.14
Thereof: Cohort (Men/Women)
1929–31 (n = 286/233)6.3310.370.2868.225.049.040.2883.00
1939–41 (n = 339/297)19.2816.221.5485.1415.2916.572.0485.14
1949–51 (n = 326/313)26.9516.053.9885.1422.5116.023.9985.14
1954–56 (n = 516/471)23.8513.073.3175.4322.0413.282.3275.43
1959–61 (n = 956/959)23.0312.963.1757.0321.1610.953.2257.03
1964–66 (n = 1,097/1,078)20.1514.172.4257.0319.1611.962.0657.03
1969–71 (n = 864/820)23.4912.144.6457.0324.4911.484.6557.03
1974–76 (n = 122/139)25.7813.139.5749.5727.1313.635.1149.53

Sources: GLHS and ALWA – own calculations.

  • View in gallery

    Educational expansion: eligibility for education at traditional university (Abitur) or at university of applied sciences (Fachhochschulreife) in West Germany, 1950–2005

  • View in gallery

    Educational expansion: freshmen in universities (percentages, 19–23) in Western Germany (1952–1993) and in unified Germany (1994–2008) as well as absolute numbers of students (in 100,000)

  • View in gallery

    Educational expansion: women and men without any school graduation or without vocational education or training in West Germany, 1971–2005

  • View in gallery

    Trend of female and male employment in West Germany (1945–2010)*

  • View in gallery

    Trend of modernisation and changing labour-market conditions in West Germany (1945–2010)*

  • View in gallery

    The effect of occupational beginners’ average educational level on their socio-economic score at entrance into their first job across periods (predicted values: models 3.1 [men] and 6 [women] in Table 2)

  • View in gallery

    Trend of returns to education (in terms of MPS socio-economic score) at entry into the first job across periods, 1949–2008 (predicted values of the full model: model 3.1 in Table 2 for men and model 6 in Table 2 for women)

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    • Export Citation
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    • Export Citation
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  • 1 University of Bern, , Switzerland
  • | 2 Otto Friedrich University Bamberg, , Germany

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