Advances in Life Course Research 18 (2013) 185–198

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Immigrants’ initial steps in Germany and their later economic success Irena Kogan *, Markus Weißmann University of Mannheim, Germany

A R T I C L E I N F O

A B S T R A C T

Article history: Received 31 May 2012 Received in revised form 20 February 2013 Accepted 22 April 2013

In line with the emerging research that acknowledges the importance of the process character of immigrants’ labour market integration, this paper examines the existence of path dependencies of early employment trajectories on later labour market outcomes. Theoretically we are interested in establishing whether career trajectories provide a distinct signal, used by both employers and employees: a signal that operates apart and beyond the accumulation of host-country relevant resources, especially, host-country labour market experience or training. The analyses are performed with the help of a unique dataset comprised of recent immigrants from the former Soviet Union in Germany. Sequence analysis techniques and multivariate regressions are applied. Results show that starting in higher-status employment leaves a distinguishable imprint on immigrants’ later occupational standings, even after the returns to the skills associated with early trajectories are taken into account. At the same time, initial career trajectories do not have any direct effect on wages, apart from the pay-off to relevant skills acquired while pursuing these careers. The findings are discussed in concurrence with the human capital and signalling theories. ß 2013 Elsevier Ltd. All rights reserved.

Keywords: Migrants’ labour market integration Sequence analysis Germany

1. Introduction Labour market incorporation is a crucial step towards immigrants’ inclusion into their receiving society. Whether immigrants quickly integrate into the host country’s labour market has long-lasting consequences for their successful inclusion in other societal areas. The dominant pattern of immigrants’ economic integration is that immigrants arriving in a new country face some initial difficulties: they often endure unemployment, experience occupational downgrading, and earn lower wages as compared to natives with similar measured characteristics (Borjas, 1994; Chiswick, 1978; Friedberg, 2000; Kalter & Granato, 2007; Kogan, Kalter, Liebau, & Cohen, 2011). With the passing of time in

* Corresponding author at: School of Social Sciences, University of Mannheim, A5, A 529, 68131 Mannheim, Germany. Tel.: +49 621 181 2015; fax: +49 621 181 2016. E-mail address: [email protected] (I. Kogan). 1040-2608/$ – see front matter ß 2013 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.alcr.2013.04.002

the host country, immigrants are expected to catch up with natives, as they learn the host country language, gain knowledge about the functioning of the host country labour market, acquire local education and training, and become integrated into local networks (Chiswick, 1978, 1991). As a result, they are expected to overcome initial disadvantages and eventually improve their labour market positions. The process of gradual straight-line upward economic assimilation is not uniform. For example, some immigrants are more successful from the onset, entering steady employment upon arrival and continuing in it for many years. Others face more serious initial labour market obstacles, e.g., switching jobs, being stuck in lower-level occupations, moving in and out of the labour market, or remaining non-employed for longer periods of time. In all these cases, as researchers, we are advised to take a notice of the process character of immigrant integration. Single outcomes, which we often observe in cross-sectional data, may have little reflection of the preceding trajectories.

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Alternatively they could be the result of a cumulative process and occur exactly because of the earlier undertaken pathways. Following the spirit of still marginal, but a slowly growing body of research on immigrant integration that takes into account its process character (Fuller, 2011; Fuller & Martin, 2012; Kogan, 2004b, 2007), this paper aims at broadening our understanding of immigrant inclusion, by investigating the trajectories and the dynamics of this process. The main focus is thereby on the existence of path dependencies and cumulative effects of early employment trajectories on later labour market outcomes. Our first major contribution is to reveal the mechanisms through which early careers might be consequential for later labour market outcomes; be it immigrants’ acquisition of host-country-specific resources or their early careers serving as signals upon which both immigrants and employers can later rely. Hence our key research questions are: Are the effects of early career trajectories solely associated with immigrants’ accumulation of host-country relevant resources, above all, hostcountry job experience and training? Or do early trajectories leave their distinguishable imprints on immigrants’ later labour market outcomes, irrespective of the extent of their early experience and resource accumulation? Our second important contribution is examining the dynamics of the integration amongst new immigrants from the former Soviet Union (FSU) in Germany immediately after their arrival, as well as their occupational mobility patterns. Permanent settlement intentions of ethnic German Diaspora returnees and Jewish immigrants from the FSU make them particularly suitable for our objectives. We rely on the recently collected dataset of the labour market integration of FSU immigrants, rich with information on these immigrants’ pre-migration employment biographies and their initial years in Germany. The data allows us, unlike in many of the previous studies, to determine the timing of the first job and the formal education or training in Germany. This enables us to analyse their cumulative effects on the outcomes of immigrants’ subsequent employment. By means of a sequence analysis technique and multivariate regressions, we are able to, first, identify various employment trajectories amongst FSU immigrants to Germany immediately after arrival, and second, explore the effects of these trajectories on their later labour market outcomes. We begin this paper by presenting the German setting as it relates to the migration from the former Soviet Union in recent decades and the context of immigrant reception. The following two sections establish specific objectives of the research, focusing on the dynamics of immigrant incorporation and presenting the main theoretical arguments concerning the consequences of initial employment paths on later job outcomes. The methodology section addresses the advantages of our analytic approach for the research questions at hand. Our main results are further presented and summarized. 2. The German setting For years, academic and political attention in Germany has been devoted to the integration difficulties faced by

immigrants who arrived throughout the 1950s and the 1970s within the framework of so-called ‘guest-worker’ recruitment programs. This attention has also focused on their offspring: second- and third-generation of immigrants from the Mediterranean countries and ex-Yugoslavia (Kalter & Granato, 2007). In the meantime, a large proportion of direct migration into Germany, in the last two decades, has come from Eastern European countries (Kogan, 2011a). Countries of the former Soviet Union play a special role in this regard (Dietz, 2000). The early 1990s mark the beginning of a mass exodus of FSU citizens possessing German roots (so called ethnic German immigrants or Aussiedler) into Germany. Since then, about two million ethnic Germans from the FSU have settled on a permanent basis in Germany (Mu¨nz, 2002). Furthermore, since 1991, Germany has had a permanent settlement programme for Jewish immigrants from the former Soviet Union, granting them a ‘Quota Refugee Status’ (Cohen & Kogan, 2005, 2007). More than 200,000 Jews and their family members have re-settled in Germany, fostering Germany’s Jewish life. A relevant feature of the migration from the FSU is that both Aussiedler and Jewish immigrants are neither purely economic, nor solely humanitarian migrants. Being a mixture of both, they arrive in the framework of special permanent settlement programs and are entitled to generous welfare support and extensive integration measures. Despite the newcomers’ clearly privileged status, FSU immigration represents a challenge for Germany’s integration efforts. In contrast to the previous immigrant waves, FSU immigrants possess relatively high levels of education and occupational qualifications, yet they still fail to integrate fully into the German labour market (Kogan, 2011a). Apparently, their problem is not the lack of educational qualifications, normally attested to the guest worker migrants in Germany, but rather a lack of transferability of these qualifications in a new setting (Kogan, 2012), as well as a lack of relevant cultural and social resources necessary to succeed (Kogan et al., 2011). With regard to labour market attainment, available research has time and time again shown that FSU Jewish and ethnic German immigrants pursue diverse investment strategies in Germany (Cohen & Kogan, 2007; Haberfeld, Cohen, Kalter, & Kogan, 2011; Kogan, 2012; Kogan et al., 2011; Liebau, 2011). Whereas ethnic Germans strive for immediate labour market returns in terms of quick employment, largely irrespective of its status, Jewish immigrants pursue a more long-term investment approach. They search for employment longer and more selectively and in the end they enter higher-status occupations. The side effects of these higher-aiming ambitions amongst Jewish immigrants are longer periods and higher rates of joblessness. 3. Why a trajectory-oriented approach? The sociological research on immigrants’ labour market integration in Germany has produced a number of influential studies relying on cross-sectional data and applying a static view of immigrants’ labour market incorporation (Kalter & Granato, 2002, 2007). As of recent the focus has shifted to a more dynamic approach, which seeks to examine the roots of immigrants’ higher

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unemployment incidence either in terms of their lower hiring propensities or their higher firing risks or both, practically analysing transitions from and to unemployment (see Kogan, 2004a; Uhlendorff & Zimmermann, 2006). The rediscovery of a dynamic approach in migration sociology led to a special issue in the International Journal of Comparative Sociology in the year 2011 with a collection of papers dealing with path dependencies in employment transitions in a number of European countries (Fullin, 2011 for Italy; Kogan, 2011b for Germany; Demireva & Kesler, 2011 for the UK; Corluy, Marx, & Verbist, 2011 for Belgium; Lagana`, 2011 for Switzerland). The analyses show that across all analysed countries, most immigrants have higher unemployment rates than their comparable natives. However, immigrants tend to experience more frequent labour market transitions. Particularly recent newcomers can be found in less permanent labour market statuses, experiencing more frequent shifts both from employment to unemployment, and the other way around (Reyneri & Fullin, 2011). Most of the studies that introduce dynamic aspects into immigrants’ integration ultimately focus on single transitions (e.g., from unemployment to employment) or a set of possible destinations within a transition (e.g., from unemployment to lower- or higher-status employment). However, they tend to ignore transition sequences, such as unemployment–training–employment (Wingens, de Valk, Windzio, & Aybek, 2011). This is unfortunate, if we recognize that labour market incorporation is unfolding over a variety of transitory states, and that the sum and the order of transitions might carry significance above and beyond single status transitions. Fuller (2011, p. 19) suggests that ‘‘particular transitions may represent critical events for immigrants, but the accumulation of a number of events and experiences over time creates overall patterns of work histories that likely matter more’’. Fuller’s two recent studies (Fuller, 2011; Fuller & Martin, 2012) and Kogan’s (2004b, 2007) earlier work, are examples of the approach that will be adopted in this study. Both groups of scholars address immigrants’ employment careers holistically, examining a number of labour market states and the order of these states. Kogan’s work focuses on immigrants’ employment pathways over a 6-year period of their lives, attending not only to the potentially multiple activities immigrants are engaged in, but also paying attention to the timing, order, and duration of these various events. Exemplary parts of immigrants’ employment careers are compared to those of their nativeborn counterparts in order to establish the degree of similarity between them. The ultimate goal is an assessment of the extent of labour market assimilation across various ethno-national groups in Germany (Kogan, 2007), and in comparison to the situation in Great Britain (Kogan, 2004b). Being able to pursue comparisons with the charter populations of both countries, Kogan, not least due to the data limitations, is unable to localize immigrants’ trajectories on a meaningful (for them) time-line; as it would be if such trajectories were observed for immigrants immediately upon their arrival in a new country. Fuller and Martin (2012) use a similar methodological approach – a sequence analysis – to uncover the monthby-month progress of immigrants through a variety of

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different labour market statuses, starting from the moment they arrive in Canada and following them for four subsequent years. They present a detailed account of the various employment trajectories that men and women pursue upon arrival in Canada, and explore the determinants of immigrants’ allocation in each particular labour market path. In Fuller’s (2011) working paper, employment sequences are no longer treated as outcome variables. Instead the focus shifts onto whether and how particular pathways that immigrants follow shape their later labour market positions. This working paper tests a number of plausible hypotheses on why individuals who manage to have a good employment career start in a new country are also more likely to be better-off economically in the longer run. This is done by implicitly relying on theories of job matching, productivity skill, and stigmatization arguments. Arguing that pathways represent a part of the mechanism through which initial circumstances create cumulative patterns of later advantages or disadvantages, the author stops short of revealing how this mechanism is likely to operate. This is where the current study sees its main objectives. 4. Theoretical framework and predictions Immigrant employment in the host country is not only associated with monetary and non-pecuniary rewards, it also implies an acquisition of host-country-specific human capital in terms of work experience. That post-migration human capital is favourable for immigrants’ labour market success requires no particular elaboration. From the human capital perspective, host-country specific human capital should increase immigrants’ productivity, making newcomers more attractive for their prospective employers (Becker, 1964). From the signalling perspective, hostcountry work experience would signal immigrants’ perseverance and employability to prospective employers (Spence, 1973; Stiglitz, 1975). Amongst those targeting highly paid and prestigious jobs, experience acquired within higher-status initial employment should be particularly valuable. Favourable working experience in the receiving country not only increases the stock of immigrants’ human capital, it also affects immigrants’ social capital. Bettersituated native-born colleagues can play a broker role in the attainment of costly information on job opportunities and provide valuable references. Altogether, this increases immigrants’ employability, particularly their chances for better-quality employment (Portes, 1995; Sanders & Nee, 1996; Sanders, Nee, & Sernau, 2002; Waldinger, 1994, 1995). Available research delivers support for the positive effect of host-country labour market experience in various societal contexts (Aydemir & Skuterud, 2005; Chiswick & Miller, 2009; De Vroome & van Tubergen, 2010; Kogan, 2004a; Lewin-Epstein, Semyonov, Kogan, & Wanner, 2003). Acquisition of host-country education and training should also provide productivity advantages within a new setting, as well as send out signals of immigrants’ trainability; which is likely to reduce employers’ uncertainty during the recruitment process. Both lines of argumentation, stemming from human capital and signalling theories, lead to the prediction of positive returns to

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host-country education and training. Empirical evidence for the positive effect of training on labour market outcomes amongst immigrants is manifold (Cohen & Eckstein, 2002; Constant & Massey, 2003, 2005; Kanas & van Tubergen, 2009; Seibert, 2005); even though only a few studies explicitly take into account individuals’ selection into training when estimating labour market effects of such training activities. Based on all these theoretical accounts, we would expect that initial employment careers, dominated by higherstatus employment and investments in German education and training, should translate into more favourable employment outcomes later on. Conversely, trajectories characterized by prevalent non-employment, should negatively affect subsequent job outcomes. During periods of joblessness, immigrants will not be in a position to gain German-source human capital, either in terms of work experience or education; nor will they acquire transferable and updated skills or helpful contacts. On top of that, long periods of non-employment may stigmatize immigrants as less employable or less attached to the labour market in the eyes of potential employers (Fuller, 2011). In an attempt to more precisely understand the mechanisms behind the hypothetically positive effects of early careers dominated by higher-status employment and training on later labour market outcomes, we pursue two leads. First, whether accounting for the sum of all elements in immigrants’ employment careers fully explains the anticipated variance in returns to specific employment trajectories. Second is related to the residual effects of career sequences after having accounted for their constituting elements. We argue that if (duration of) skill and resource accumulation vs. eventual skill loss is an underlying mechanism, then the effects of the career trajectories are to be fully accounted for by the sum of the underlying career elements, delivering support for the human capital and resource accumulation argument. If we find a residual effect of initial job trajectories for the later labour market outcomes, then there is more to the early careers than just sheer skill and resource accumulation. In line with the signalling approach, such persistent effects of the early curriculum vitae for the later careers can be traced back to a number of not necessarily mutually exclusive processes. On the one hand, immigrants’ favourable early career choices might set high standards for them, which they try to match in their later occupational decisions. Lack of economic success immediately after immigration might, on the contrary, lower subsequent occupational aspirations or produce other path dependencies. On the other hand, such effects may also mean that employers tend to read positive, as well as negative signals conveyed by immigrants’ early employment histories and reward them accordingly. Which of the two mechanisms – signalling or resource accumulation – is at work, will be established in the paper’s empirical sections. 5. Data and research methodology We use German data from ‘‘Labour Market Integration: Aussiedler and Jewish Immigrants from the former Soviet Union in Germany and Israel,’’ a project funded by the

German-Israeli Foundation between 2005 and 2009. The data was collected by means of a telephone survey in Germany, in May and June 2007. The target population were immigrants from the former Soviet Union, between the ages of 25 and 54, who arrived in Germany at the age of 18 or older, and between the years of 1994–2005. A Germany-wide telephone number register provided a sample frame, whereas the names of the potential respondents were pre-selected based on the onomastic procedure (Humpert & Schneiderheinze, 2000).1 After the list of potential immigrants from the former Soviet Union was created, the sample was screened to establish whether the selected individuals indeed belonged to the target population (for more details on the sampling procedure and methodological issues of the telephone survey, see Liebau, 2011). All respondents were provided with the option of being interviewed by a native Russianlanguage speaker, which was preferred by the vast majority of the interviewed. For the aims of our analyses to examine the effects of immigrant’s early careers in Germany for their later labour market outcomes, we restrict our sample to those individuals who experienced job mobility in Germany (total of 488 individuals), i.e., changed employment – including full-time, part-time, or marginal employment – at least once while in the host country. As this group is likely to be selective with regard to a number of characteristics, in the first part of our analysis, with the help of probit regression models, we assess the degree of this group’s selectivity in comparison to those immigrants who have never changed their employment status in Germany, being either continuously employed (in the very same job) or never being employed since their arrival until the moment of interview.2 For the aims of the analyses we had to exclude all cases that either had incomplete information on the date or status of episodes or reported implausible dates (e.g., when the reported start date of an episode lies after the reported end date).3 In a small number of cases, there was no

1 This procedure calculates the probability that a certain combination of first and last names pertains to a specific ethnic background, based on the computerized dictionaries of names and pertinent regional codes. 2 Our original sample contains 1610 individuals. Altogether 952 cases were not subjected to the sequence and subsequent regression analyses since respective individuals had never experienced any job episode in Germany until the moment of interview (total of 168 individuals or about 10% of the initial sample), were still employed in their first job at the moment of the interview (total of 585 people or about 36% of the initial sample) or, on the contrary, were not employed at the moment of the interview (total of 199 people or about 12 % of the initial sample), i.e., they had no valid information of ISEI or wages. 3 First, we excluded all observations that had missing information on the dates of one or more episodes reported (N = 89) as well as missing information on the date of arrival (N = 3). Furthermore, we excluded all cases that reported implausible dates. This includes start dates that lay before end dates of episodes or start dates that are equal to end dates (N = 20). We also excluded cases that started their first episode in Germany more than six month earlier to their arrival (N = 20) or that reported episodes in Germany that lay entirely before their date of arrival (N = 4). Finally, we excluded all cases that had missing information on occupation of their first employment (N = 34). In sum, 170 cases (around 10 percent of the initial sample) have been excluded from our analyses due to missing or implausible information.

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information on the start or end months of an episode, whereas information on the year was present. In such cases we imputed the month of an episode based on the information for the month of a preceding or subsequent episode or, for the first episodes after immigration, the month of arrival. When no information of the adjacent episodes was available, we set the month of an episode to June. For identifying the patterns of immigrants’ initial labour market careers we utilized a sequence analysis as a useful tool in describing life course data (Aisebrey & Fasang, 2010; Barban & Billari, 2012; Bru¨derl & Scherer, 2004; Brzinsky-Fay & Kohler, 2010; Scherer & Bru¨derl, 2010).4 The sequence analysis is usually carried out in two steps. In our study, the first step is conducted by means of a specific technique, an optimal matching analysis (OMA). Its aim is to assess the dissimilarity between each pair of sequences in the data. Sequences are comprised of an array of categorical statuses for each person. The following statuses are differentiated in the initial years of immigrants’ residence in Germany: non-employment (which encompasses any type of activity unrelated to employment or education/training, including language courses, integration courses or an orientation period in Germany), first ever employment in Germany, distinguishing between higher status PTM (professional, technical and managerial)5-jobs and non-PTM jobs, as well as vocational education and training, or training conducted during employment, including on-the-job training. Due to the fact that our data is of a retrospective character, only encompassing information about the first and current employment spell along with training activities, we do not have any information about the whereabouts of the respondents between those two jobs. Furthermore, we recode the gap if the first job was followed by education/ training or education/training was followed by the first job, with some interruption in between. Having a full employment calendar from the first day after migration to the moment of the interview would certainly be an advantage. However, due to the focus of the current study being on the very first steps in the country (i.e., first job and education/training) amongst rather recent immigrants (with a maximal stay of 11 years in Germany), this unfortunate omission should not have severely negative consequences. In fact, we try to account for the missing parts of the sequences by including variables which capture the length of stay in Germany and tenure in the current job. In this regard, it can be reported that the average duration of an unobserved period between the end of the first employment or training spell and the start of the current job is 21.7 months, whereas the median is only 12 months. Overall it should be noted that the current data structure does not enable a full and complete utilization of all favourable features of the sequence

4 The sequence analysis has recently been implemented into the common-use statistical packages, e.g., R (TraMineR package) or Stata (Brzinsky-Fay et al., 2006; Halpin, 2010). 5 Professional, technical, and managerial occupations encompass all occupations found under ISCO-1-digit codes: 1, 2, and 3.

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analysis technique, but is entirely suitable for the identification and categorization of early career paths (Barban & Billari, 2012). With the help of OMA, we calculate an interval-level measure of dissimilarity between sequences. This is done by counting a minimum number of transformations needed to make both sequences equal and weighing them with costs. In our case, the cost of substitutions for all statuses is set to 2, whereas insertions/deletions6 are weighed by 1 (MacIndoe & Abbott, 2004). We also experimented with alternative cost weights, but our results remained quite robust irrespective of the applied weighting scheme. Because of unequal sequence lengths, we standardized the dissimilarity measure in relation to the longest sequence in the data (Brzinsky-Fay, Kohler, & Luniak, 2006, p. 450). In the second step, the hierarchical cluster analysis by means of Ward’s algorithm is performed on the matrix of distances resultant from OMA with the aim of discovering patterns of job entry. After identifying clusters of job entry, we, first, descriptively explore whether individuals who are found in various clusters, differ in regard to their pre-migration characteristics. This is done in order to assess the degree of selectivity of various clusters, which is likely to be a part of the explanation for varying returns to early career paths (clusters). In the second step of the analysis, we investigate whether cluster membership exerts any unique effect on later career outcomes once pre-migration and current-situation related characteristics are taken into account. In the crucial model of this analysis, we include variables which summarize the elements of the underlying sequences in order to establish whether there is a residual effect for the early career sequences above and beyond a sheer sum of one’s career constitute parts. The outcomes we focus on are observed in the year 2007 and pertain to the current job of the respondents. Two dependent variables are scrutinized: (1) occupational status (measured against the International Socio-Economic Index, ISEI) and (2) log gross monthly wages. Upon measuring immigrants’ labour market outcomes on two different dimensions, we can obtain insights into the potential trade-offs or the cumulative risks faced by newcomers to Germany. An extensive set of independent variables is considered. These include immigrants’ pre-migration characteristics: level of education acquired in the FSU, the recognition of this education in Germany, information on employment in the FSU, and ISEI-status of employment back in the sending country. We also include the level of proficiency in the German language (a proxy for cultural resources) and the information on whether respondents knew someone in Germany prior to migration (a proxy for social resources). In addition, we control for legal status upon migration, differentiating between those who arrived with the status of Aussiedler (or their family members) or Jewish Quota Refugees. We further take gender, marital status upon migration, and age at migration into account.

6 Substitution, insertion and deletion are three types of transformations possible in OMA.

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Table 1 Probit regression coefficients predicting employment status in year 2007 amongst FSU immigrants in Germany. Never employed vs. employed at least once Characteristics of stay Years since migration ISEI of first job in Germany Pre-migration characteristics FSU education (low-sec. – ref.) General secondary Vocational secondary Post-secondary Tertiary Recognition of FSU education ISEI of FSU job Not employed in FSU prior to migration No friends in Germany before migration German language at least ‘OK’ Socio-demographic characteristics Jewish migrants Female Married at time of immigration Marital status missing Age at migration (18–30 – ref.) 31–40 41–50 Personality traits Conscientiousness Openness Extraversion Agreeableness Neuroticism Constant

0.19***

Still employed in the first job vs. changed jobs

(0.02)

0.07*** 0.02***

(0.01) (0.00)

0.37 0.42 0.37 0.39 0.06 0.00 0.01 0.15 0.20

(0.31) (0.29) (0.28) (0.30) (0.12) (0.00) (0.29) (0.12) (0.19)

0.17 0.10 0.09 0.16 0.18+ 0.01* 0.57* 0.05 0.31*

(0.20) (0.18) (0.17) (0.20) (0.10) (0.00) (0.23) (0.10) (0.14)

0.47*** 0.54*** 0.24+ 0.33+

(0.13) (0.12) (0.13) (0.18)

0.11 0.52*** 0.03 0.12

(0.11) (0.10) (0.11) (0.20)

0.26* 0.16

(0.13) (0.15)

0.13 0.13

(0.10) (0.13)

0.01 0.01 0.04* 0.01 0.02 0.57+

(0.02) (0.01) (0.02) (0.02) (0.02) (0.33)

0.02 0.01 0.01 0.01 0.01 0.11

(0.02) (0.01) (0.01) (0.02) (0.01) (0.25)

Observations Pseudo R2 Chi2

1285 0.210 189.76 (21)

956 0.085 112.42 (22)

Note: Standard errors in parentheses. + p < 0.1. * p < 0.05. ** p < 0.01. *** p < 0.001.

To get some leverage on immigrants’ unobserved characteristics and thus to better account for possible variation in selectivity patterns of both groups of FSU immigrants, we control for immigrants’ personality traits measured by the so-called ‘Big Five’ (Dehne & Schupp, 2007; Lang & Lu¨dtke, 2005). This captures items pertaining to openness, conscientiousness, extraversion, agreeableness, and neuroticism. By including these measures we try to get rid of possible biases associated with psychological factors that are potentially relevant for immigrants’ labour market integration, yet, are usually ignored in migration research. In order to proxy the extent of immigrants’ progress in the receiving society, for which we lack any detailed account due to the omission of information between the first steps in the country and immigrants’ status upon the interview, we control for years since migration (YSM). In addition, in order to account for specific characteristics of the current job, we capture its tenure. In wage equations we also take weekly working hours into account. Finally, to describe career sequences we calculate the length in each career status (in years) and include this information in the

final model of our multivariate analysis. Further details on all variables applied in the study can be found in Table A.1 in appendix. 6. Findings 6.1. Are occupationally mobile immigrants a select group? To properly test our theoretical expectations about the effects of early career steps on later labour market outcomes, we are constrained to limit our sample to the individuals who experienced some sort of career mobility in Germany, that is, changed an employer at least once.7 Since this may make them a select group, the aim of this

7 Compared to those who have been employed in one single job since arrival, among the occupationally mobile, the effects of early careers are exogenous for their later career outcomes. Compared to those who never worked in Germany, occupationally mobile immigrants can report the occupational status and wages of their current job.

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section is to assess the degree of selectivity of the analysed immigrant group (see Table 1). In the first column of Table 1 we juxtapose those who have never been employed in Germany and those who have had at least one job (including our interest group, i.e., immigrants with at least one job change). Our results show that gaining employment is largely a function of time since migration. Recent arrivals are less likely to be employed; whereby a longer duration in the host country increases the probability of entering employment. Pre-migration characteristics are not systematically related to the probability of employment. Neither human capital, nor cultural or social resources prior to migration seem to differentiate between those who never had a job and those who have been employed at least once. However, it is noticeable that Jewish immigrants, as compared to Aussiedler, are more likely to stay jobless, other things being equal. This largely corresponds to the results of earlier studies which compare these two groups of FSU immigrants. Whereas women are more likely to stay out of work, there is an indication that individuals who arrived with their families are more likely to seek employment (this effect is significant at the 10% level). Individuals who arrived in Germany at age 31–40 are more likely to enter gainful employment than the rest. Finally, extraverted persons seem to be more likely to report non-employment than the rest. That those who changed jobs are a select group is visible from the second column of Table 1. The negative effect of YSM suggests that recent arrivals are more likely to be observed in their very first employment at the moment of interview. This is not surprising seeing as the longer immigrants reside in Germany, the more likely they are to have changed jobs. The higher the status of their first job,

0

the least likely immigrants are to leave it. Those who had a higher status job back in the FSU, along with those who had not yet been employed at all, are, on the other hand, more likely to change jobs in Germany. FSU immigrants, who managed to get their education officially recognized in Germany, also seem to be more prone to occupational mobility; this effect is only significant at the 10% level though. Individuals with better knowledge of the German language upon migration are less likely to be occupationally mobile, possibly due to their better job matches from the very beginning. Women are more likely to stick to their first employment. 6.2. Descriptive evidence on early careers of occupationally mobile immigrants For the visualisation of employment career sequences we apply sequence index plots (Brzinsky-Fay et al., 2006; Kohler & Brzinsky-Fay, 2005). In such plots, the career sequence of each individual is presented. The career sequences are sorted by cluster membership, a result of the hierarchical cluster analysis of the distance matrix calculated pairwise. Relying on the Duda Hart criterion, ten, eight, and six cluster solutions were identified as acceptable; according to the Calinski-Habarasz test, 10 and 6 clusters seemed to be preferred. We decided to stick to a six-cluster solution, as it yielded the most meaningful results from the substantive point of view (see Fig. 1). Cluster 1 is marked by individual’s engagement in education or training in Germany; either alone or in combination with employment activities. There is large variation in this cluster in regard to the timing of entry into education and training activities. Whereas some people

Non-employment 1

First job (PTM) First job (non-PTM) School/vocational training in Germany

100

2

First job - school/training Gap

200

Description of clusters (from top to bottom): 1) Starting careers with education/training

3

2) Quick entry to a short spell of non-PTM 300

employment 3) Slow entry to a short spell of predominantly non-

4

PTM employment 400

5

4) Starting with PTM job 5) Quick entry to a long spell of non-PTM

6

employment 6) Quick entry to a shorter spell of non-PTM

500 0

50

100

150

191

employment

Fig. 1. A six-cluster solution of the patterns of employment entry observed amongst FSU immigrants in Germany.

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started with training immediately after arrival, others stayed non-employed for quite a long time before starting training. The duration of training also differs. It remains to be seen whether starting employment careers in this cluster is associated with more favourable labour market outcomes, as theoretically expected. The second and third clusters represent immigrants’ transition from non-employment to a short spell of a non-PTM job. Whereas cluster 2 documents an immediate or rather quick entry into a short spell of non-PTM employment, in cluster 3 we observe individuals with a more prolonged period of non-employment prior to entering a non-PTM job. Clusters 5 and 6 are also marked by the transition into a first non-PTM job. Unlike in both previously discussed clusters, here we observe a relatively quick entry into a somewhat longer spell of non-PTM employment. The duration of a nonPTM job is the longest in the fifth cluster, with this being somewhat shorter in the case of the sixth cluster. The fourth cluster encompasses transitions into PTM employment. Similar to the first cluster, here we encounter both quick and delayed entries into PTM employment, which lasts from several months to several years. In accordance with our expectations, individuals starting their careers in this cluster should experience more favourable labour market outcomes later on. Whereas the average number of elements in clusters 2–6 is about 2, cluster 1 is characterized by a larger number of various statuses (almost 4) (see Table 2). Table 2 also delivers information on the composition of the whole sample and of the identified clusters in regard to the selected characteristics of its members. Immigrants’ educational level clearly varies across the clusters. The first cluster is predominantly occupied by immigrants with tertiary or general secondary

education, who are likely to participate in further education and training or retraining programmes. Tertiary educated immigrants also dominate the PTMemployment cluster (number 4), whereas immigrants with other educational levels are clearly underrepresented here. Tertiary educated are, on the other hand, obviously underrepresented in all clusters encompassing non-PTM employment positions, apart from cluster 3, in which non-PTM employment follows after a long period of joblessness. Individuals with an education below tertiary, tend to predominantly start their employment careers in Germany in non-PTM jobs. Immigrants with a recognized education are substantially more likely to be found in clusters dominated by PTM employment and training. It seems that a higher proficiency in the German language prior to migration contributes to an easier entry into the PTM employment cluster. Compared to the rest of the sample, immigrants in Cluster 5 and 6 are also more likely to have had some command of the German language prior to their migration. Having no friends in Germany prior to migration does not seem to be a handicap in securing relatively quick employment entry (clusters 4 and 5). Having demonstrated a successful employment career in the FSU is also associated with higher-status employment in Germany. Individuals in cluster 4 are clearly more advantaged when it comes to the occupational status of the jobs they pursued back in the FSU. Age at migration, on the other hand, does not seem to be a strong differentiating factor. A single exception is that younger immigrants flock into the education and training cluster. Overall, the results of this descriptive exercise largely confirm non-randomness in immigrants’ selection in regard to their early career trajectories in Germany.

Table 2 Selected characteristics of individuals in the identified clusters (column percentage in italics if not stated otherwise). Clusters 1

2

3

4

5

6

All

Proportion (out of total, row %) Mean number of elements (SD in parentheses)

12.91 3.92 (0.33)

29.51 1.99 (0.31)

21.31 2.08 (0.39)

13.73 2.13 (0.55)

7.99 2.03 (0.36)

14.55 2.10 (0.51)

100 2.30 (0.75)

FSU education Lower secondary General secondary Vocational secondary Post-secondary Tertiary

0.00 14.29 4.76 20.63 60.32

13.19 12.50 18.75 33.33 22.22

10.58 3.85 24.04 25.00 35.58

2.99 1.49 1.49 16.42 74.63

15.38 12.82 23.08 33.33 15.38

14.08 12.68 29.58 28.17 15.49

9.84 9.43 17.62 26.84 35.66

Recognition of FSU education

65.08

20.14

37.50

71.64

20.51

26.76

37.70

Spoke German at least ‘OK’ before immigration

7.94

7.64

7.69

11.94

10.26

9.86

8.81

Had no friends in Germany before immigration

23.81

25.00

24.04

40.03

35.90

19.72

26.84

ISEI of FSU job (SD in parentheses)

45.06 (28.71)

39.10 (19.43)

43.58 (22.69)

60.24 (24.74)

35.18 (19.16)

41.49 (17.64)

43.76 (23.06)

Age at migration (SD in parentheses)

30.52 (7.31)

32.37 (8.26)

31.85 (8.09)

31.75 (6.85)

31.49 (7.02)

31.11 (7.09)

31.68 (7.65)

N

63

144

104

67

39

71

488

Note: For the description of clusters see Fig. 1.

I. Kogan, M. Weißmann / Advances in Life Course Research 18 (2013) 185–198

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6.3. Returns to initial career paths

Individuals pursuing education and training in their early careers seem to be somewhat younger, more educated, and able to get their FSU education recognised. Individuals starting in the PTM employment cluster are more likely to have been working in higher-status jobs back in their home countries, possess tertiary education, and enjoy recognition of their diplomas from the FSU. Positive selfselection into these two more ‘promising’ clusters is likely to play a role in the explanation of these clusters’ hypothetically more positive effects for the later career outcomes.

In the following section, we finally address the question, whether immigrants’ initial career trajectories leave distinct imprints on their later labour market outcomes and scrutinize the possible mechanisms responsible for this. The focus is, first, on immigrants’ occupational status and, second, on the net monthly wages of their employment. The modelling is organized in the following manner. In Model 1 we assess the gross effect of job entry trajectories while controlling for missing career elements, i.e., years since

Table 3 OLS regression coefficients predicting occupational status (ISEI) of the current employment (in 2007) amongst FSU immigrants. Model 1 Clusters of job entry Starting with training Quick entry to a short spell of non-PTM employment Slow entry to a short spell of non-PTM employment Starting with PTM job Quick entry to a long spell of non-PTM employment (ref.) Quick entry to a shorter spell of non-PTM employment

Model 2

Model 3

15.66*** 0.89 1.02 27.99***

(2.65) (2.52) (2.51) (2.67)

6.36* 0.68 1.61 16.93***

(2.50) (2.26) (2.26) (2.58)

0.17 1.05 1.29 14.58**

(5.28) (4.46) (4.65) (5.55)

1.19

(2.70)

0.55

(2.42)

0.04

(3.44)

1.55* 0.01 2.71+ 0.25 3.17**

(0.76) (0.89) (1.59) (0.64) (1.17)

Characteristics of trajectories Length PTM employment Length of non-PTM employment Length of first job/training Length of non-employment Length of schooling Current status characteristics Years since migration Current job tenure

0.48+ 0.02

(0.28) (0.28)

Pre-migration characteristics FSU education (low-sec. – ref.) General secondary Vocational secondary Post-secondary Tertiary Recognition of FSU education ISEI of FSU job Not employed in FSU No friends in DE before migration German language at least ‘OK’ Socio-demographic characteristics Female Jewish migrants Married at time of immigration Marital status missing Age at migration (18–30–ref.) 31–40 41–50 Personality traits (centered) Conscientiousness Openness Extraversion Agreeableness Neuroticism Constant N R2 Adjusted R2 Note: Standard errors in parentheses. + p < 0.1. * p < 0.05. ** p < 0.01. *** p < 0.001.

25.03***

(3.30) 437 0.392 0.382

0.51* 0.13

(0.25) (0.25)

0.34 0.23

(0.28) (0.28)

2.67 1.00 2.02 7.22** 3.08* 0.08+ 2.78 1.88 0.38

(2.51) (2.12) (2.06) (2.41) (1.28) (0.05) (2.91) (1.23) (4.34)

2.17 1.07 2.17 6.62** 3.23* 0.09+ 2.70 1.46 0.27

(2.53) (2.15) (2.05) (2.42) (1.27) (0.05) (2.89) (1.23) (4.29)

4.51*** 5.39*** 1.71 1.76

(1.22) (1.43) (1.39) (2.61)

4.23*** 5.44*** 1.56 1.25

(1.23) (1.41) (1.38) (2.58)

2.33+ 6.19***

(1.26) (1.75)

2.33+ 6.09***

(1.25) (1.73)

0.21 0.18 0.13 0.24 0.08 23.02***

(0.20) (0.15) (0.16) (0.21) (0.17) (3.83)

0.08 0.17 0.16 0.33 0.08 23.78***

(0.20) (0.15) (0.16) (0.21) (0.17) (5.85)

437 0.562 0.533

437 0.578 0.545

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we take the duration in each of the possible states into account, pursuing the aim of estimating a residual effect of cluster membership apart and beyond its constitutive elements. Table 3 presents the results of the analyses which pertain to the question of whether a successful career start in Germany ensures higher status employment in the long run. The findings lend support to our major expectation: entry into PTM employment early in the

migration and tenure in the current job, as well as accounting for the number of working hours (the latter variable is included only in the analyses of monthly wages). In Model 2 we take pre-migration (e.g., education or FSU occupation), socio-demographic characteristics, and personality traits into account. This is done in order to estimate effects of early career trajectories net of the compositional differences between them, for which we obviously have evidence (see section above). In Model 3,

Table 4 OLS regression coefficients predicting monthly wages (ln) of the current employment (in 2007) amongst FSU immigrants. Model 1 Clusters of job entry Starting with training Quick entry to a short spell of non-PTM employment Slow entry to a short spell of non-PTM employment Starting with PTM job Quick entry to a long spell of non-PTM employment (ref.) Quick entry to a shorter spell of non-PTM employment

Model 2

Model 3

0.19 0.08 0.05 0.66***

(0.15) (0.14) (0.14) (0.15)

0.09 0.08 0.05 0.53**

(0.16) (0.14) (0.14) (0.16)

0.04 0.09 0.08 0.35

(0.33) (0.28) (0.29) (0.35)

0.25+

(0.15)

0.23

(0.15)

0.22

(0.21)

0.09* 0.01 0.06 0.01 0.06

(0.05) (0.05) (0.10) (0.04) (0.08)

Characteristics of trajectories Length PTM employment Length of non-PTM employment Length of first job/training Length of non-employment Length of schooling Current status characteristics Years since migration Current job tenure Weekly working hours

0.05** 0.05** 0.05***

(0.02) (0.02) (0.00)

Pre-migration characteristics FSU education (low-sec. – ref.) General secondary Vocational secondary Post-secondary Tertiary Recognition of FSU education ISEI of FSU job Not employed in FSU No friends in DE before migration German language at least ‘OK’ Socio-demographic characteristics Female Jewish migrants Married at time of immigration Marital status missing Age at migration (18–30–ref.) 31–40 41–50 Personality traits (centered) Conscientiousness Openness Extraversion Agreeableness Neuroticism Constant N R2 Adjusted R2 Note: Standard errors in parentheses. + p < 0.1. * p < 0.05. ** p < 0.01. *** p < 0.001.

4.63***

(0.22) 350 0.559 0.548

0.05** 0.05** 0.04***

(0.02) (0.02) (0.00)

0.04* 0.06** 0.04***

(0.02) (0.02) (0.00)

0.10 0.05 0.03 0.13 0.07 0.00 0.25 0.07 0.14

(0.15) (0.13) (0.13) (0.14) (0.08) (0.00) (0.17) (0.08) (0.29)

0.10 0.03 0.00 0.13 0.07 0.00 0.23 0.06 0.15

(0.15) (0.13) (0.13) (0.15) (0.08) (0.00) (0.17) (0.08) (0.29)

0.30*** 0.09 0.04 0.17

(0.08) (0.09) (0.08) (0.16)

0.29*** 0.08 0.05 0.16

(0.09) (0.09) (0.08) (0.16)

0.08 0.29**

(0.08) (0.11)

0.07 0.27*

(0.08) (0.11)

(0.01) (0.01) (0.01) (0.01) (0.01) (0.27)

0.03* 0.01 0.01 0.01 0.00 4.94***

(0.01) (0.01) (0.01) (0.01) (0.01) (0.39)

0.03* 0.01 0.00 0.00 0.00 4.92*** 350 0.608 0.574

350 0.615 0.574

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immigrants’ employment career is associated with employment in the highest-status occupations later on. Starting with education and training in Germany, also subsequently secures higher-status employment, although the effect is not as strong as the one associated with entering PTM employment after migration. Entering a short or long-term non-PTM first job, either (almost) immediately upon arrival or after some adjustment period, does not seem to differentially affect the occupational status of the later employment, once YSM and the current job tenure are held constant. Once we control for compositional differences across the analysed clusters in terms of immigrants’ premigration, socio-demographic characteristics, and personality traits in Model 2, the advantages in terms of higherstatus occupations amongst immigrants in the first (training) and fourth (PTM-employment) clusters of job entry are substantially reduced, but remain pronounced. This finding indicates that a part of the advantage associated with more ‘promising’ clusters is related to the positive selection of individuals constituting these clusters. Once duration in various statuses is accounted for, as in Model 3, only those immigrants starting their career in Germany by entering PTM jobs display significant advantages in terms of their higher-status current employment (a premium of about 14.6 ISEI points). A careful look at the characteristics of trajectories which contribute to a more favourable job status, suggests that schooling and PTM employment in the earliest years in Germany play a decisive role. Most importantly, longer investment in education and training seems especially helpful for the later career: each year in schooling or training increases the ISEI-status of the current employment by 3.17 points. An additional year in PTM employment raises the status of the current job by only 1.55 ISEI points, beyond the overall premium for being employed in a PTM-job, other things being equal. A marginally significant negative effect of the training conducted in a firm setting seems, at first glance, somewhat surprising. It may however be related to the difficulties of transferring job-specific skills acquired during on-the-job training from one firm to another. Another notable finding is the lack of any significant negative effects associated with the length of time spent in non-employment for the later career. The bulk of the human capital characteristics operate in the expected direction. Tertiary education is associated with higher status employment; recognition of education considerably helps in increasing ISEI-status as well. Having better employment back in the FSU seems to be helpful in acquiring a better job in the receiving country; this effect is however only marginally significant. Women acquire jobs with lower ISEI than men; Jewish immigrants are, on the other hand, more successful. Finally, the chances of entering higher-status occupations in Germany decrease with older age upon arrival, hitting the bottom when immigrants are between 41 and 50 years old. Turning now to the analyses of monthly wages (see Table 4), we observe a significant wage premium for

195

immigrants who started their careers in Germany with PTM employment. A quick entry into a shorter spell of non-PTM employment seems to be rewarded as well, as compared to a quick entry into non-PTM jobs of longer duration, yet this effect is only marginally significant. A significant effect of starting in PTM employment on later wages remains largely preserved, albeit being somewhat reduced, once we control for pre-migration, socio-demographic characteristics, and personality traits. However, once characteristics of the analysed trajectories enter Model 3, all the effects of job entry clusters totally vanish. This implies that in terms of wages, the effects of early career trajectories are mediated by host-country work experience or accumulation of German-specific human capital and other resources associated with working in Germany. Each year in PTM employment significantly increases wages in the later job by 9%. The wage premium for schooling and on-the-job training is also substantial, but remains below the threshold of statistical significance. No wage penalties can be reported for career starts in nonemployment or lower-status jobs. Monthly wages are, not unexpectedly, related to working time. We also observe a strong significant gradient of the tenure in the current job on wages, which would also be in accordance with the argumentation of the human capital theory. Accumulation of host-country specific resources and experiences, captured by the YSM variable, also seem to play a significant role in predicting wages of the current job, whereas other pre-migration characteristics no longer matter. Arriving in Germany at an older age (over 40) is clearly penalized in the German labour market in the long run. Women from the FSU earn at least 30% less than men; conscientious individuals receive higher wages. 7. Summary and discussion In recent years, migration research has acknowledged the importance of the process character of immigrants’ labour market integration, moving away from the description of integration outcomes at specific time points, whilst disregarding the underlying dynamics and trajectories. In concurrence with this emerging line of research, the current paper pursues the question of how immigrants’ start in a new society determines their later success and whether these first years leave their distinguishable imprints on the newcomers’ later employment careers. The German situation is insofar telling, as there are signs of substantial difficulties even amongst highly educated immigrants in obtaining gainful employment, and in matching their qualifications in Germany’s skill-oriented labour market. The analysed group of FSU immigrants is particularly suitable to answer our research questions due to these immigrants’ permanent settlement intentions assuring that we are able to observe almost all immigrants entering the country in the subsequent years. Which particular employment trajectory newcomers pursue upon their arrival in Germany largely depends on their socio-demographic characteristics and pre-migration

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human capital. Hence, the finding that a large part of the effects of early careers is related to individuals’ self-selecting into specific initial employment trajectories is not surprising. As a result, the later advantages of those who started successfully in Germany are at least partially due to their better human capital and more favourable socio-demographic characteristics. Compositional differences are, however, not able to fully explain the impact of initial trajectories on later labour market outcomes. In pursuance of the research question, what is so special about these initial trajectories that they may be capable of leaving such imprints on the subsequent economic outcomes, we looked at the constituting elements of these careers. We asked ourselves whether the effect of practicing a PTM-job is solely related to gaining favourable experience, resources, and skills, or whether there is more than just a sheer human capital acquisition. Do successful early careers provide immigrants with a transferable signal that they themselves can use for their future employment decisions or that prospective employers are able to recognise and reward? We explored this research question by analysing two labour market outcomes – occupational status of current employment and wages. First of all, we can show that starting successfully in Germany, i.e., entering higher-status employment after arrival, clearly helps immigrants gain higher-status occupations later on. Also, resource accumulation during the initial years in Germany is a part of the explanation for more successful economic standing of immigrants in the long run. Furthermore, we record a distinct signal associated with early success, which is meaningful for acquiring higher-status employment in later years apart and beyond mere human capital accumulation. These findings lend support to the signalling argument. Whether initial success raises the occupational aspirations of immigrants or whether employers perceive immigrants’ earlier success as a positive signal and hence entrust immigrants with better jobs, cannot explicitly be answered with the data at hand. Based on the findings that initial career trajectories do not leave any imprints in terms of wages, beyond the pay-off of the human capital and hostcountry relevant skills acquired while pursuing these careers, we are more inclined to relate the signalling effect of early careers to employees’ elevated expectations. Whereby employers seem to appreciate jobseekers’ favourable CVs and hire them to high-status jobs, they appear less inclined to additionally reward immigrants in pecuniary terms. Our results also indicate that immigrants aspiring for better-status employment should not settle on lowstatus jobs upon arrival, as this pathway does not seem to be promising in the long run. If the prospect of quickly entering the higher-status labour market is bleak, the best strategy, according to our results, would be the acquisition of German-source education or training. Even though we do not observe any monetary rewards associated with completion of education and training in Germany, each additional year of education and training significantly contributes towards higher-status employ-

ment in the subsequent career. Finally, our results do not indicate any scars related to particularly long nonemployment or lengthy spells of lower-status employment on the job status or wages of immigrants’ later careers. Key additional findings of our study extend to the importance of higher education and educational recognition for immigrants’ entering higher-status employment. Furthermore, in regard to both outcomes analysed, we find substantial disadvantages for labour market success when migrating at an older age. Moreover, we observe consistent gender inequalities in the immigrant labour market: women pursue occupations of lower status, and earn lower wages than their male counterparts; an important topic for future research. Finally, in accordance with earlier research, we observe that Jewish immigrants appear more successful at entering higher-status employment, albeit without experiencing the benefits of higher wages associated with it. When interpreting our results, we have to bear in mind that by only analysing occupationally mobile individuals, we are more than likely ignoring more recent arrivals in Germany. We are also more likely focusing on younger, male immigrants as well as those who had higher-status jobs back in their home countries. At the same time, our respondents are less likely to have been employed in higher-status jobs in their first employment in Germany. Based on these findings, it seems rather difficult to mark these occupationally mobile immigrants as either a positively or negatively selected group – they are apparently positively selected on some dimensions but not on others. Furthermore, since we are only able to get a glimpse at a rather short period of residency in Germany our results should be interpreted cautiously. Immigrants’ early careers were operationalized through their very first employment and education/training spells without taking into account longer and more complicated sequences of various employment and training statuses. As the observed sequences are short, the amount of temporal variability appears rather limited. Due to this the sequences naturally may not have much of an emergent own component beyond their constitutive elements. Further research with true longitudinal data and longer observation periods should deliver more conclusive results in this regard. With the aim of contributing to the understanding of the situation of recent immigrants in Germany, the results of our study are relevant for migration research at large. Immigrants from the FSU are a typical example of the highly educated immigrants, which increasingly dominate the migration flows into western industrialized countries. Consequently the questions that this article raises are relevant for other immigrant-receiving societies, because in the grander scheme of things it aims to understand how highly educated immigrants make their initial steps in a new society, accumulate relevant human capital and work experience, and translate these into favourable labour market outcomes in the long run.

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Appendix A See Table A.1. Table A.1 Description of the variables in the analyses. Variable description Dependent variables ISEI of current job Wage of current job Independent variables Clusters of job entry

Occupational status of current job in Germany, measured against the International Socio-Economic Index (ISEI) Logarithmized gross monthly wages from current employment

(1) Starting careers with education/training; (2) Quick entry to a short spell of non-PTM employment; (3) Slow entry to a short spell of predominantly non-PTM employment; (4) Starting with PTM job; (5) Quick entry to a long spell of non-PTM employment (reference category); (6) Quick entry to a shorter spell of non-PTM employment

Characteristics of trajectories Length PTM employment Length of non-PTM employment Length of first job combined with training Length of non-employment Length of schooling

Length of first PTM-job (in years) Length of first non-PTM-job (in years) Length of combined spell of training and first job (in years) Length of initial non-employment period (i.e., not in training, school, or job) in Germany (in years) Length of schooling or training (in years)

Current status characteristics Years since migration Current job tenure Weekly working hours

Years since migration = Year 2007 Year of migration Length of current job (in years) Average weekly working hours in current job

Pre-migration characteristics FSU education

Recognition of FSU education ISEI of FSU job Not employed in FSU No friends in Germany before migration German language at least ‘OK’

Socio-demographic characteristics Female Jewish migrants Married at time of migration Marital status at migration missing Age at migration

Highest educational degree obtained in country of origin, dummy-coded variables: (1) lower secondary (either general or vocational) – ref.; (2) general secondary; (3) vocational secondary; (4) post-secondary non-tertiary; (5) tertiary FSU educational degree fully/partially recognized (=1), no/not tried (=0) ISEI of last job in country of origin Was not employed in/no information about job in country of origin (=1), was employed (=0) Had no friends in Germany before immigration (=1), rest (=0) Spoke German language before immigration ‘‘very good’’, ‘‘good’’ or ‘‘okay’’ (=1) versus ‘‘poorly’’ or ‘‘not at all’’ (=0)

Respondent is female (=1), male (=0) Respondent is Jewish Quota Refugee or a subsequent immigrant to a Jewish Quota Refugee (=1), Ethnic German or a subsequent immigrant to an Ethnic German (including family reunification) (=0) Respondent was married at time of migration (=1), rest (=0) No information about respondent’s marital status at time of immigration (=1), rest (=0) Respondent’s age at time of immigration: (1) 18–30 (reference), (2) 31–40, (3) 41–50

Personality traits (centred around the sample mean) Openness A sum score of the items ‘Seeing oneself as original, coming up with new ideas, who values artistic experience and has active imagination’ Conscientiousness A sum score of the items ‘Seeing oneself as the one who does a thorough job, is not lazy, does things effectively and efficiently’ Extraversion A sum score of the items ‘Seeing oneself as communicative, talkative, outgoing, social, and not reserved’ Agreeableness A sum score of the items ‘Seeing oneself as not rude to others, with a forgiving nature, considerable and kind to others’ Neuroticism A sum score of the items ‘Seeing oneself as someone who worries a lot, gets nervous easily, is not relaxed and handles stress badly’

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