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ABSTRACT
Given the challenges immigrants and their descendants face in entering the labour market, we add to the existing literature by considering a previously neglected explanation: a foreign accent. Using unique data with objective accent measures from the Children of Immigrants Longitudinal Survey in Four European Countries (CILS4EU), we first establish whether foreign-accent effects could be found in a non-experimental setting. Second, we seek to disentangle the accent effect by human capital, signalling, and discrimination approaches. Finally, we explore the extent to which employment and educational paths of accented speakers reflect their self-selection into the fields of study that lead to occupations for which accented speech is not a precondition. Our findings demonstrate that respondents with a stronger foreign accent are more likely to be found in occupations for which language skills are less essential. This is in line with the human-capital explanation. Self-selection tendencies might also be present, even though the findings are equivocal. Our analyses lend no support to the statistical discrimination explanation, as employers’ perceptions of foreign accents do not vary according to the extent of their contact with accented speakers at work or at home.
Disclosure statement
No potential conflict of interest was reported by the author(s).
Ethical approval and informed consent
The CILS4EU-study obtained ethical approval from the ethical vetting board from the Universities of Stockholm, Oxford and Mannheim. The Dutch team did not need to obtain ethical approval, but they followed the same ethical standards as the other research teams. Furthermore, informed consent prior to participating in the survey was provided by all participants.
Notes
1 N = 5,074 respondents agreed to participate in face-to-face interviews, while the remaining 746 respondents were interviewed via web or postal questionnaires or via telephone interviews. During the face-to-face interviews, 4,059 respondents agreed to be recorded which was the basis for our accent rating.
2 We grouped the vocational training programmes in this fashion since the number of respondents enrolled was too small to be analysed separately. We decided to group apprenticeships together with the work category as dual vocational training has a strong labour-market orientation. Trainees have to apply for apprenticeship positions with a training company, and they spend three to four days working on the job. Schools-based training courses also have practical phases, which differ between occupations.
3 Release version 25.0 (https://www.onetcenter.org/database.html).
4 While the classification is sponsored by U.S. Department of Labor/Employment and Training Administration (USDOL/ETA) and refers to US-American occupations, it is also used in research on European context (e.g. Hardy, Keister, and Lewandowski Citation2018).
5 In the following, we only describe the procedure for importance rating of the language domains. Further information can be found at https://www.onetcenter.org/reports.
6 http://ibs.org.pl/en/resources/occupation-classifications-crosswalks-from-onet-soc-to-isco/ (version from April 6, 2016; last accessed November 20, 2023).
7 NEPS is carried out by the Leibniz Institute for Educational Trajectories (LIfBi, Germany) in cooperation with a nationwide network.
8 Top five occupations coded as ‘Language is not important’ by our procedure (ISCO-08 code in brackets): General office clerks (4110); Dental assistants and therapists (3251); Medical assistants (3256); Agricultural and industrial machinery mechanics and repairers (7233); Accounting associate professionals (3313).Top five occupations coded as ‘Language is important’: Shop sales assistants (5223); Nursing associate professionals (3221); Child care workers (5311); Police officers (5421); Trade brokers (3324). Top five study subjects coded as ‘Language is not important’: Civil Engineering; Mechanical Engineering; Informatics; Civil Engineering; Business Informatics; Pharmaceutics. Top five study subjects coded as ‘Language is important’: Business Administrations; Interdisciplinary Studies (Focus Area: Law, Business and Social Science); Law; Medicine; German. All refer to our analytical sample (see below).
9 For initial panel respondents without information on these tests, we used information for achievement tests administered in wave one (the test consisted of 30 synonyms to pick from).
10 See in the Appendix for the assignment of countries of origin as found in the CILS4EU-DE data to the respective groupings.
11 This information was taken from retrospective information on education histories from a life history calendar (LHC) administered in wave six as well as information from wave seven and wave eight. In addition, for respondents from the initial panel sample, we used repeated cross-sectional information about acquired degrees provided during wave two to wave eight.
12 We used the Scientific Use Files of the German Microcensus from the years 2012 to 2016 (RDC of the Federal Statistical Office and Statistical Offices of the Federal States, Microcensus, Scientific Use Files, survey years 2012–2016; all result used are own calculations).
13 As a robustness-check, we also focussed on respondents first job. For this, we made use of retrospective longitudinal information on respondents' education, training, and labour market careers from a life history calendar (LHC) in wave six. From this data set, we defined the first employment that lasted for more than six months after having left the education and training system for more than twelve months as the first job. If no such job occurs in the LHC, we used the first information on employment from either wave seven or wave eight. Respondents without employment information were coded as tertiary students if they reported to study during their last observed interview. The remaining respondents were coded as ‘other status’. Even though point estimates seemed to be reduced, results from Tables A3 and A4 in the Appendix show comparable results to our main analyses.
14 We also tested whether a foreign accent means something different for different ethnic groups. Although such ethnic hierarchies seem plausible, we do not find significant interaction effects between ethnic groups and the strength of foreign accents except for respondents from Southern Europe (cf. in Appendix). This finding is consistent with other findings regarding the role of foreign accents for the formation of friendships and romantic relationships (Kogan, Dollmann, and Weißmann Citation2021) as well as for the German school context (Lorenz et al. Citation2023), where the authors report that statistical relationships between non-native student accents and teacher achievement expectations in language and mathematical domains are independent of the concrete ethnic origin.
15 For respondents that have not applied for a position up until wave six, having a stronger accent is associated with a higher propensity of pursuing higher education in fields of study that typically lead to occupations where language is more important. However, no information is available as to why these respondents never have applied for any position which makes an informed interpretation difficult.
16 Income was provided in the data as categorical information which we replaced as follows: 0-200 Euro: 100 Euro; 401-600 Euro: 500 Euro; 601-800 Euro: 700 Euro; 801-1,000 Euro: 900 Euro; 1,001-1,200 Euro: 1,100 Euro; 1,201-1,400 Euro: 1,300 Euro; 1,401-1,600 Euro: 1,500 Euro; 1,601-1,800 Euro: 1,700 Euro; 1,801-2,000 Euro: 1,900 Euro; More than 2,000 Euro: 2,100 Euro.