This paper is published as: Janta, H., Jephcote, C., Williams, A. M., & Li, G. (2019). Returned migrants acquisition of competences: the contingencies of space and time. Journal of Ethnic and Migration Studies, 118. https://doi.org/10.1080/1369183X.2019.1679408 ***Please consult the final published version if citing*** “Returned Migrants Acquisition of Competences: the Contingencies of Space and Time” Hania Janta*1 ORCID: https://orcid.org/0000-0001-6545-5266, Calvin Jephcote1;2 ORCID: https://orcid.org/0000-0003-0464-8448, Allan Williams1 ORCID: https://orcid.org/0000-0001-61343611, Gang Li1 ORCID: http://orcid.org/0000-0002-9858-5232 *1Faculty of Arts and Social Sciences, University of Surrey, UK 2 Centre for Environmental Health and Sustainability, University of Leicester, UK 1 Abstract The conditions which determine the acquisition of skills by migrants are still poorly understood. This paper addresses two of those conditions: the temporality of the acquisition of competences, whether the number and duration of migrations matter, as well as the spatiality, or the variation across countries of origin and return. Based on a large-scale online panel survey of returned young migrants in nine European countries, the significance of time (duration) and space (number of migrations) in the acquisition of skills and competences are examined. The findings reveal that young European returnees‟ experiences gained abroad result in largely positive outcomes but with significant differences between formal qualifications, language skills and personal and cultural competences. However, their acquisition of skills and competences is mediated by temporality – the combination of number of trips, and duration of migration. Spatiality is also important, with outcomes depending on the destination countries, and whether migration and return are from or to rural versus urban areas. These indicate that structural considerations continue to shape individual migration experiences within the EU‟s freedom of movement space. Keywords: human capital, competences, time and space, youth migration, intra-EU mobility 2 Introduction The acquisition of skills and competences has long been recognised as an individual outcome of international migration in Europe (Dustmann 1999; Williams and Baláž 2005; Williams 2006), with significant implications for migrant‟s welfare and long-term employability. In seeking to understand the determinants of the skills outcomes, most researchers have focussed on the characteristics of the individuals (existing skills, education etc.) and their networks (Lulle and Buzinska 2017; Lados and Hegedus 2016; Barcevičius 2016). The characteristics of the migration process itself have been neglected, with our understanding of both temporality and spatiality being relatively weak and fragmented. This paper addresses these two fundamental gaps: the first in how the temporality of migration (the duration of migration, as well as the number of migrations) influences learning: are there either minimum thresholds or diminishing returns to learning (Cushner and Mahon 2002; Williams and Baláž 2005)? Secondly, how does spatiality – or where you migrate to or from – shape the acquisition of competences? These are important questions in the face of shifts in the nature of migration, as well as the increasing importance attached to migration as a vehicle for skills acquisition, employment and employability. This study aims to fill these gaps and contribute to the understanding of the acquisition of skills and competences through international mobility experience(s), by addressing the following research questions. Firstly, what is the importance of total migration duration, the number of migrations, and the interaction between these, for acquiring skills and competences? Secondly, what is the „optimum‟ migration duration in acquiring skills and competencies? And thirdly, which skills and competences are acquired in different countries (studied at the level of macro-regions), and urbanrural areas, of origin and return? This study draws on a large-scale online panel survey of young people aged 16-35, undertaken in nine European countries in late 2015, as part of the EU H2020 project YMOBILITY. It uses a data subset of 3,542 return migrants, who had spent at least six months abroad. The paper is structured as follows. We first review the literature on the competences and skills acquired via migration return. In the second part of the literature review, we consider the 3 somewhat fragmented evidence on how space and time affect individuals‟ success in obtaining competences through international migration. We then outline the methods used. Our results are presented in two parts; first, the acquisition of competences in relation to duration and number of migrations is examined, and second; the importance of space in the acquisition of competences, including the role of the urban-rural areas of origin and return as well as that of migrants originating and migrating from/to different European macro regions. The paper ends with a discussion with conclusions. Mobility and Lifelong Learning Some earlier studies of return migration portrayed migrants‟ decision to go back to their homeland as a failure in terms of either their lack of competences or opportunities to utilise these; whether in economic (Borjas and Bratsberg 1996) or socio-cultural terms (Gmelch 1980). More recent research portrays return as a chance to utilise the newly required skills and unique knowledge that returnees possess (Williams 2006). Despite the tendency to separate highly skilled professionals from unskilled workers, it is contended that all migrants can potentially add to the stocks of skills and competences in the countries and regions they return to (Williams and Baláž 2005). Even those with little schooling informally learn through migration, and these competences can enable them to make an enhanced economic contribution after returning (Hagan and Wassink 2016). These contrasting views of the outcome of return migration reflect Cerase‟s (1974) seminal distinction between different types of return. This in turn leads to consideration of the key determinants of the considerable variation in skills and competences that have been acquired by individual migrants, a theme we return to in the next section. First, however we consider further the notion of competences. Increasing attention has been paid by researchers to the competences gained via international migration, rather than only to more formal skills. The „starfish model‟ of competences created by Evans (2002), developed as a basis for investigating informal learning experiences, captures a range of abilities that show „successful change, adaptation and personal growth in ways that transcend national boundaries‟ (2002, 86). These soft skills are grouped into five categories; Learning abilities (i.e. adaptability to different learning contexts), Social and interpersonal abilities (i.e. creativity, 4 awareness of others‟ viewpoints), Methodological competences (i.e. problem solving, networking), Competences related to values and attitudes (i.e. reliability, tolerance) and Content related and practical competences (i.e. operating in a modern work environment). Many of the soft skills listed by Evans (2002) can be gained via accelerated learning opportunities provided by mobility. Among these, (English) language skills, intercultural knowledge, and self-confidence are key achievements often cited as outcomes of international mobility, as opposed to or in addition to prestigious qualifications (i.e. Jendrissek 2016). Among those, ‟language capital‟ (Dustmann 1999), English, which can be defined as an internationalised form of human capital, relatively easily transferrable to other locations, and valued in global labour markets, is particularly appreciated by both migrants and students. Considered as a migration driver and a shaper of individuals‟ migration and return experiences, it enhances wages and career prospects after return (Lianos and Pseiridis 2009). Conversely, a failure in obtaining language fluency poses challenges in home labour market reintegration (Lados and Hegedus 2016). For international student mobility, the main driver is completion of a foreign degree but students also acquire a range of other skills during their sojourn. Because of their dual status emanating from combining their study with the potential or need to work they can gain various skills during their sojourn in both the educational and workplace arenas (Bijwaard and Wang 2016; Lulle and Buzinska 2017). However, students differ from labour migrants because formal qualifications are as important as the soft skills and other competences acquired during migration. The various competences discussed above can be understood in context of lifelong learning defined as an array of processes that an individual encounters throughout their lifetime; this is increasingly championed by national as well as international bodies such as the EU (European Commission 2018). These processes are „integrated into the individual person‟s biography resulting in a continually changing (or more experienced) person‟ (Jervis 2007, 1). However, over the life course individual learning is less likely to change radically, so that the youth and young adult stages are particularly important in this respect. This is also the life course stage at which the propensity to migrate is strongest, and the opportunities offered by mobility for lifelong learning are substantial (Williams and Baláž 2008). However, there are considerable variations in how migration contributes 5 to lifelong learning (Guo 2010; Morrice 2014). This is a major gap, which is considered more detail in the following section. Success in Acquiring Competences – the Influence of Time and Space The length of the migration and the optimal duration have been subject to a number of quantitative studies, although mostly in terms of economic outcomes, such as wages in the home- and host regions, rather than skills acquisition. Yet these studies help explain individuals‟ decisions whether to invest (or not) in the development of particular skills. In terms of the duration of migration, Constant and Massey (2003) argued that the odds of returning were the highest in the first five years after arrival, while Dustmann and Weiss (2007) suggested that the duration was longer; migrants were likely to return in the first decade of their sojourn. The level of schooling decreased the length of the migration period; hence the more highly skilled migrants returned earlier (Dustmann and Kirchkamp 2002). There is also an argument that the planned length of stay, rather than the actual duration, of migration is key to understanding investment decisions in human capital (Adda, Dustmann, and Görlach 2015, 4). Planned shorter sojourns may deter individuals from investing in the development of country-specific human capital, such as new language skills. In their study of highly-skilled migrants in Hong Kong, Findlay, Li, Jowett, Brown and Skeldon (1994) found that the probability of return was the highest amongst those who had been absent for one to two years, and the probability of return subsequently declined. More recent studies echo this finding. White (2014) who looked at a socio-economically diverse group of Polish returnees, also pointed to two years being the optimal duration for obtaining new skills while at the same time sustaining strong links with the home country. The optimal duration is different for student cohorts. Analysis of a large representative data set for international students in the Netherlands found that graduates accumulate their human capital through education and then work by prolonging their sojourn for another two years (Bijwaard and Wang 2016). While there have been a number of studies of migration duration, the question of how the length of stay affects effective learning of various competences remains under-researched. The few 6 available studies point to international migrants having short learning curves for competences. A study of USA students found that very short experiences of working abroad, between 8 and 14 weeks, were valuable in terms of expanding cross-cultural knowledge (Cushner and Mahon 2002). Focusing on returnees to Slovakia, Williams and Baláž (2005) also found that even very short sojourns abroad, up to six months, significantly enhanced one‟s skill portfolio, although this was selective in terms of particular competences. Unsurprisingly, the acquisition of language skills, for some migrants the main objective of their visits, was the most highly rated by competence by the three contrasting groups in this study: professionals, students and au pairs. In addition, self-confidence appeared to be an important competence learned, irrespective of duration. Next, we need to consider where one learns. Countries, regions and cities shape an individual‟s skills acquisition and learning. Where one learns clearly matters; and some global, creative cities becomes strongly associated with learning skills and creativity which is also related to a particular life-cycle stage (Williams 2006). For example, London has gained a reputation as a global financial hub (King, Lulle, Conti and Mueller 2016) and an educational hub (Findlay, McCollum, and Packwood 2017) promising substantial gains in human capital, even for the lesser skilled migrants (see Moroşanu, King, Lulle and Pratsinakiset, this issue). While there has been considerable research focusing on London, or widely; the UK, as a receiving country, less is known about other „global‟ cities or other regions that shape mobile individuals‟ learning and future careers. Another research gap relates to understanding how the recent changes in international mobility, including the increased tendency to multiple migration, relates to learning. In this study, for example, as many as 38% of returnees lived, worked or studied in more than one country abroad. While the number of trips to different destinations is likely to influence individuals‟ skills portfolios, there is a dearth of literature on how these destinations shape individual learning. One study relevant to our analysis is a small qualitative study of Polish women in Barcelona (Main 2014), which focussed on „multiple migrants‟ (having lived previously in other destinations) and the acquisition of two competences: language skills and cultural adaptation. Main (2014) suggested that highly-skilled women tended to become repeat migrants as they combined education and work in their mobilities. Linked to this, King (2018) notes that many European highly-skilled professionals living outside their 7 home countries had their first migration experience as an “Erasmus experience”. This “Erasmus” youth as well as other educational movers (Findlay et al. 2017) are highly-educated and potentially well placed to benefit from living in multiple destinations. Yet, such mobility is arguably linked to a particular life-course stage and tends to pose complex challenges for families with children (Ciobanu 2015). Not only temporality but also spatiality are important in experiences of return, highlighting a distinct divide between core and periphery. A cross-country analysis of return migration using data from the European Union Labour Force Survey (EU-LFS) demonstrated that recent migrants were more likely to return to their regions of origin rather than to other, economically more dynamic regions (Martin and Radu 2012). In White‟s study (2014) as many as 90% of Poles returned to their rural region or small towns because of their caring duties for elderly relatives, childcare provision or housing opportunities. The latter relates to an opportunity for consumption which is not only less costly and pleasurable at home than abroad (or more dynamic region), and is an important motive for return (Dustmann and Weiss 2007). Of course this is likely to constrain the opportunities to utilise skills after return; for example, women returning from Italy to a peripheral area in Romania (Vlase 2013) were unable to find employment. Whatever the reasons – including the potential for circular and „temporary‟ return – many Europeans seemed to be tied to their own regions. Clearly, the usefulness and valorisation of the required skills depends on the regional context, and the return to rural areas poses a number of challenges. Finally, it is also important to consider skills transferability and the value of the new skill portfolio after return, and how this varies across Europe (Lulle, Janta and Emilsson this issue). Recent empirical studies, which are on the newer EU accession countries, suggest that employers seem to be less enthusiastic in taking up young returnees (i.e. Barcevičius 2016). As pointed out in their study of students and workers (Lulle and Buzinska 2017, 1374), the ‟global‟ value of a good degree is highly relative back home if a person lacks social networks‟. Convinced that jobs are only available through arrangements made via informal channels, many consider migrating again. The review of the literature demonstrates positive outcomes of mobility resulting in the acquisition of numerous competences; notably language skills, self-confidence and inter-cultural 8 abilities, yet their valorisation after return is variable. In part this depends on the spatiality of the regional context. Less is known about the impact of the duration and the number of migrations on learning, and the few available studies tend to be based on small qualitative research (i.e. Main 2014). This paper seeks to make a contribution in examining both spatiality and temporality of migration on the skills acquisition using a large dataset. Specifically, it examines the importance of migration duration and number of migrations in acquiring skills and competences, as well as, the influence of macro-regions and the urban-rural environment of origin and return. Methods This study is based on the data from the HORIZON 2020 funded “Youth Mobility (YMOBILITY) project: Maximizing opportunities for individuals, labour markets and regions in Europe”, which collected responses from 29,679 young adults (16-36 years) via an online panel survey exploring their lifestyle, socio-demographics, and behavioural experiences. Data collection took place between November 2015 and January 2016, in nine European countries: Germany, Ireland, Italy, Latvia, Romania, Slovakia, Spain, Sweden and UK. From the panel survey, 3,542 (13.0%) respondents were identified as „returnees‟; having international migration experience of at least six months and now residing in their country of birth. The minimum of six months contrasts with the 12 months that is usually employed in secondary migration data, but is utilised in order to reflect the increasingly shortterm nature of intra-European mobility, particularly among younger people (King 2018) who are the focus of this research. This paper focuses only on the competences of the returnees, and does not seek to compare them to non-return migrants, which poses questions about the selectiveness of return which are beyond the aims and scope of this analysis. Data was not available on the competences of non-migrants. Following a previous study on the acquisition of competences via international migration by Williams and Baláž (2005), self-assessed changes in “human capital” were explored through themes of competency, skill, and behavioural transitions: returnees used a series of 5-point Likert scales to rank the importance of experiences abroad, with responses ranging from (1) “not at all important” to 9 (5) “very important”. Six themes of personal development were captured by the survey: a) Acquiring formal qualifications; b) Learning new skills; c) Ability to deal with new challenges; d) Learning a language; e) Self-confidence, and; f) Learning to adapt to new cultures. Upon establishing the connection between human capital outcomes, the analysis sought to determine whether the acquisition of competences varied across the different sub-populations at a Pan-European level of analysis. Firstly, “Multivariate analysis of variance” (MANOVA) tests assessed if the sub-population groups reported different response to the acquisition of six competences. Then a series of "Analysis of Variance" (ANOVA) tests assessed whether significant differences for a single measure of human capital development exist, across all sub-population groups. Finally, a post-hoc analysis of the ANOVA highlighted significant differences between sub-population group pairings, in the mean acquisition of the six competences. To avoid controversy, this paper presents a two-tick validation approach, with significant linear group-wise comparison and post-hoc trends confirmed by their nonlinear alternative. This is considered a conservative approach towards the interpretation of intuitive linear outputs, and removes the need for the questionable tests of normality and homogeneity. In our study, young European returnees are, unsurprisingly, on average older than the remainder of the total sample (mean = 27 years old), and more likely to be tertiary educated (62%), and to be single without children. Although previous research identified young men as typical returnees (i.e. Coniglio and Brzozowski 2018), our sample shows that there were also substantial numbers of young women returning to their countries of birth. The fluid nature of contemporary mobility is evident in the large proportion (38%) who had migrated to more than one destination. Results: Pan-European Analysis The self-assessed acquisition of formal skills and competences indicates that the experiences gained abroad often result in positive outcomes (TABLE 1). Only 4-9% of respondents identified their experience abroad to have a minimal effect (Likert Score = 1-2). 10 11 TABLE 1: Frequencies for the importance of returned migrant experience abroad in developing competences (N=3,542) Response Formal New Skills Overcome Learning Self- Cultural Scale Qualificati Adversity 1 522 (15%) 129 (4%) 68 (2%) 2 392 (11%) 166 (5%) 78 (2%) 3 858 (24%) 648 (18%) 508 (14%) 4 913 (26%) 1171 (33%) 1130 (32%) 5 857 (24%) 1428 (40%) 1758 (50%) Note: 1= not important at all; 5= very important. Language 253 (7%) 169 (5%) 509 (14%) 934 (26%) 1677 Confidence 63 (2%) 114 (3%) 528 (15%) 1189 (34%) 1648 (47%) Adaptation 112 (3%) 146 (4%) 568 (16%) 1176 (33%) 1540 (43%) 12 The acquisition of human capital is explored: (a) temporally, (b) geographically by changes in the type of area of residence prior to and post migration, and (c) geographically based on the interaction between European region of origin/return and a person‟s migration destination. Variance approaches to compare the mean (linear) or median (non-linear) response were used to analyse the perceived acquisition of six competences by different population groups. The Acquisition of Competences in Relation to Duration and Number of Migrations Temporal influences on the acquisition of competencies amongst European returnees were explored by two distinct grouping structures. The first used a five-fold classification of the time a person had spent living abroad (“Time Abroad”): “6-12 months”, “1-1.5 years”, “1.5-3 years”, “3-6 years”, “6+ years”. The second measure, “Periods abroad”, comprised a simple three-fold classification structure of the number of migrations: “Once”, “Twice”, “Three or more times”. MANOVA tests initially explored the two-way grouping structure‟s significance, through simultaneous analysis of the six competencies. The tests revealed that a significant linear relationship existed between the interactions of the six competencies and the measures of temporality, that is the grouping structures of “Time Abroad” (P ≤ 0.05), “Periods Abroad” (P ≤ 0.05) and “Time x Periods Abroad” (P ≤ 0.05). The results indicate that temporality does inform the acquisition of competencies and skills amongst returned migrants. TABLE 2 explores these temporal influences in greater detail, through presenting the linear and non-linear forms of the ANOVA with post-hoc analysis. Detailed interpretations of the ANOVA results focus on group-wise comparisons which are deemed significant by both linear and non-linear approaches (two-tick validation, where P ≤ 0.05). The tests reveal that attainment of “Formal Qualifications” and “Self-Confidence” is influenced by migration duration, while number of migrations only impacts on “Self-Confidence”. Meanwhile, the interaction between time and periods abroad is shown to affect changes in “Language Skills” and “Cultural Adaptation”. A post-hoc analysis of the ANOVA was further conducted to identify where significant differences exist. The 13 result indicates that the acquisition of “Formal Qualifications” amongst return migrants that have lived abroad for a period of 3-6 years is on average 9.7% and 6.8% higher, compared to their respective counterparts that have lived abroad for 6-12 months and 1.5-3 years. A timeframe of 3-6 years appears to be the optimal time for a young person to obtain a range of formal qualifications in a foreign country, with the level of acquisition incrementally decreasing until it is no longer of significance after 6 years. This seems to suggest the completion of a typical bachelor degree or perhaps doctoral studies degree abroad, which lasts on average between 3 to 4 years. However, it may also indicate remaining in education and completing a master‟s degree after first degree graduation or remaining in the destination after graduation in order to obtain foreign work experience before returning to one‟s country of origin (i.e. Bijwaard and Wang 2016). In addition, spending more than 6 years abroad would appear to be detrimental to the “SelfConfidence” of returned migrants. On average, the “Self-Confidence” of return migrants that have lived more than 6 years abroad is 4.7% lower than for persons that have lived abroad for 6-12 months. “Self-Confidence” is not shown to deteriorate significantly with the length of stay for persons that have lived fewer than 6 years abroad. This finding is in line with previous studies suggesting that even very short experiences abroad increase one‟s self-confidence (i.e. Williams and Baláž 2005). How the number of migrations influences “Self-Confidence” could not be robustly explained in greater detail. The combined effect of total time and periods abroad is shown to affect changes in “Language Skills” and “Cultural Adaptation” for only a few groups. Returned migrants that lived abroad for 3-6 years across three or more destinations have “Language Skills” that are 10.6% greater than those that have lived abroad in one location for 1.5-3 years. The knowledge required for “Cultural Adaptation” is on average 8.4% higher amongst return migrants that have lived abroad for 3-6 years across three or more destinations, compared to those that have spent two periods living abroad for a total time of 6-12 months. This resonates with the finding by Main (2014) that „multiple migrants‟ who experienced a number of destinations, also reported the importance of the same two competences. This seems to suggest that living in more than two destinations abroad leads to the acquisition of language skills and greater cultural adaptation. This poses questions about whether there are diminishing returns from the total duration of migration, and whether these can be 14 moderated by moving to more than one destination, providing opportunities to engage with partly similar and different challenges and opportunities. Yet, the benefits of intensive mobility may be most valuable for young mobile individuals with no dependents. In contrast, for families, frequent moves, learning new languages and adapting to new cultures and educational systems may be perceived as a burden rather than an opportunity for championing lifelong learning (Ciobanu 2015). 15 TABLE 2: ANOVA with post-hoc analysis describing differences in competences’ acquisition in relation to the “time”, “periods” and “time x periods” that returned migrants spent abroad (N = 3,542) 2-Way ANOVA: P-Value ≤ 0.05 Outcome (1-5 Likert Scale) Time (Linear Non-Linear*) Periods| Abroad Time x Periods Abroad Formal ✔✔ Qualifications Language Skills Self-Confidence ✘✘ ✔✔ Abroad ✘✘ ✘✘ ✘✘ ✘✘ ✔✔ ✘✘ ANOVA Post-Hoc: Pairwise Analysis (Linear = Tukey HSD, Non-Linear = Dunn’s Test) Pairwise Comparison Means Lower Upper P-Value ≤ 0.05 (A) 3-6 years vs. + 9.7% Differen + 3.7% 95% CI + 15.6% 95% CI (Linear | Non✔✔ (B) 6-12 months (A) 3-6 years vs. + 6.8% + 0.2% + 13.4% ✔✔ (B) 1.5-3 (A) Threeyears or more vs. + 2.9% - 1.9% + 7.7% ✘✔ (B) Once (A) 3-6 years x Once vs. + 12.5% + 0.0% + 25.0% ✔✘ (B) 6-12 months x Once (A) 3-6 years x Three or more vs. + 13.0% + 1.6% + 24.4% ✔✔ (B) 6-12 months x Once (A) 3-6 years x Three or more vs. + 10.6% + 0.3% + 20.9% ✔✔ (B) 1.5-3 years (A) 6+ years vs.x Once - 4.7% - 8.8% - 0.7% ✔✘ (B) 6-12 months (A) 6+ years vs. - 4.8% - 9.2% - 0.4% ✔✘ (B) 1.5-3 years (A) 6+ years vs. - 5.7% - 10.3% - 1.1% ✔✘ (B) 3-6 years 16 TABLE 2: Continued … 2-Way ANOVA: P-Value ≤ 0.05 Time (Linear Non-Linear*) Periods| Abroad Time x Periods Abroad Abroad ANOVA Post-Hoc: Pairwise Analysis (Linear = Tukey HSD, Non-Linear = Dunn’s Test) Pairwise Comparison Means Lower Upper P-Value ≤ 0.05 (A) 6+ years x Two times vs. Differen - 10.8% 95% CI - 19.5% 95% CI - 2.0% (Linear | Non✔✘ (B) 6-12 months x Once (A) 6+ years x Two times vs. - 10.3% - 20.0% - 0.5% ✔✘ (B) 1.5-3 years x Once (A) 6+ years x Two times vs. - 11.2% - 21.7% - 0.7% ✔✘ (B) 3-6 years xx Two Oncetimes vs. (A) 6+ years - 10.4% - 20.0% - 0.8% ✔✘ (B) 1.5-3 yearsx xThree Two or times (A) 3-6 years more vs. + 13.5% + 2.1% + 25.0% ✔✘ (B) 6+ years Twovs. times (A) Three or xmore + 1.9% - 1.0% + 4.8% ✘✔ (B) Once (A) Three or more vs. + 2.2% - 1.0% + 5.5% ✘✔ (B) Twice (A) 3-6 years x Three or more vs. + 8.4% + 0.0% + 17.6% ✘✔ Outcome (1-5 Likert Scale) Cultural Adaptation ✘✘ ✘✔ ✔✘ (B) 6-12 months x Twice Note: * The nonparametric equivalent of the ANOVA was achieved through use of the “Scheirer-Ray-Hare” test; Time Abroad: “6-12 months”, “1-1.5 years”, “1.5-3 years”, “3-6 years”, “6+ years”; Periods Abroad: “Once”, “Twice”, “Three or more times”. 17 The Importance of Space in the Acquisition of Skills and Competences The second theme explored in this paper is spatiality and its influence on the acquisition of skills during international migration. The first exploration of spatial influences on the acquisition of competences focuses on the impact of the working and living environment prior to and post migration. This was measured by a traditional two-fold rural-urban classification with Urban defined as “Large City (Metropolitan Area)” and “Small-Medium Town” and Rural as “Village or Rural Area”. The “Pre-Migration Residence” describes the individuals living environment before international migration (known as Stage 1, or S1), and their “Current Residence” captures the environment that of the returned migrant in their country of origin at the time of the survey (known as Stage 3, or S3). This may be different to the initial point of return, but that information is not available and, arguably, is less important than current residence. Living areas were classified based on the perceptions of the survey respondent, and not in accordance to definitions based on economic function, population size or density. The MANOVA tests revealed a significant linear relationship exists between the interactions of the six competencies and the grouping structures at “S1” (P ≤ 0.05), “S3” (P ≤ 0.05) and “S1 x S3” (P ≤ 0.05) working-living environments. The results indicate that an urban-rural influence, prior to and after migration, is related to the acquisition of skills and competences. TABLE 3 explores these spatial influences in greater detail, through presenting the linear and non-linear forms of the ANOVA with post-hoc analysis. The tests reveal that the acquisition of “Formal Qualifications”, “New Skills” and “Language Skills” are significantly influenced by the type of pre-migration working-living environment (S1). The type of post-migration environment (S3) was shown to be significantly related to all six competencies. The interaction between the two rural/urban environments was only found to be related to “Formal Qualifications”, under the two-tick validation approach. Specifically, the post-hoc analysis indicates that individuals living in rural environments before migration acquire 11.8% fewer “Formal Qualifications” than their urban counterparts. One may therefore observe that being brought up in a rural location substantially decreases a person‟s chances of completing a foreign higher degree in later life. This may suggest that individuals from 18 urban backgrounds are more likely to be driven to go abroad by economic rather than educational reasons. Previous research has shown that young people in rural areas are more likely to be in lowpaid work and have insecure employment than their urban counterparts (Commission for Rural Communities 2012). According to a recent European study (Jentsch and Shucksmith 2017), stereotypes also play a role as they portray young people from rural areas as unreliable, with few skills and dependent on their parents. Meanwhile, individuals leaving an urban and returning to a rural location pick up 9.5% fewer “Formal Qualifications” than an urban leaver-returner. In other words, residence in a rural area either before or after migration is associated with reduced acquisition of skills compared to those who migrate from and return to urban areas. A similar story can be seen with the acquisition of “New Skills” and “Language Skills”, the respective uptake of which are 3.1% and 4.7% lower for individuals that lived in rural rather than urban environments prior to a migration episode. In addition, those returning to a rural area are expected to respectively have a 3.5%, 4.9%, and 4.4% lower uptake of “New Skills”, “Language Skills” and “Cultural Adaptation” than their urban counterparts. This provides systematic support for the argument that residence in rural areas is associated with lower levels of achievement in terms of skills and competences. This broadly accords with the existing fragmented evidence on the importance of urban-rural differences (Commission for Rural Communities 2012; Jentsch and Shucksmith 2017). 19 TABLE 3: ANOVA with post-hoc analysis describing differences in competences’ acquisition in relation to the type of “pre-migration” and “postmigration” living areas (N = 3,542) 2-Way ANOVA: P-Value ≤ 0.05 Outcome (1-5 Likert Scale) PreMigration Formal ✔✔ (Linear | Non-Linear*) Current Pre-Migration x Residence ✔✔ Qualifications New Skills Overcoming Adversity Language Skills ✔✔ ✔✘ ✘✘ ✔✔ ✔✔ ✔✔ ANOVA Post-Hoc: Pairwise Analysis (Linear = Tukey HSD, Non-Linear = Dunn’s Test) Pairwise Comparison Means Lower Upper P-Value ≤ 0.05 (A) Rural [S1] vs. - 11.8% Differen - 15.6% 95% CI - 8.0% 95% CI (Linear | Non✔✔ (B) Urban [S1] vs. (A) Rural [S3] - 5.6% - 9.4% - 1.7% ✔✔ (B) Urban [S3]x Urban [S3] vs. (A) Rural [S1] - 11.7% - 18.3% - 5.0% ✔✔ (B) Urban [S1] x Urban [S3] vs. (A) Rural [S3] - 9.5% - 16.4% - 2.6% ✔✔ (B) Urban [S1]xxRural Urban[S3] [S3]vs. (A) Rural [S1] - 13.3% - 20.2% - 6.4% ✔✔ (B) Urban [S1] vs. x Urban [S3] (A) Rural [S1] - 3.1% - 5.6% - 0.6% ✔✔ (B) Urban [S1] vs. (A) Rural [S3] - 2.5% - 5.1% + 0.0% ✔✔ (B) Urban [S3]x Rural [S3] vs. (A) Rural [S1] - 6.0% - 10.5% - 1.4% ✔✔ ✘✘ (B) Urban [S1] vs. x Urban [S3] (A) Rural [S3] - 3.1% - 5.2% - 1.0% ✔✔ (B) Urban [S3] (A) [S1] x Rural [S3] vs. - 3.8% - 7.6% + 0.0% ✔✘ ✘✘ (B) Urban [S1] vs. x Urban [S3] (A) Rural [S1] - 4.7% - 7.5% - 1.8% ✔✔ (B) Urban [S1] vs. (A) Rural [S3] - 4.9% - 7.7% - 2.0% ✔✔ Current ✘✔ ✔✘ (B) Urban [S3] 20 (A) Urban [S1] x Rural [S3] vs. - 5.9% - 11.1% - 0.7% ✔✘ (B) Urban [S1] x Urban [S3] TABLE 3: Continued … 2-Way ANOVA: P-Value ≤ 0.05 Outcome (1-5 Likert Scale) Language Skills Cultural Adaptation PreMigration ✔✔ ✔✘ (Linear | Non-Linear*) Current Pre-Migration x Residence ✔✔ ✔✔ Current ✘✘ ✘✘ ANOVA Post-Hoc: Pairwise Analysis (Linear = Tukey HSD, Non-Linear = Dunn’s Test) Pairwise Comparison Means Lower Upper P-Value ≤ 0.05 Differen - 8.0% 95% - 13.2% CI 95% - 2.9% CI (Linear | Non✔✔ (B) Urban [S1] vs. x Urban [S3] (A) Rural [S1] - 2.9% - 5.3% - 0.5% ✔✘ (B) Urban [S1] vs. (A) Rural [S3] - 4.4% - 6.8% - 2.0% ✔✔ (B) Urban [S3] (A) [S1] x Rural [S3] vs. - 6.4% - 10.7% - 2.1% ✔✘ (B) Urban [S1]xxRural Urban[S3] [S3]vs. (A) Rural [S1] - 5.1% - 9.4% - 0.8% ✔✘ (A) Rural [S1] x Rural [S3] vs. (B) Urban [S1] x Urban [S3] Note: * The nonparametric equivalent of the ANOVA was achieved through use of the “Scheirer-Ray-Hare” test; Stage 1 - Pre-Migration Residence [S1]: “Urban”, “Rural”, Stage 2 - Current Residence [S2]: “Urban”, “Rural”. 21 A European Macro-Regional Perspective on Skills Acquisition The second exploration of geographical influences on the acquisition of competences focuses on the migration story of Eastern and Southern European migrants. The YMOBILITY online panel survey collected information on returned migrants from two Eastern (Slovakia, Romania) and two Southern (Italy, Spain) European countries. The former are traditionally „sending‟ countries while the latter are „mixed migration‟ countries; being both on the sending and receiving end. Following the EuroVoc classification (2017) and its groupings of European sub-regions, for this analysis, one grouping structure defines the “European Region of Origin/Return Country” (known as Stage 1/3, or S1/3) in accordance to the following two-fold classification: Eastern Europe and Southern Europe. A second grouping structure defines the “European Region of Migration Destination” (known as Stage 2, or S2). This reflects the location where an individual has spent the most time living abroad in accordance to the following four-fold classification: Eastern Europe, Northern Europe, Southern Europe and Western Europe. The main destination can be any one of the EU28 countries, whereas the first grouping structure focused only on four countries of origin in Eastern and Southern Europe. The following analysis therefore compares perceptions of the extent to which skills and competences have been accrued by returned migrants (a) originating from different European macro regions, and (b) in relation to the macro region of Europe migrated to. The MANOVA tests revealed a significant linear relationship between the interactions of the six competencies and the grouping structures at “S1/S3: Country of Origin” (P ≤ 0.05), “S2: Main Destination Abroad” (P ≤ 0.05) and “S1/S3 x S2” (P ≤ 0.05). The results indicate that both country of origin and the main destination country influence the rate at which skills and competencies are collectively developed through international migration experience. We further explored these geographical influences in greater detail, through the linear and non-linear forms of the ANOVA with post-hoc analysisi. The tests reveal that all skills and competences, except “Self-Confidence”, are significantly influenced by the different groups of countries of origin (S1/S3). In contrast, only “Formal Qualifications” are seen not to be significantly influenced by the destination where an individual has spent the most time living abroad (S2). The post-hoc analysis indicates that migrants 22 originating from Southern Europe consider that they have acquired 13.8%, 7.8%, 13.0%, 4.6% and 10.9% more “Formal Qualifications”, “New Skills”, “Language Skills”, “Overcoming Adversity” and “Cultural Adaptation” competences from their experiences abroad, than migrants from Eastern European countries. These findings seem to confirm considerable research examining return experiences of Eastern European migrants which reveal that their diplomas and unique skills gained abroad carry less weight than personal connections through which labour market is accessed (i.e. White 2014; Lulle and Buzinska 2017). The focus is next shifted to the single effect of a migration destination on the acquisition of skills and competences. Immigrants to Western Europe respectively develop their “Overcoming Adversity”, “Language Skills” and “Cultural Adaptation” competencies to levels 4.8%, 30.6% and 5.7% above those of immigrants to Eastern Europe; the difference with respect to language skills is particularly marked. This points out to the importance of Western European countries and their role in acquiring „language capital‟ (Dustmann 1999). Fewer differences exist when comparing immigrants to Western and Southern Europe, with the only significant difference being a 3.8% higher uptake of “New Skills”. No significant differences were observed between the two traditional destination regions of Western and Northern Europe (P > 0.01). Immigrants to Northern Europe tended to have a 26.0% higher level of acquisition in “Language Skills” and a 5.7% greater increase in their “Cultural Adaptation” abilities, when compared to immigrants to Eastern Europe. No significant differences were observed between immigrants to Northern or Southern Europe (P > 0.05). The final section of the post-hoc analysis examines the combined effect of the country of origin and migration destination on skills and competencies (see TABLE 4). The optimal migration route(s) for developing the skills are identified in relation to the benchmark group of internal migration within Eastern Europe (N=149) – that is originating from, working abroad in, and returning to this region. This was selected as the benchmark group because it was significantly different for the largest number of migration routes. Returned migrants from Southern Europe that have lived in Western Europe, as well as Eastern Europeans that have lived in Southern Europe, appear to have the greatest overall acquisition of skills and competencies. This indicates quite a complex mapping of the geography of competence acquisition, with difference between those leaving the South and the East, 23 as well as the somewhat unexpected importance of East to South flows (i.e. Main 2014). No significant effects were recorded for the detailed migration pathways of Eastern or Southern Europeans that had lived in Northern Europe. TABLE 4: Post-hoc pairwise analysis describing the migration route effects on human capital development (N = 1,749) Outcome/Migration Route Relative Effect Overcoming Adversity (…… vs. East –> East –> East)  South –> West –> South (N = 668): + 11.0%  East –> South –> East (N = 146): + 8.6% Language Skills (…… vs. East –> East –> East)  East –> South –> East (N = 146): + 57.1%  South –> West –> South (N = 668): + 56.3%  South –> North –> South (N = 49): + 56.0%  South –> South –> South (N = 263): + 53.7%  East –> West –> East (N = 233): + 49.8% Self-Confidence (…… vs. East –> East –> East)  East –> South –> East (N=146): + 11.1%  South –> West –> South (N = 668): + 7.1%  South –> South –> South (N = 263): + 6.4% Cultural Adaptation (…… vs. East –> East –> East)  South –> North –> South (N = 49):  South –> West –> South (N = 668):  South –> South –> South (N = 263):  East –> South –> East (N = 146):  East –> West –> East (N = 233): + 26.7% + 20.9% + 18.5% + 16.6% + 9.8% 24 Note: The reported significant results of Tukey and Dunn tests are based on P ≤ 0.05 Internal migration within Eastern Europe used as a benchmark for comparison (N=149) Discussion and Conclusions Youth or young adult migration is one of the most striking and powerful social phenomena in the EU (King 2018). Although the underlying motives are diverse (Williams and Baláž 2005; King et al. 2016), these international sojourns provide opportunities for acquiring skills and competences. They have potential to transform the lives of returned migrants, and the economies of the countries and regions of return. The emerging literature in this field suggests that their experiences vary considerably, but while individual characteristics have been analysed in some depth, especially differences relating to pre-migration education and skills, there is still little systematic comparative research on the characteristics of the migration process itself, a gap that this paper has sought to address in relation to temporality and spatiality. The findings reveal that although the acquisition of formal qualifications as well as soft skills was highly valued by young European returnees, their experiences also varied in relation to the characteristics of the migration process. There are three main findings. Firstly, the acquisition of lifelong skills and competences is mediated by the temporality of the migration experience(s). The length or duration of migration is associated with the acquisition of formal qualifications and selfconfidence. Not surprisingly, the optimum time for acquiring formal qualifications (often involving university programmes) is between three and six years. In contrast, there are relatively weak associations between the duration of migration and the acquisition of other competences, suggesting that there are relatively steep learning curves while abroad. Indeed, there can even be a decline in the importance attached to the acquisition of some competences after a period of six years, which may be due to frustration at diminishing returns and flattening learning curves. However, a more nuanced picture is obtained if we consider the interaction between the length of the migration period and the number of migrations participated in. Developments of 25 language skills and cultural adaptation appear to be associated with the interaction of both duration and the number of migration sojourns, a finding confirming a previous qualitative study (Main 2014). A longer duration of three to six years, combined with multiple mobility experiences in three or more destinations, was most positively associated with the acquisition of competences. In addition to the length of time abroad, the extent to which the migrants have been exposed to different challenges in different countries also matters. These sequential challenges have provided opportunities to refine their new competences, and to utilise their accumulated expertise in learning to learn (Williams and Baláž 2008) which is itself a key competence in lifelong learning, employability and career development. These findings bring a different perspective to how human capital (Dustmann and Kirchkamp 2002; Dustmann and Weiss 2007) theories conceptualise the increasing return over time to investment in skills. Secondly, perceptions of the importance of the labour market competences acquired also vary spatially, being influenced by the country of origin of young Europeans. Gou (2010) notes that many migrants‟ prior learning and work experience can be devalued – particularly when moving from less to more developed countries - and consequently they experience downward social mobility, and reduced opportunities for lifelong learning. Southern European migrants seem to have the largest perceived gains from their international experiences, while acquiring formal qualifications and other new skills seems to be valued less by returnees to the Eastern regions of Europe, regardless of where they returned from. Even highly-qualified East European migrants experience challenges in terms of the recognition of their qualifications, leading to taking up jobs that offer few opportunities for learning (i.e. Johnston, Khattab and Manley 2015). An explanation can also be in migrants‟ low selfesteem which impacts on how they perceive and evaluate their own skills (Nowicka 2014). Interestingly however, their language skills gained in South Europe, notably Spanish and Italian, are highly valued, a finding rarely mentioned in the context of international mobility and learning. Perceptions are also shaped by labour market experiences after return. Social capital and personal networks still play an important part in the labour market in former Eastern bloc countries, suggesting that acquisition of a foreign degree or experience may be insufficient to obtain a good job, and that employers are sometimes reluctant to employ foreign-educated individuals (Barcevičius 26 2016). Within this broad picture, our analysis has highlighted how the acquisition of skills and competences varies depending on the exact pathway followed in terms of the combination of countries of origin and destination. There are structural effects at play here in the (assessment of) skill acquired, but they are not easily reducible to macro-economic differences. Perhaps the most interesting aspect of these pathway findings is that, for East Europeans, migration to Western Europe is not necessarily likely to lead to more valued acquisitions of skills and competences than migration to Southern Europe. This suggests that what is critical is engaging with the challenges and opportunities of migration per se, rather than the specific challenges and opportunities of particular countries. This suggests that Lyng‟s (2008) notion of edgework, learning to manage risks (of migration), plays an important role in the evaluation of some competences, and merits further exploration in future research. A third conclusion is that in terms of spatiality, urban-rural differences matter as well as national-level differences. While recent studies demonstrate that European migrants tend to return to less developed, rural areas (i.e. Martin and Radu 2012), our study suggests that residence in a rural area either before or after migration is associated with reduced acquisition of skills compared to those who migrate from and return to urban areas. This broadly accords with the limited evidence available on this issue (Jentsch and Shucksmith 2017), although our research also points to the importance of analysing the pathways undertaken and not only the final destination, with significant differences being observed between urban-urban, rural-rural, urban-rural and rural-urban pathways. This again points simultaneously to both the importance of structural influences, and the need to avoid oversimplifying these. Overall, the study confirms that international mobility does tend to increase the lifelong skills and competences of returned migrants, thereby enhancing their potential employability and career trajectories. However, the significance of the pre-migration characteristics and identities which shape learning processes in a new destination should not be underestimated (Morrice 2014). Discrimination and stereotyping still influence the extent to which migrants return to their human capital through opportunities and constraints (Williams 2006). This study highlights the importance of where you 27 come from and where you migrate to, as well as for how long and how often you are abroad, so that structural conditions still shape individual migration experiences in the intra-EU mobility zone. Finally, it is important to note some limitations of this study. First, we have analysed the perceived importance of the skills and competences acquired, rather than measurable objective outcomes. Moreover, these perceptions are likely to vary over time as migrants readjust to labour market conditions in their country of origin. Secondly, we analysed the acquisition of skills and competences rather than the resulting occupational outcomes, although the respondents‟ evaluation of the importance of these skills is likely to be shaped by their actual job market experiences. Thirdly, they may evaluate some of these skills and competences, such as self-confidence, in terms of personal development rather than their occupational utility (Palovic, Janta and Williams, this issue). Indeed, there is evidence that migration intentions are complex and include considerations other than occupational or material advancement (Williams et al. 2018). Fourthly, although we examined a relatively large data set, it still only applies to nine countries of origin and return, and both space and statistical requirements mean that the analysis at times has been limited to a smaller number of countries. 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