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This study proposes a novel way to examine self-selection on unobserved skills and applies it to a sample of young males seeking asylum in 2015/2016 in Germany. First, the degree of intergenerational mobility of these refugees is assessed, specifically their educational improvement in comparison to their parents’ level of education. Next, the esti- mates are compared with the level of educational mobility of similar-aged males in the refugees’ regions of origin. The idea is that this difference indicates the pattern of self-selection on unobserved skills such as grit and motivation. Our findings hint at positive selection on such unobserved skills among these young male refugees. Keywords: Immigrant selection, Asylum seekers, Human capital, Family background Reasoning in the economics of migration literature 1 Introduction suggests that migrants are a group of self-selected indi- Between 2014 and 2016 Europe, and in particular Germany, viduals. Self-selection influences the causes and eco - saw a rapid increase in asylum applications. According to nomic consequences of migration, in particular the Eurostat, in 2016 alone around 750,000 refugees relocated to labour market achievements of migrants (Borjas 1985; Germany. Such a significant influx of people has renewed Chiswick 1978). All else equal, higher skilled individuals public concerns about the integration of immigrants into may assimilate faster into the host country’s society com- society, even influencing voting outcomes in favour of anti- pared to lower skilled individuals. Hereby, the definition immigration parties (e.g. Dustman et al. 2017; Bratti et al. of skills is comprised of observable characteristics, such 2020). Apprehensions regarding refugees and migrants as education, as well as unobserved traits, such as grit, partly stem from cultural differences between migrants and motivation, perseverance or risk preferences. the society of the host country, and partly from the eco- The Roy-Model of income maximisation predicts that nomic burden they may impose on the host country pop- countries with more generous social insurance and ben- ulation (Dustmann and Frattini 2014; Fuest 2016, among efit systems might attract negatively selected migrants others). This latter issue is particularly relevant to refugees, who need more time to assimilate into the host country’s since they may begin contributing only in the medium or labour market (Borjas 1987, 1999). However, since refu- long term after their assimilation into the labour market is gees may differ from economic migrants in several ways, complete; and are often net beneficiaries for a period fol - lowing their arrival. In addition, the inflow of migrants may adversely affect the labour market opportunities of directly Henceforth, we will use the terms asylum seekers and refugees as synonyms. competing residents in the receiving countries (e.g. Borjas In Germany, for instance, asylum seekers are initially allocated to recep- and Monras 2017). tion centres where their basic needs are met and are later entitled to receive financial support up to the amount warranted to citizens by the social secu- rity system, once they move to private accommodations. The longer-term assimilation of immigrants in the host country can be understood as an intergenerational process where observed as well as unob- *Correspondence: firstname.lastname@example.org served skills of the first generation are transmitted to the second generation ZEW–Leibniz Centre for European Economic Research, Mannheim, of immigrants (Bönke and Neidhöfer 2018; van de Werfhorst and Heath Germany 2019; Zuccotti et al. 2017). © The Author(s) 2021. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http:// creat iveco mmons. org/ licen ses/ by/4. 0/. 8 Page 2 of 9 M. Hebsaker et al. which in turn may affect their economic assimilation, it unobserved component depends mainly on the trans- remains an open question whether and how these con- mission of personality traits such as motivation, grit, siderations apply to refugees. The scant existing inter - perseverance or the willingness to take risk in the family national evidence shows contrasting results. Refugees in (see Dohmen et al. 2012; Kosse and Pfeiffer 2012, among Sweden and the US have been shown to assimilate faster others). Hence, the novel idea is that the difference in than other migrants (Luik et al. 2018; Cortes 2004), while the degree of intergenerational mobility should indicate the evidence in Norway points to a slower rate of assimi- the pattern of self-selection on unobserved skills. lation for refugees (Bratsberg et al. 2014). As a conse- Our results show that the refugees in our sample dis- quence, a lack of information about the relative skill level play higher than average relative rates of intergenera- of current refugees makes it difficult to forecast their tional mobility, measured by the association between economic assimilation prospects within the destination their own years of schooling and the years of school- countries (Dustmann et al. 2017). Due to the nature of ing achieved by their parents. Additionally, we estimate their displacement–reasons for its occurrence are mostly the average degree of educational upward mobility, war, human rights violations or other fatal, unforeseen assessed by the probability of refugees to achieve more events–the migration decisions of refugees are presum- years of schooling than their parents. We find that refu - ably less based on economic considerations such as gees from Afghanistan, Iraq, and Sub-Saharan Africa income maximisation. Hence, the selection pattern of also display higher rates of absolute upward mobility refugees may work in two directions; refugees might be when compared to the same-aged male population in more positively or more negatively selected than other their respective home region. Given our interpretation migrants from comparable countries of origin. this finding should be a sign of positive selection on This study contributes to broaden our knowledge on unobservable skills for our sample of refugees. the skill selection of recently arrived refugees, taking The remainder of the paper is structured as follows: advantage of novel survey data for asylum seekers liv- Sect. 2 briefly summarises the literature on the inter - ing near the city of Heidelberg (see Lange and Pfeiffer generational persistence of education. Section 3 pro- 2019). The survey includes information on the refugees’ vides a detailed description of the data. Section 4 own education background and retrospective ques- presents and discusses our results. Section 5 concludes. tions about their parents’ education. Lange and Pfeiffer (2019) showed that, on average, the young male asylum seekers in this sample and their parents received more 2 Relative and absolute intergenerational mobility years of schooling compared to same-aged males from in education their country of origin. They thus seem to be a positively Education, as a proxy for human capital, is strongly selected group (relative to their country of origin) with determined by family background since education deci- respect to their amount of time in education. Guichard sions are shaped by parental preferences, the avail- (2020) confirms these findings for asylum seekers in Ger - ability of economic resources and credit constraints many originating from Iraq and Syria based on a repre- (Becker and Tomes 1979; Checchi et al. 2013). Hence, sentative survey, and finds a neutral pattern of selection parent–child-schooling correlations are strongly related for those that fled from Afghanistan. to other measures of social intergenerational mobility In this analysis our aim is to focus on the unobserved such as those based on income or occupation (Blanden skills of the sample of young male asylum seekers from 2013; Black and Devereux 2011). An established way to Lange and Pfeiffer (2019) and propose a novel way to measure the intergenerational mobility of education is measure them. First, we estimate the degree of inter- to estimate the following linear regression model: generational mobility of the refugees in our sample, O P S = α + βS + ε (1) specifically their educational improvement in compari - i i i son to their parents’ level of education. Then, we com - O P where S represent the offspring’s and S the parents’ pare our estimates with cross-country estimates on education in family i , measured in years of schooling. the level of educational mobility of similar-aged males The slope coefficient β measures the degree of inter- in the refugees’ regions of origin. In doing so we are generational persistence (see e.g. Black and Devereux able to disentangle the structural component of educa- 2011). The higher β , the stronger the association tional mobility caused by country level characteristics, between parents’ and children’s education within the such as the expansion of schooling or cultural factors. analysed sample. α is a constant, and ε an error term. At the same time we are able to keep the largely unob- The cross-country study by Hertz et al. (2007) applies served component influencing the relative improve - this framework and shows that education is more gen- ment of individuals with respect to their parents. This erationally-persistent in developing countries than in Intergenerational mobility and self‑selection on unobserved skills: New evidence Page 3 of 9 8 OECD countries. Furthermore, educational mobility is a lower mobility rate indicates that refugees in this group low in South America and Southeast Asia and rather are negatively self-selected. high in Scandinavian countries. Table S1 in Addi- In this application, we may face a limitation when tional file 1 reports some published estimates of inter- assessing intergenerational mobility using the estimated generational mobility for developed countries and for slope coefficient in Eq. (1): the slope coefficient β meas- countries in the geographic regions from which the ures the partial correlation between parents’ and chil- individuals in our sample of refugees originate. These dren’s years of schooling and, hence, is sensitive to each estimates indicate that intergenerational mobility is form of variation within a family from one generation to higher in Germany than in the regions of origin for the the next without making a distinction between whether refugees in our sample. it is an improvement or a deterioration. It is therefore The degree of educational mobility within a popula - insightful to also estimate an absolute measure of inter- tion is considered to be a summary measure, indicating generational upward mobility for our refugee sam- the persistence of human capital within families over ple, namely, the probability of children having a higher time. As such, it comprises different channels of the level of education than their parents, given that parents human capital production function and intergenerational are not in the highest educational category m (tertiary transmission into one single measure at the cost of los- education ): ing information about the strength of each component of O P P Pr(c > p) = Pr(S > S |S < m). (2) the relationship. In our analysis, we use the information i i i contained in the mobility estimates to examine the self- The higher this probability, the higher is the average selection of refugees on unobserved skills. Hence, we are educational upward mobility within the sample. This sec - interested in disentangling the structural component of ond indicator of intergenerational mobility, the probabil- educational mobility, caused by country level character- ity of upward mobility, should be even more insightful as istics such as educational expansions or cultural factors, a measure of self-selection with respect to the population while keeping the unobserved component. According to of origin, since the first indicator, namely the slope coeffi - our argumentation, this unobserved component is the cient, captures the degree of regression to the population one influencing the relative improvement of individu - mean among our sample. To provide a comprehensive als with respect to their parent’s education. It depends description of intergenerational mobility among young on personality traits and skills such as motivation, grit, male asylum seekers from different countries of origin, perseverance, or the willingness to take risk. Hence, it both will be reported. should be a suitable indicator of self-selection on unob- served skills. 3 Data We do so by comparing the intergenerational mobil- The sample of young male asylum seekers that we use ity of refugees in our sample with the average degree of stems from the “Real-world Laboratory Survey among intergenerational mobility of same-aged non-migrants in Asylum Seekers”, a novel survey data set of asylum seek- their regions of origin. We retrieve the mobility estimates ers who were part of the large influx to Germany in for the latter from the World Bank’s Global Database on recent years (see Lange and Pfeiffer 2019). The survey Intergenerational Mobility (GDIM; see Narayan et al. contains information on asylum seekers living in two 2018). A higher rate of intergenerational mobility among group accommodations close to the city of Heidelberg, in the subgroup of refugees with respect to their region of southern Germany. In cooperation with the administra- origin hints at positive skill selection for this group, while tion of these group accommodations and the local for- eigner’s administration offices, a scientific survey among the asylum seekers was conducted in August/Septem- ber 2016. Participation in the survey was on a voluntary basis and was open to all individuals over 18 living in Neidhöfer et al. (2018) show that in most Latin American countries educa- the accommodations. The computer-assisted interviews tional mobility has risen substantially for people born in the eighties in com- parison to their parents and grandparents. were undertaken by professional and native speaking Borjas et al. (2019) use the residuals from earnings regressions to meas- ure the self-selection on unobservable characteristics of Danish emigrants. Corneo and Neidhöfer (2019) measure the unobserved skill level of Italian migrants worldwide, via the probability an individual is either unemployed, or has a high occupational position in the destination country, given their The necessary years of schooling to be eligible for attending tertiary edu - level of education. These two methods for measuring unobserved skill selec - cation tracks vary between most sending countries (usually 12 or 13 regular tion are suitable for long-term migrants, but not applicable to this study, years of schooling to finish secondary education). We follow the official and since the refugees in our sample were interviewed shortly after arrival, and country specific UNESCO ISCED Educational Mappings from 2011. See thus most do not present any measurable labour market outcomes.http:// uis. unesco. org/ en/ isced- mappi ngs [latest view 03.06.2019]. 8 Page 4 of 9 M. Hebsaker et al. interviewers. The design of the survey aimed to cover the population of newly-arrived asylum seekers in Germany, main languages spoken by the respondents (Arabic, Dari/ it focuses on a crucial age interval for young male asylum Farsi, Tigrinya, Pashtu, English and German). seekers. The data set contains items related to the socio-eco - In the sample asylum seekers from Central Asia nomic status of the respondents before and after they account for a total share of 43.5 percent, while 36.5 left their home country. We rely on self-assessment by and 20 percent stem from the Middle East and Africa, the respondents in regard to their own and their par- respectively. Almost 41 per cent of the asylum seek- ents’ educational attainment and follow the literature in ers stem from Afghanistan, 17 percent from Syria and employing years of education as a proxy for human capi- 15.5 percent from Iraq. Gambians constitute the larg- tal (e.g. Hertz et al. 2007). Years of schooling is retrieved est group of African asylum seekers in our sample (10.2 from the answer to the following question: “How many percent). The remaining 16.8 percent stem from other years did you go to school? (If applicable, including uni- Asian and African countries. Table 1 shows the aver- versity)” for the asylum seeker, as well as his or her father age years of schooling for respondents (S ) , their fathers F M and mother. It is possible that, particularly among the ( S ), mothers ( S ) and the maximum value among both i i young refugees in our sample, some individuals might parents ( S ). We find an average of nine years of educa - not yet have completed their educational career. Brücker tion attained within the sample of asylum seekers. This et al. (2016) report that 26% of the refugees dropped out figure is in line with results of other studies investigating of school or interrupted their education due to conse- educational patterns of newly-arrived asylum seekers. quences of war and flight. Thus, education might be con - Buber-Ennser et al. (2016) for Austria, as well as Brücker sidered as a truncated variable and our intergenerational et al. (2016) for Germany, find comparable average years mobility estimates as a lower bound if individuals were to of schooling based on survey data. None of these studies continue their education in Germany. report the educational attainment of parents. The legally required minimum age to participate in Per the literature, we use the maximum level of educa- the survey was 18. To preserve homogeneity within the tion among both parents as a proxy for parental educa- sample we set the maximum age to 34, excluding the few tion in order to estimate intergenerational mobility. In female respondents (seven observations, less than 2% of our sample, we observe on average 5.97 years of educa- the sample), as well as asylum seekers from European tion for fathers and 3.85 years for mothers. Decile val- countries (eight observations). Hence, from an initial ues reveal a clustering pattern; particularly in the case of survey sample comprising 370 respondents, we end up mothers (57% with zero years of schooling) and fathers with a sample of 206 non-European, male asylum seek- (38.5% with zero years of schooling), but less so for the ers within the age interval of 18–34, with all necessary information available to measure the degree of inter- Brücker et al. (2016) report an average age of 31.2 years within their repre- generational mobility. The average age of respondents sentative survey among asylum seekers in Germany. A comparison of our data in our sample is 23.34 years, and the median age is 22. base to the IAB-BAMF-SOEP survey of refugees shows that the asylum seek- ers in our sample are on average not only younger, but spent also a shorter According to the Federal Office for Migration and Refu - amount of time in Germany (see Lange and Pfeiffer 2019). gees (BAMF 2017), 47 percent of the asylum seekers who Table S2 in the Online Appendix reports the complete list of countries applied for asylum in 2016 were in the age group 18–34 of origin, as well as their respective absolute and relative frequencies. Our and more than 70 percent of them were male. Hence, sample is not representative of the recent influx of asylum seekers to Ger - many with respect to the country of origin. According to BAMF (2017), although our sample is not representative of the entire refugees applying for asylum in Germany predominantly stem from Syria (37%), Afghanistan (18%) and Iraq (13%). Asylum seekers from Afghanistan 7 and Gambia are relatively overrepresented in our sample, while Syrian asy- Robustness checks performed on the age range 22–34 are included in the lum seekers seem to be relatively underrepresented. Online Appendix and confirm our main results. Additional file 1: Table S2 in the Online Appendix reports the complete While almost all survey respondents answered the question about their list of countries of origin, as well as their respective absolute and relative own education (92%), the response rates on fathers’ years of schooling (69%) frequencies. Our sample is not representative of the recent influx of asy - and mothers’ (72%) are lower. The presence of selective non-response on lum seekers to Germany with respect to the country of origin. According parental education could potentially bias the intergenerational persistence to BAMF (2017), refugees applying for asylum in Germany predominantly estimates. However, we find no indication for selective non-response in our stem from Syria (37%), Afghanistan (18%) and Iraq (13%). Asylum seekers sample; response behaviour on parental education is not associated with the from Afghanistan and Gambia are relatively overrepresented in our sample, average levels of education of individuals. The difference between the aver - while Syrian asylum seekers seem to be relatively underrepresented. age years of schooling of survey respondents that disclosed information about the education of their parents and those who did not is negligible (9.0 Other studies, such as Hertz et al. (2007), use the average among both vs. 8.98 years of schooling) and statistically undistinguishable from zero. parents instead. As shown by Neidhöfer et al. (2018), country rankings usu- Hence, if non-response on parental education is more likely when the par- ally do not change when applying one or the other variable for sufficiently ents have low levels of education, our estimates of intergenerational mobil- high and similar levels of spouse correlations among parents across coun- ity should not be upwardly biased. Additional file 1: Figure S1 in the Online tries. The correlation between father’s and mother’s years of schooling in Appendix shows the distribution of years of schooling of the refugees in our our sample is 0.65, ranging from 0.48 for refugees from Sub-Saharan Africa sample and their parents. to 0.74 for refugees from MENA countries. Intergenerational mobility and self‑selection on unobserved skills: New evidence Page 5 of 9 8 Table 1 Descriptive Statistics on O F M P F M Age S S S S = max S ,S i i i i i i Individual and Parental Years of Schooling Mean 9.00 5.97 3.85 6.48 23.34 Standard deviation 4.89 5.87 5.21 5.91 3.92 10th decile 0 0 0 0 19 20th decile 4 0 0 0 20 30th decile 7 0 0 0 20 40th decile 9 2 0 3 21 50th decile 11 5.5 0 6 22 60th decile 12 8 3 9 24 70th decile 12 10 6 12 26 80th decile 12 12 9 12 27 90th decile 14 14 12 14 29 O F M P S : Individual years of schooling of asylum seekers; S : Father’s years of schooling; S : Mother’s years of schooling; S : i i i i Years of schooling of the parent with the highest years of schooling among the two. Last column displays the average and distribution of the age of respondents. Source: Own estimates. Sample taken from `Real-world Laboratory Survey among Asylum Seekers’ individual’s level of educational attainment (13% have schooling is associated with an increase of about one zero years of schooling). third of a year of schooling for the next generation. In the subsequent columns we measure the association with father’s and mother’s years of schooling separately, and 4 Results then include both in the regression. The estimates do not 4.1 The intergenerational mobility of male asylum seekers change the overall pattern substantially and show that Table 2 shows the estimates for the β coefficient in the father’s education is a better predictor of children’s Eq. (1), further controlling for age and including coun- education than the education of the mother. As is evi- try of origin fixed effects. The dependent variable is the dent, the inclusion of age does not change the estimates years of schooling of the respondent. Column (1) and (2) significantly. show our main specifications, measuring parental human Additional file 1: Table S1 in the Online Appendix sur- capital by the maximum level of schooling among both veys part of the literature on intergenerational mobil- parents. We find a point estimate of 0.36 for the average ity estimates. We include the most comparable ones to degree of intergenerational persistence measured by the our estimates, relying on the same methodology, similar slope coefficient within our sample of young male asylum age cohorts and parent-son pairs (see Additional file 1: seekers. This means that an additional year of parental Table S1 for additional information on samples and Table 2 Slope coefficient of parent–child associations in years of schooling (1) (2) (3) (4) (5) (6) 0.35*** 0.36*** – – – – Schooling parents S (0.05) (0.05) – – 0.33*** – 0.27*** 0.27*** Schooling father S (0.05) (0.06) (0.06) – – – 0.29*** 0.11 0.11* Schooling mother S (0.05) (0.07) (0.07) Age – 0.21** - – -– 0.20** (0.08) (0.08) Constant 5.71*** 1.03 5.94*** 6.83*** 5.96*** 1.45 (0.63) (1.87) (0.61) (0.59) (0.61) (1.90) Adj. R 0.204 0.241 0.207 0.156 0.211 0.232 Sample comprises 206 individuals. Schooling Parents refers to the years of schooling of the parent with the highest years of schooling among the two. Schooling Father/Mother refers to the years of schooling. Regressions controlling for country of origin fixed effects. Robust standard errors in parentheses. Statistical significance level of the estimates: * for p < .10, ** for p < .05, and *** for p < .01. Source: Own estimates, sample taken from `Real-world Laboratory Survey among Asylum Seekers’ 8 Page 6 of 9 M. Hebsaker et al. descriptive statistics). The comparison shows that indi - countries are included in the GDIM. For Syria, since no viduals in our sample of refugees are, on average, more country specific estimates are available in the GDIM, we mobile than the population in most transitioning and built a synthetic comparison group based on the same developing countries, but less mobile than the population cultural and geographic region and income group the in most refugee reception countries, such as Germany. countries are ranked in (middle income countries). We then report the unweighted average among the countries belonging to this group. To provide further compari- 5 Comparison to region of origin son groups with sufficiently high numbers of observa - Lange and Pfeiffer (2019) uncovered a positive pattern tions, we form two further subgroups of refugees by their of selection on years of schooling for the refugees in our region of origin—MENA and Sub-Saharan Africa—and sample. In addition, their results show that the parents of compare the estimates with the unweighted average of the refugees in our sample have, on average, higher edu- all country estimates contained in the GDIM in these cational achievements than the population of parents in regions (see Table 3 notes). the country of origin. Hence, a priori no conclusions can Table 3 shows our estimates and the World Bank esti- be drawn from these findings about the degree of inter - mates. We report the regression-based index for rela- generational mobility of the asylum seekers in our sam- tive mobility, obtained by estimating Eq. (1) on our own ple; it might be higher, lower or the same in comparison sample and retrieved from the World Bank data for each to the average intergenerational mobility of their peers in country or region of origin, as β . The table also con - their country of origin. tains the predicted probability that individuals attained In this section we compare the intergenerational mobil- a higher level of education than their parents, given ity estimates for our sample of asylum seekers with the that neither of the parents is in the highest education overall level of intergenerational mobility in their coun- category. try or region of origin. For this purpose, we estimate the Iraq (32), Algeria (3); Sub-Saharan Africa: Eritrea (14), intergenerational mobility separately for subgroups of Gabon (1), Gambia (21), Niger (1), Nigeria (1). Regional refugees, clustered by their country or region of origin. composition in the GDIM: MENA: Djibouti, Egypt, Iran, We compare these assessments with estimates retrieved Iraq, Jordan, Lebanon, Morocco, Tunisia, West Bank and from the World Bank’s Global Database on Intergen- Gaza, Yemen; Sub-Saharan Africa: Benin, Burkina Faso, erational Mobility (GDIM, 2018; see also Narayan et al. Central African Republic, Comoros, Ethiopia, Guinea, 2018). Intergenerational persistence estimates retrieved Guinea-Bissau, Liberia, Madagascar, Mali, Mozambique, from the GDIM pertain to even-aged males belonging Malawi, Niger, Rwanda, Senegal, Sierra Leone, South to the most comparable birth cohort to the refugees in Sudan, Chad, Togo, Tanzania, Uganda. Source: Own esti- our sample, namely individuals born between 1980 and mates, sample taken from `Real-world Laboratory Survey 1989. The refugees in our sample were born between among Asylum Seekers’, and World Bank Global Data- 1982 and 1998, and are slightly younger than the cohort base on Intergenerational Mobility (GDIM). chosen from the GDIM for comparison purposes. The The average probability that individuals in the sample latter, however, is the last available cohort in the data- improve their level of education with respect to their par- base. Further reducing our sample of refugees limits ents is 0.6, which is consistent with the high degree of the power of the analysis due to the small sample size. relative mobility estimated within this sample. Excluding However, our intergenerational persistence estimates individuals younger than 22, the probability of upward obtained with a restricted sample of refugees aged 22–34, mobility is even higher and amounts to 0.67. Hence, the i.e. born between 1982 and 1994, are consistent with our main estimates (see Additional file 1: Tables S3 and S4 in the Online Appendix). For this subsample of on average older asylum seekers we observe even higher levels of The synthetic comparison group for Syria drawn from the GDIM includes the following countries: Djibouti, Egypt, Morocco, Tunisia, West Bank and educational upward mobility. Gaza, and Yemen. Country classifications are drawn from published World For both Afghanistan and Iraq, we have enough obser- Bank country classifications, online: https:// datah elpde sk. world bank. org/ vations to estimate the intergenerational mobility indices k nowl e dg e b a s e/ ar ti c le s/ 906519- wor ld- bank- c oun t r y - and- lend i ng - g r oup s. [10.04.2019]. within our sample and make a direct comparison, as the The other alternative would be to build the average by weighting coun- tries using their population size. However, this would lead to a bias towards the intergenerational persistence estimate of more populous countries The comparison data selected from the GDIM builds on large Microdata within the region. Instead, our aim is to evaluate the intergenerational retrieved from population surveys, which were conducted in the correspond- mobility of the asylum seekers in our sample with respect to the level of ing countries. Selected data is restricted to parent-son pairs given that the mobility of residents in their regions of origin as a benchmark. For this pur- child is born in the 1980′s birth cohort. The underlying population surveys pose, the unweighted average over all countries in the region yields a more were conducted between 2010 and 2016. informative measure. Intergenerational mobility and self‑selection on unobserved skills: New evidence Page 7 of 9 8 Table 3 Educational Mobility of Asylum Seekers in Comparison to their Region of Origin Country/ N Slope coefficient Absolute upward Region mobility β β GDIM Pr(c > p) Pr(c > p) GDIM Afghanistan 84 0.42 0.54 0.53 0.36 (0.09) (0.06) (0.24–0.60) (0.41–0.64) Syria 35 0.23 0.33 0.62 0.66 (0.12) [0.21–0.48] (0.10) [0.46–0.77] (0.00–0.45) (0.45–0.80) Iraq 32 0.31 0.45 0.54 0.45 (0.11) (0.10) (0.10–0.52) (0.34–0.74) Fig. 1 Educational Mobility of Asylum Seekers in Comparison to their MENA 78 0.25 0.36 0.59 0.64 Region of Origin. Notes: Figure shows the intergenerational mobility (0.08) [0.21–0.55] (0.06) [0.45–0.77] estimates for our sample of refugees and the World Bank estimates (0.10–0.40) (0.46–0.71) of the country or region of origin. β is the slope coefficient retrieved Sub-Saharan 38 0.45 0.52 0.74 0.35 from the estimates of Eq. (1). Pr(c > p) is the probability of children (0.10) [0.23–0.78] (0.07) [0.13–0.64] attaining higher education than their parents, given that the parents (0.26–0.64) (0.61–0.88) are not in the highest educational category (tertiary education). In Total Sample 206 0.35 – 0.60 – the graph, higher values mean higher intergenerational mobility (0.05) (0.04) in education. For more details on the estimates see Table 3. Source: Estimates pertain to the respective subgroups of young male refugees in our Own estimates, sample taken from `Real-world Laboratory Survey sample by their country or region of origin. β is the slope coefficient retrieved among Asylum Seekers’, and World Bank Global Database on from the estimates of Eq. (1). Pr(c > p) is the probability an individual has a Intergenerational Mobility (GDIM) higher level of education than their parents, given the parents are not in the highest category (tertiary education). Below our estimates in parentheses are the bootstrapped standard errors and 95% confidence intervals obtained with 1000 replications. GDIM: World Bank estimates retrieved from the GDIM for males of the 1980′s birth cohort. Point estimates shown for single countries, 6 Conclusions while average values for synthetic control groups include the range [min–max] In this study we analysed the self-selection of a sample in brackets. N shows the number of observations within the subgroup. Reginal of recently arrived male asylum seekers near the city of composition in our sample: MENA: State of Palestine (6 observations), Syria (35), Iran (2) Heidelberg based on a novel method. Previously, Lange and Pfeiffer (2019) showed that these young male asy - lum seekers are positively selected on observed years regression-based estimate for the sample of young male of schooling compared to their country of origin. To refugees is not driven by a downward mobility pattern. assess the degree of self-selection on unobserved char- Figure 1 visualises the difference between the degree of acteristics for these young male refugees, this study intergenerational mobility of male asylum seekers meas- measured their degree of intergenerational mobility ure in our sample and the World Bank estimates for com- and compared it to the average for comparable individ- parable peers in the country or region of origin. Here, for uals in their region of origin. We found that the refu- reason of simplification, intergenerational mobility meas - gees in our sample display, on average, a higher degree ured by the slope coefficient is displayed as 1 − β. of intergenerational mobility than a same-aged refer- The estimates show that the refugees in our sample dis - ence group in their country of origin. In conclusion, the play consistently higher rates of intergenerational mobil- findings indicate that the asylum seekers in our sample ity than the average for their respective country or region presumably are likely not a negatively, but a positively of origin; with the exception of refugees from Syria and selected group in comparison to the resident popula- the MENA region, whose upward mobility rate is simi- tion in their regions of origin. lar to the average rate of comparable individuals in their Our sample covers young male refugees living in two region of origin. For Syria and the MENA region the set group accommodations in a German municipality. This of countries in our sample differs from the ones included group of young male asylum seekers forms a major com- in the World Bank data, and hence may lead to imprecise ponent of refugees in Germany, and the findings should results regarding the comparison of these two groups. therefore be of particular importance. The quota-based Furthermore, because of our small sample size and since and random allocation of refugees among the German the GDIM does not provide standard errors of the point Federal States and municipalities may support the exter- estimates, the validity of statistical tests for differences nal validity of these results, although this needs further between these estimates remains limited. 8 Page 8 of 9 M. Hebsaker et al. Authors’ contributions confirmation with larger datasets. Because of the rela - The authors contributed equally to the analysis and the writing of the article. tively small sample size, the analysis has only limited sta- All authors read and approved the final manuscript. tistical power. Although our sample and estimates should Funding be comparable with the World Bank estimates, to some This study was funded by Ministry of Science, Research and the Arts of Baden- degree, uncertainty persists. The measurement of educa - Württemberg under grant number 8809–12/206/1. tional achievement in our data is the years of schooling Availability of data and materials as indicated by the respondents, while the World Bank The data have been collected by the authors during a research project which analysis uses the imputed regular years of schooling, is a part of “Real-World Laboratory: Asylum Seekers in the Rhine-Neckar- based on the educational degree obtained as indicated by Region” and can be accessed onsite at the ZEW—Leibniz Centre for European Economic Research in Mannheim. the respondents. Measurement error might challenge the comparison of estimates. Furthermore, it goes beyond Declarations the scope of this work to evaluate the relative skill level, and associated integration prospects, of certain refugee Competing interests groups in comparison to each other. The authors declare that they have no competing interests. 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