# Heterogeneity or consistency across life domains? An analysis of disparities between second-generation migrants and the Swedish majority population

Rosa Weber, Louisa Vogiazides

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Rosa Weber, Louisa Vogiazides. Heterogeneity or consistency across life domains? An analysis of disparities between second-generation migrants and the Swedish majority population. Research in Social Stratification and Mobility, 2023, 83, pp.100744. 10.1016/j.rssm.2022.100744. hal-03899393

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# Heterogeneity or consistency across life domains? An analysis of disparities between second-generation migrants and the Swedish majority population

Rosa Weber<sup>a, b, *, 1</sup>, Louisa Vogiazides<sup>c</sup>

<figure><img src="image_2.png" /></figure>

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## ARTICLE INFO

### Keywords:

Attainment

Second-generation migrants

Integration

Socioeconomic background

Register data

## ABSTRACT

Migrant integration is theoretically conceived as a multidimensional process where integration in one life domain does not necessarily imply integration in another domain. An expanding literature analyses several aspects of the lives of migrants and their children. However, to date research has mainly assessed how attainment in one life domain influences attainment in another domain. This study analyses the extent to which attainment across multiple life domains–socioeconomic, social and residential–coincides among second-generation migrants. Using Swedish register data, we compare 10,450 children of migrants from six regions of origin, who were aged 30–40 in 2015, to individuals born in Sweden with two Swedish-born parents. Multigenerational linkages moreover allow us to control for parental socioeconomic status as well as residential characteristics when growing up. Our analyses reveal considerable disparities in social and residential outcomes between second-generation migrants and the Swedish majority group, as well as across origin groups. Differences in socioeconomic attainment are comparatively small once we account for parental characteristics and residential background. Second-generation Turkish and Middle Eastern migrants differ in terms of their social and residential outcomes when compared to the Swedish majority group, but have commensurate socioeconomic attainment. In contrast, we find overall consistency across domains for Polish, ex-Yugoslav and Latin American second-generation migrants. Our findings underline the importance of studying outcomes in multiple domains in order to gain a more comprehensive understanding of the life situation of second-generation migrants.

## 1. Introduction

A growing body of research has studied various aspects of the lives of migrants' descendants: education (Brinbaum & Guéngard, 2013; Crul, 2013; Engzell, 2019; Hillmert, 2013), employment and earnings (Algan et al., 2010; Hermansen, 2013, 2016; Maskileyson et al., 2021), intermarriage (Kalmijn & van Tubergen, 2006; Lichter et al., 2011; Smith et al., 2012; Tegunimataka, 2021), and the residential situation (de Valk & Willaert, 2012; Edgar, 2014; Hermansen et al., 2022; Skovgaard Nielsen, 2016). The literature shows that in many countries, the children of migrants tend to be more similar to the majority population than first-generation migrants (Drouhot & Nee, 2019), though there remain notable differences in outcomes between second-generation migrants and the majority group, particularly for some origin groups (Kelly & Maharaj, 2019; Waters & Jimenez, 2005; Zhou & Gonzales, 2019).

Despite integration being theorised as a multidimensional process (Drouhot & Nee, 2019; Gordon, 1964; Jonsson et al., 2018), research about first- and second-generation migrants tends to focus on a single life domain (Engzell, 2019; Heath et al., 2008; Jonsson & Rudolphi, 2011). Studies usually use variables from other life domains as independent variables to explain the dependent variable from the domain of interest. For instance, intermarriage is used to predict labour market outcomes (Dribe & Nystedt, 2015; Furtado & Theodoropoulos, 2010) or neighbourhood characteristics (Macpherson & Strömgren, 2013; Vogiazides & Chihaya, 2020). At the same time, other studies analyse how labour market or residential trajectories relate to the likelihood of intermarriage (Kalmijn & van Tubergen, 2006; Muttarak & Heath, 2010), suggesting that these processes are difficult to disentangle. This also indicates that it is important to study outcomes across multiple life domains to gain a deeper understanding of disparities between migrants

<footnote><sup>a</sup> Department of Sociology, Stockholm University, Sweden</footnote>

<footnote><sup>b</sup> Institut National d'Études Démographiques, Paris, France</footnote>

<footnote><sup>c</sup> Department of Human Geography, Stockholm University, Sweden</footnote>

<footnote>* Corresponding author at: Department of Sociology, Stockholm University, 106 91 Stockholm, Sweden.
E-mail address: rosa.weber@sociology.su.se (R. Weber).</footnote>

<footnote n="1">¹ ORCID ID: https://orcid.org/0000-0001-8422-7023</footnote>
<figure><img src="image_3.png" /><figcaption>Fig. 1. Study population and design.</figcaption></figure>

and the majority population. Indeed, inequalities in one domain do not necessarily imply inequalities in another domain. Migrants may integrate into the labour market but prefer marrying a co-ethnic spouse or living in a migrant-dense neighbourhood (White & Glick, 2009). Alternatively, they may have obtained a high level of education, but find themselves in precarious working relationships due to employer discrimination (Zuccotti & Platt, 2019). Research focusing on a single domain thus runs the risk of providing an incomplete picture of migrants' life situation. Research that addresses multiple life domains often does so by reviewing separate empirical studies (Drouhot & Nee, 2019; Waters & Jimenez, 2005; White & Glick, 2009; Zhou & Gonzales, 2019). However, a growing number of studies attempt to simultaneously analyse several life domains (Fajth & Lessard-Phillips, 2022; Heath & Schneider, 2021; Lessard-Phillips, 2017; Telles & Oritz, 2009; Wallace et al., 2022; Zhou & Xiong, 2005).

The present study seeks to increase our understanding of the experiences of migrants' descendants, by analysing the outcomes of second-generation migrants in Sweden across three life domains. Empirically, we assess the likelihood that second-generation migrants resemble the majority group in terms of their socioeconomic, social and residential attainment. We use Swedish register data to study socioeconomic

outcomes measured by educational attainment, employment and disposable income, social outcomes measured by intermarriage and the ethnic composition at the workplace, and residential outcomes measured by the ethnic composition and level of deprivation of the neighbourhood of residence, as well as homeownership. We focus on individuals from the birth cohort 1975–85 and observe their outcomes in 2015, when they were between 30 and 40 years of age. Second-generation migrants are individuals born in Sweden with both parents born abroad, whose outcomes we compare to individuals born in Sweden with two Swedish-born parents. We account for the socioeconomic and residential contexts in which individuals grew up, and compare the educational attainment and employment rate of second-generation migrants with that of their (first-generation) parents at a similar age. Our analyses differentiate between six origin countries/regions: Finland, Poland, ex-Yugoslavia, Turkey, Middle East and Latin America.

Studying second-generation migrants in Sweden is of particular interest given that an increasing proportion of the population has a foreign background. In 2021, about 6% of the Swedish-born population had two foreign-born parents (Statistics Sweden, 2021). Children of migrants are also an increasingly diverse group. In 1990, adult second-generation migrants were principally of European origin. They consisted of

<table><caption>**Table 1**

Descriptive results for second-generation migrants' socioeconomic, social and residential attainment in 2015.</caption><thead><tr><th rowspan="2"></th><th rowspan="2">Swedish<br/>majority group</th><th rowspan="2">All second-<br/>generation<br/>migrants</th><th colspan="6">Second-generation migrants by region of origin</th><th rowspan="2">Total</th></tr><tr><th>Finland</th><th>Poland</th><th>ex-Yugoslavia</th><th>Turkey</th><th>Middle East</th><th>Latin America</th></tr></thead><tbody><tr><td><strong>Socioeconomic outcomes</strong></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Educational attainment</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Compulsory educ.</td><td>7</td><td>16</td><td>16</td><td>7</td><td>14</td><td>19</td><td>13</td><td>12</td><td>7</td></tr><tr><td>Upper secondary educ.</td><td>47</td><td>49</td><td>54</td><td>38</td><td>53</td><td>49</td><td>47</td><td>50</td><td>47</td></tr><tr><td>Tertiary educ.</td><td>46</td><td>34</td><td>29</td><td>54</td><td>32</td><td>30</td><td>39</td><td>36</td><td>46</td></tr><tr><td>Unknown educ.</td><td>1</td><td>1</td><td>1</td><td>1</td><td>1</td><td>1</td><td>1</td><td>2</td><td>1</td></tr><tr><td>Labour market outcomes</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Employed</td><td>93</td><td>88</td><td>88</td><td>86</td><td>87</td><td>89</td><td>87</td><td>86</td><td>93</td></tr><tr><td>Median disposable income<br/>(in 100 SEK)</td><td>2 721</td><td>2 517</td><td>2 537</td><td>2 571</td><td>2 570</td><td>2 565</td><td>2 558</td><td>2 315</td><td>2 719</td></tr><tr><td><strong>Social outcomes</strong></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Intermarriage</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Swedish spouse</td><td>49</td><td>15</td><td>32</td><td>22</td><td>15</td><td>6</td><td>9</td><td>18</td><td>49</td></tr><tr><td>Co-ethnic spouse</td><td>N.A.</td><td>21</td><td>10</td><td>5</td><td>28</td><td>34</td><td>23</td><td>11</td><td>1</td></tr><tr><td>Other ethnic spouse</td><td>10</td><td>13</td><td>7</td><td>8</td><td>8</td><td>18</td><td>15</td><td>12</td><td>10</td></tr><tr><td>Not married</td><td>40</td><td>51</td><td>51</td><td>65</td><td>49</td><td>43</td><td>53</td><td>60</td><td>40</td></tr><tr><td>Share of migrants in workplace<br/>(median)</td><td>22</td><td>34</td><td>32</td><td>32</td><td>32</td><td>42</td><td>36</td><td>33</td><td>22</td></tr><tr><td><strong>Residential outcomes</strong></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Vulnerable neighbourhood</td><td>1</td><td>13</td><td>6</td><td>6</td><td>8</td><td>19</td><td>14</td><td>11</td><td>1</td></tr><tr><td>Share of migrants in neighbourhood<br/>(median)</td><td>22</td><td>39</td><td>31</td><td>32</td><td>36</td><td>47</td><td>42</td><td>39</td><td>22</td></tr><tr><td>Homeowner</td><td>77</td><td>61</td><td>62</td><td>62</td><td>62</td><td>68</td><td>60</td><td>45</td><td>77</td></tr><tr><td>N</td><td>807 067</td><td>10 450</td><td>2 254</td><td>733</td><td>569</td><td>3 583</td><td>1 627</td><td>1 684</td><td>817 517</td></tr></tbody></table>

Notes. Within origin-group percentages are presented.
<table><caption>**Table 2**
Descriptive results of mothers' and fathers' socioeconomic status and the share of co-ethnics in the neighbourhood in 1990.</caption><thead><tr><th rowspan="2">Mothers' characteristics</th><th rowspan="2">Swedish majority group</th><th rowspan="2">All second-generation migrants</th><th colspan="4">Second-generation migrants by region of origin</th><th rowspan="2">Latin America</th><th rowspan="2">Total</th></tr><tr><th>Finland</th><th>Poland</th><th>ex-Yugoslavia</th><th>Turkey</th></tr></thead><tbody><tr><td>Educational attainment</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Compulsory educ.</td><td>23</td><td>50</td><td>38</td><td>7</td><td>52</td><td>75</td><td>49</td><td>29</td><td>23</td></tr><tr><td>Upper secondary educ.</td><td>51</td><td>34</td><td>46</td><td>56</td><td>36</td><td>14</td><td>35</td><td>48</td><td>51</td></tr><tr><td>Tertiary educ.</td><td>26</td><td>10</td><td>13</td><td>31</td><td>6</td><td>1</td><td>10</td><td>19</td><td>26</td></tr><tr><td>Unknown educ.</td><td>N.A.</td><td>6</td><td>3</td><td>6</td><td>6</td><td>10</td><td>5</td><td>4</td><td>N.A.</td></tr><tr><td>Labour market outcomes</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Employed</td><td>94</td><td>76</td><td>90</td><td>86</td><td>82</td><td>61</td><td>71</td><td>90</td><td>94</td></tr><tr><td>Residential outcome</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Share of co-ethnics in neighbourhood (median)</td><td>N.A.</td><td>5</td><td>7</td><td>1</td><td>2</td><td>7</td><td>6</td><td>3</td><td>N.A.</td></tr><tr><td>N mothers</td><td>807 067</td><td>10 450</td><td>2 254</td><td>733</td><td>569</td><td>3 583</td><td>1 627</td><td>1 684</td><td>817 517</td></tr><tr><td>Fathers' characteristics</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Educational attainment</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Compulsory educ.</td><td>29</td><td>40</td><td>40</td><td>8</td><td>45</td><td>59</td><td>37</td><td>18</td><td>29</td></tr><tr><td>Upper secondary educ.</td><td>50</td><td>41</td><td>44</td><td>56</td><td>41</td><td>29</td><td>40</td><td>59</td><td>50</td></tr><tr><td>Tertiary educ.</td><td>21</td><td>11</td><td>9</td><td>31</td><td>4</td><td>3</td><td>17</td><td>18</td><td>21</td></tr><tr><td>Unknown educ.</td><td>N.A.</td><td>7</td><td>7</td><td>6</td><td>11</td><td>9</td><td>6</td><td>5</td><td>1</td></tr><tr><td>Labour market outcomes</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Employed</td><td>97</td><td>86</td><td>87</td><td>86</td><td>86</td><td>82</td><td>84</td><td>92</td><td>97</td></tr><tr><td>N fathers</td><td>807 067</td><td>10 450</td><td>2 254</td><td>733</td><td>569</td><td>3 583</td><td>1 627</td><td>1 684</td><td>817 517</td></tr></tbody></table>

Notes. Within origin-group percentages are presented.

children of WWII refugees from Germany, other Nordic countries and the Baltics, or were descendants of labour migrants who came in the 1950s and 1960s, predominantly from Finland, Italy, Greece, Turkey and Yugoslavia (Westin, 2003). A quarter of a century later, a substantial proportion of the second-generation migrants originated from more geographically and culturally distant countries. In 2015, the group comprised predominantly children of refugees who arrived in Sweden from the 1970s onwards to flee persecution and conflict in Chile, Turkey, Iran and Lebanon among others. The diversification of the second-generation is thus a reflection of the growing variety in migration flows to Sweden.

In the next sections, we review the relevant theories and previous literature on the attainment of second-generation migrants. Then, we describe our data and methods and present the empirical findings. We conclude with a summary of the results and a consideration of the theoretical implications.

## 2. Theorising integration pathways of second-generation migrants

Integration can be defined as the process through which migrants and the majority group gradually converge and become more similar. With roots in the Chicago School writings, the *classical assimilation theory* developed by Gordon (1964) envisaged a process unfolding in several stages and across multiple dimensions, including acculturation (i.e. language acquisition and adoption of values and norms), structural assimilation (i.e. the entry of migrants into the social cliques and institutions of the receiving society) and marital assimilation (i.e. intermarriage). More recently, two additional dimensions of integration have been emphasised: socioeconomic and residential attainment (Alba & Nee, 1997; Massey, 1985).

The classical assimilation theory describes integration as a process that takes place across generations and assumes that migrants' descendants resemble the majority group to a greater extent than first-generation migrants. It further envisions a uniform pattern of convergence across life domains and migrant groups (Gans, 1974; Park & Burgess, 1921; Sandberg, 1974; Warner & Srole, 1945). The *neo-assimilation theory* developed in the 1990s posits that progress across different dimensions of integration can occur at a different pace for different migrant groups, though it hypothesises a general co-occurrence across dimensions (Alba & Nee, 1997, 2003).

Given the increased diversity of immigration flows in the US, the view of a linear and unidirectional path into mainstream American society for all migrants was put into question. Alejandro Portes and his colleagues proposed the *segmented assimilation theory* which postulates that, as the American society has become stratified, different 'segments' of society are available for migrants and their descendants to integrate in (Portes & Rumbaut, 2001; Portes & Zhou, 1993; Portes et al., 2008). The theory highlights three distinct paths of adaptation. First, adaptation can occur upward into the middle-class, as suggested by the classical assimilation theory. Second, adaptation can go downward into the lower class, leading to persistent disadvantages. Third, migrants can improve their socioeconomic position while deliberately retaining their cultural and ethnic identity.<fnref n="2" />

Segmented assimilation thus highlights the complexity and diversity of integration processes. It assumes that migrant groups will follow

<footnote n="2">² The segmented assimilation theory has been criticised for neglecting the fact that the majority group, in which migrants are supposed to integrate, is itself changing. If integration is conceived as a mutual process whereby migrants and the majority group become increasingly similar over time and across generations, it becomes difficult to identify what constitutes upward and downward adaptation pathways (Alba & Nee, 2003; Thomson & Crul, 2007). Still, it is important to understand that integration may take different forms and that it is influenced by the social settings in which migrants are embedded.</footnote>
<figure><img src="image_4.png" /><figcaption>**Fig. 2.** Average marginal effects from logistic regressions on socioeconomic attainment. *Notes*. All origin groups are compared to the Swedish majority group, whose outcomes are indicated by the horizontal line. The baseline model (circles) differentiates between region-of-origin groups. The model that controls for parental SES (diamonds) includes the variables: parental educational attainment, parental employment status and mother's age in 1990. The model that controls for individual characteristics (triangles) additionally includes gender, age, educational attainment, municipality of residence and average income in the neighbourhood of residence in 2015. Corresponding results are provided in Tables A2–A4 in the Appendix.</figcaption></figure>

different pathways and that migrants may converge with the majority group in some areas but not in others (White & Glick, 2009). The theory posits that the segmented character of assimilation is the result of an interaction between individuals' human capital, parental socioeconomic status, the characteristics of the co-ethnic community and the policies, values and prejudice in the receiving society (Portes & Zhou, 1993; Zhou & Gonzales, 2019). A lack of convergence in a certain life domain may then stem from the presence of discriminatory practices, notably in the housing and labour markets (Auspurg et al., 2019; Zschirnt & Ruedin, 2016). Yet it can also be a result of migrants' deliberate choice. For instance, migrants may prefer to reside in neighbourhoods with a high concentration of co-ethnics even when they can afford a residence in wealthier and majority-dominated areas (White & Glick, 2009). This is because co-ethnic concentration can imply certain advantages, such as the presence of cultural institutions and shops, employment opportunities and mutual support (Bolt, Özüekren, & Phillips, 2010). Similarly, based on the principle of homophily (McPherson et al., 2001; Smith et al., 2014), individuals may have a preference for marrying a co-ethnic spouse.

In the North American context, people of non-European origin are considered more vulnerable to following a downward integration path. While race is a disputed topic in Europe, religion and especially Islamic beliefs have attracted considerable attention in shaping distinct adaptation pathways in Europe (Arai et al., 2016; Drouhot & Nee, 2019). Beyond religion, cultural distance to the host country is similarly related to different challenges, both with regard to how migrants are received in the host country and the extent to which their norms and habits differ from those of the majority population at arrival in the country (Thomson & Crul, 2007).

The interlinkages between different dimensions of integration have been a focus of theoretical discussions since the 1960s. In his classical assimilation theory, Gordon (1964) envisaged that structural assimilation would lead to an increase in intermarriage and a decline of prejudice among the majority population. More recently, the role of resourceful contacts has been emphasised by social network theory (Aguilera & Massey, 2003; DiMaggio & Garip, 2011; Lin, 2001). Research finds that contact with the majority group promotes migrants' socioeconomic outcomes (Kanas et al., 2012; Lancee, 2010). This can also strengthen positive attitudes in the host society, as argued by intergroup contact theory (Pettigrew & Tropp, 2006; Pettigrew et al., 2011). Likewise, having a native-born spouse has been related to migrants' socioeconomic attainment (Dribe & Nystedt, 2015; Furtado & Theodoropoulos, 2010). However, when migrant groups are large and unified, this can induce feelings of threat among the majority population, as ethnic competition theory suggests (Smith et al., 2016). Co-ethnic contacts may then act as a safety network. Depending on the resourcefulness of co-ethnic communities, this can promote or inhibit migrants' outcomes (Andersson Joona & Wadensjö, 2012; Klinthäll & Urban, 2016).

Similarly, there is substantial debate about the interlinkages between residential attainment and other dimensions. According to the spatial assimilation theory formulated by Massey (1985), socioeconomic mobility and cultural integration are the main drivers of residential improvement. In contrast, the literature on neighbourhood effects conceptualises that the relationship works in the opposite direction, i.e. that residence in a socioeconomically deprived neighbourhood can have negative consequences for individuals' socioeconomic prospects (Musterd et al., 2008). For instance, a recent study from Sweden found that neighbourhood characteristics largely explain the intergenerational income mobility gap between individuals with foreign- and native-born parents (Bratu & Bolotnyy, 2022). There are also discussions regarding the temporal order of residential and social integration. One perspective assumes that residential improvement precedes intermarriage, as living in majority-dense areas gives migrants the opportunity to meet a partner from the majority group (Massey, 1985). Another perspective considers that it is rather intermarriage that facilitates
<caption>**Table 3**</caption>

Average marginal effects from logistic regressions on the socioeconomic attainment of second-generation migrants in 2015.

<table><thead><tr><th rowspan="2">Region of origin (ref. Finland)</th><th colspan="2">Tertiary education</th><th colspan="2">Employed</th><th colspan="2">Top income quartile</th></tr></thead><tbody><tr><td>Poland</td><td>0.062 **</td><td>(0.021)</td><td>-0.037 *</td><td>(0.018)</td><td>0.017</td><td>(0.017)</td></tr><tr><td>ex-Yugoslavia</td><td>0.012</td><td>(0.022)</td><td>0.004</td><td>(0.015)</td><td>0.030</td><td>(0.019)</td></tr><tr><td>Turkey</td><td>0.063 ***</td><td>(0.013)</td><td>0.023 *</td><td>(0.009)</td><td>0.063 ***</td><td>(0.011)</td></tr><tr><td>Middle East</td><td>0.068 ***</td><td>(0.016)</td><td>-0.007</td><td>(0.011)</td><td>0.058 ***</td><td>(0.013)</td></tr><tr><td>Latin America</td><td>-0.016</td><td>(0.015)</td><td>-0.009</td><td>(0.012)</td><td>-0.054 ***</td><td>(0.012)</td></tr><tr><td><strong>Parental socioeconomic status</strong></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td><em>Parental educational attainment</em><br>(ref. Both parents have compulsory educ.)</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>One parent has compulsory educ.</td><td>0.053 ***</td><td>(0.011)</td><td>-0.012</td><td>(0.008)</td><td>-0.009</td><td>(0.010)</td></tr><tr><td>Neither parent has compulsory educ.</td><td>0.182 ***</td><td>(0.012)</td><td>-0.009</td><td>(0.008)</td><td>0.002</td><td>(0.011)</td></tr><tr><td><em>Parental employment status</em><br>(ref. Both parents are employed)</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>One parent is employed</td><td>-0.059 ***</td><td>(0.010)</td><td>-0.018 *</td><td>(0.007)</td><td>-0.019 *</td><td>(0.009)</td></tr><tr><td>Neither parent is employed</td><td>-0.110 ***</td><td>(0.019)</td><td>-0.052 ***</td><td>(0.015)</td><td>-0.061 ***</td><td>(0.016)</td></tr><tr><td>Mother's age</td><td>0.004 ***</td><td>(0.001)</td><td>-0.001 **</td><td>(0.001)</td><td>-0.001</td><td>(0.001)</td></tr><tr><td>Mother's duration of residence in Sweden</td><td>-0.004 *</td><td>(0.002)</td><td>-0.001</td><td>(0.001)</td><td>0.006 **</td><td>(0.002)</td></tr><tr><td>Co-ethnic neighbourhood (terciles)</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>tercile 2</td><td>-0.048 ***</td><td>(0.011)</td><td>0.011</td><td>(0.008)</td><td>-0.001</td><td>(0.010)</td></tr><tr><td>tercile 3 (highest)</td><td>-0.085 ***</td><td>(0.012)</td><td>0.007</td><td>(0.008)</td><td>-0.014</td><td>(0.010)</td></tr><tr><td><strong>Individual characteristics</strong></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Female</td><td>0.127 ***</td><td>(0.009)</td><td>-0.041 ***</td><td>(0.006)</td><td>-0.172 ***</td><td>(0.007)</td></tr><tr><td>Age</td><td>-0.006 **</td><td>(0.002)</td><td>0.003</td><td>(0.001)</td><td>0.012 ***</td><td>(0.002)</td></tr><tr><td><em>Educational attainment</em><br>(ref. Compulsory education)</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Upper secondary educ.</td><td></td><td></td><td>0.130 ***</td><td>(0.012)</td><td>0.043 ***</td><td>(0.009)</td></tr><tr><td>Tertiary educ.</td><td></td><td></td><td>0.188 ***</td><td>(0.012)</td><td>0.180 ***</td><td>(0.011)</td></tr><tr><td>Unknown</td><td></td><td></td><td>-0.594 ***</td><td>(0.038)</td><td>-0.096 ***</td><td>(0.020)</td></tr><tr><td><em>Municipality of residence</em><br>(ref. Greater Stockholm)</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Greater Gothenburg</td><td>0.011</td><td>(0.016)</td><td>-0.019</td><td>(0.011)</td><td>-0.045 ***</td><td>(0.013)</td></tr><tr><td>Greater Malmö</td><td>0.010</td><td>(0.021)</td><td>-0.064 ***</td><td>(0.016)</td><td>-0.079 ***</td><td>(0.018)</td></tr><tr><td>Medium-sized city</td><td>0.001</td><td>(0.011)</td><td>-0.018 *</td><td>(0.008)</td><td>-0.058 ***</td><td>(0.009)</td></tr><tr><td>Small city or rural</td><td>-0.097 ***</td><td>(0.019)</td><td>-0.016</td><td>(0.013)</td><td>-0.047 ***</td><td>(0.018)</td></tr><tr><td>Average income in neighbourhood (terciles)</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>tercile 2</td><td>0.102 ***</td><td>(0.011)</td><td>0.045 ***</td><td>(0.008)</td><td>0.090 ***</td><td>(0.009)</td></tr><tr><td>tercile 3 (highest)</td><td>0.170 ***</td><td>(0.011)</td><td>0.066 ***</td><td>(0.007)</td><td>0.167 ***</td><td>(0.009)</td></tr><tr><td>McFadden's Adj. R<sup>2</sup></td><td>0.091</td><td></td><td>0.120</td><td></td><td>0.149</td><td></td></tr><tr><td>N</td><td>10 450</td><td></td><td>10 450</td><td></td><td>10 450</td><td></td></tr></tbody></table>

Notes. Robust standard errors at the individual level in parentheses. * p < 0.05; ** p < 0.01; *** p < 0.001 (two-tailed).

migrants' residential improvement (Ellis et al., 2006). Indeed, couples that include a partner from the majority group may both have a greater preference for majority-dense neighbourhoods and be less vulnerable to discrimination in the housing market.

### 3. Literature review

While much research in Sweden and other countries analyses the attainment of second-generation migrants within a single life domain, less attention has been paid to the extent to which outcomes across different domains coincide (van Ham & Tammaru, 2016). Research that addresses multiple dimensions of integration often does so by reviewing separate empirical studies (Drouhot & Nee, 2019; Waters & Jimenez, 2005; White & Glick, 2009; Zhou & Gonzales, 2019). In the US context, asymmetries between dimensions have been observed for the children of Mexican and Asian migrants. For the former, cultural integration in terms of English language acquisition is accompanied with lower rates of intermarriage and residential attainment (Telles & Oritz, 2009). For the latter, language acquisition coincides with a low level of self-identification as Americans (Zhou & Xiong, 2005).

In the Western European context, a recent study shows that ethnic and generational differences vary between structural, cultural, social, political and civic integration (Heath & Schneider, 2021). Other studies find that different dimensions of integration are positively but not necessarily strongly related. Some dimensions are also relatively independent. For instance, some first- and second-generation migrant groups differ in their social and cultural outcomes when compared to the

majority group, but not in their economic outcomes (Fajth & Lessard-Phillips, 2022; Safi, 2008). Evidence from the UK points to distinct clusters of adaptation. In particular, ethnic minority groups that have high levels of cultural adaptation often appear to have low levels of socioeconomic and political adaptation (Lessard-Phillips, 2017). Another paper focuses on Caribbean migrants in the UK and finds that second-generation Caribbean women are in a disadvantaged position compared to the White British population regarding their housing situation, but not in terms of socioeconomic attainment (Wallace et al., 2022). A recent study from Sweden uses latent class analysis to identify multidimensional life course trajectories followed by the children of migrants. The most disadvantaged trajectory is characterised by early childbearing, a high dependency on social welfare, low employment and education levels (Wilson et al., 2022).

Studies on multiple dimensions of integration constitute a small but growing part of the literature on migrant's life outcomes. By contrast, a rich body of research examines how variables from one life domain explain a dependent variable from another domain. In Sweden, studies have assessed how educational outcomes are shaped by residential trajectories. Second-generation migrants, who grow up in neighbourhoods with a high share of co-ethnics, tend to obtain lower school grades than migrants who grow up elsewhere (Bygren & Szulkin, 2010). Still, overall differences in educational attainment are small once differences in parental socioeconomic status are controlled for (Engzell, 2019; Jonsson & Rudolphi, 2011). When it comes to labour market outcomes, studies find that second-generation migrants from Turkey, the Middle East and Africa tend to have lower employment rates and earnings than the
<table><caption>**Table 4**
Average marginal effects from logistic regressions on the social outcomes of second-generation migrants in 2015.</caption><thead><tr><th></th><th>Swedish spouse</th><th></th><th>Migrant-dense workplace</th><th></th></tr></thead><tbody><tr><td><strong>Region of origin</strong> (ref. Finland)</td><td></td><td></td><td></td><td></td></tr><tr><td>Poland</td><td>-0.114 **</td><td>(0.038)</td><td>0.063 **</td><td>(0.023)</td></tr><tr><td>ex-Yugoslavia</td><td>-0.361 ***</td><td>(0.029)</td><td>0.043</td><td>(0.023)</td></tr><tr><td>Turkey</td><td>-0.497 ***</td><td>(0.018)</td><td>0.138 ***</td><td>(0.014)</td></tr><tr><td>Middle East</td><td>-0.406 ***</td><td>(0.023)</td><td>0.093 ***</td><td>(0.017)</td></tr><tr><td>Latin America</td><td>-0.217 ***</td><td>(0.026)</td><td>0.093 ***</td><td>(0.017)</td></tr><tr><td><strong>Parental socioeconomic status</strong></td><td></td><td></td><td></td><td></td></tr><tr><td>Parental educational attainment<br>(ref. Both parents have compulsory educ.)</td><td></td><td></td><td></td><td></td></tr><tr><td>One parent has compulsory educ.</td><td>0.003</td><td>(0.015)</td><td>-0.007</td><td>(0.012)</td></tr><tr><td>Neither parent has compulsory educ.</td><td>0.030</td><td>(0.016)</td><td>-0.011</td><td>(0.013)</td></tr><tr><td>Parental employment status<br>(ref. Both parents are employed)</td><td></td><td></td><td></td><td></td></tr><tr><td>One parent is employed</td><td>-0.025</td><td>(0.014)</td><td>0.006</td><td>(0.011)</td></tr><tr><td>Neither parent is employed</td><td>-0.034</td><td>(0.028)</td><td>0.008</td><td>(0.022)</td></tr><tr><td>Mother's age</td><td>0.003 **</td><td>(0.001)</td><td>-0.001</td><td>(0.001)</td></tr><tr><td>Mother's duration of residence in Sweden</td><td>0.001</td><td>(0.003)</td><td>-0.003</td><td>(0.002)</td></tr><tr><td>Co-ethnic neighbourhood (terciles)</td><td></td><td></td><td></td><td></td></tr><tr><td>tercile 2</td><td>-0.039 **</td><td>(0.014)</td><td>0.015</td><td>(0.011)</td></tr><tr><td>tercile 3 (highest)</td><td>-0.092 ***</td><td>(0.016)</td><td>0.039 **</td><td>(0.012)</td></tr><tr><td><strong>Individual characteristics</strong></td><td></td><td></td><td></td><td></td></tr><tr><td>Female</td><td>-0.025 *</td><td>(0.011)</td><td>0.010</td><td>(0.009)</td></tr><tr><td>Age</td><td>0.005 *</td><td>(0.002)</td><td>-0.002</td><td>(0.002)</td></tr><tr><td><strong>Educational attainment</strong></td><td></td><td></td><td></td><td></td></tr><tr><td>(ref. Compulsory education)</td><td></td><td></td><td></td><td></td></tr><tr><td>Upper secondary educ.</td><td>0.016</td><td>(0.018)</td><td>-0.086 ***</td><td>(0.012)</td></tr><tr><td>Tertiary educ.</td><td>0.057 **</td><td>(0.019)</td><td>-0.241 ***</td><td>(0.013)</td></tr><tr><td>Unknown</td><td>-0.152</td><td>(0.116)</td><td>N.A.</td><td>N.A.</td></tr><tr><td><strong>Municipality of residence</strong></td><td></td><td></td><td></td><td></td></tr><tr><td>(ref. Greater Stockholm)</td><td></td><td></td><td></td><td></td></tr><tr><td>Greater Gothenburg</td><td>0.062 **</td><td>(0.020)</td><td>-0.097 ***</td><td>(0.016)</td></tr><tr><td>Greater Malmö</td><td>0.031</td><td>(0.027)</td><td>-0.074 ***</td><td>(0.022)</td></tr><tr><td>Medium-sized city</td><td>0.128 ***</td><td>(0.014)</td><td>-0.205 ***</td><td>(0.012)</td></tr><tr><td>Small city or rural</td><td>0.140 ***</td><td>(0.024)</td><td>-0.254 ***</td><td>(0.022)</td></tr><tr><td>Average income in neighbourhood (terciles)</td><td></td><td></td><td></td><td></td></tr><tr><td>tercile 2</td><td>0.091 ***</td><td>(0.014)</td><td>-0.052 ***</td><td>(0.011)</td></tr><tr><td>tercile 3 (highest)</td><td>0.132 ***</td><td>(0.014)</td><td>-0.067 ***</td><td>(0.011)</td></tr><tr><td>McFadden's Adj. R<sup>2</sup></td><td>0.245</td><td></td><td>0.100</td><td></td></tr><tr><td>N</td><td>5 134</td><td></td><td>9 166</td><td></td></tr></tbody></table>

Notes. In the analysis on the likelihood to have a Swedish spouse, the sample is restricted to married individuals. In the analysis on the likelihood to be in a migrant-dense workplace, the sample is restricted to employed individuals. Robust standard errors at the individual level in parentheses. * p < 0.05; ** p < 0.01; *** p < 0.001 (two-tailed).

Swedish majority group, while migrants from the other Nordic countries and Western Europe often have similar outcomes to natives (Hammarstedt & Palme, 2012; Rooth & Ekberg, 2003). There are also notable differences in education-job mismatch across regions of origin (Andersson Joona et al., 2014; Dahlstedt, 2015; Visintin et al., 2015), which could indicate ethnic discrimination in the labour market. Regarding the relationship between migrants' labour market and social outcomes, Dribe and Nystedt (2015) find that intermarriage leads to a wage premium for migrants in Sweden.

The relationship between labour market outcomes and social integration is the subject of a vibrant debate. Indeed, other Swedish studies find that selection accounts for the relationship between intermarriage and migrants' economic situation (Bevelander & Irastorza, 2014; Nekby, 2010). After controlling for socioeconomic factors, studies also find considerable differences in the likelihood to intermarry across regions of origin (Behtoui, 2010; Haandrikman, 2014). This may be the result of differential preferences across origin groups and/or constraints, as natives' preferences also play an important role for intermarriage (Haandrikman, 2014). Prior research also finds that migrants with tertiary education and those who initially settled in a neighbourhood with a high share of natives are more likely to become employed in a native-dense workplace (Chihaya et al., 2022). To the extent that neighbourhoods provide a context for social interaction, native neighbours may provide migrants with information on job openings.

Finally, when it comes to residential attainment, Swedish research shows that having a higher income, tertiary education and a Swedish

spouse increases migrants' probability of moving out of a deprived neighbourhood (Alm Fjellborg, 2021; Chihaya et al., 2022; Macpherson & Strömgren, 2013; Vogiazides, 2018; Vogiazides & Chihaya, 2020), residing in a native-dominated neighbourhood (Kadarik, 2020), or becoming homeowners (Magnusson Turner & Hedman, 2014). Yet, differences in neighbourhood characteristics between origin groups remain even after controlling for individuals' demographic and socioeconomic characteristics. First-generation migrants from the Middle East and North Africa are less likely to translate their socioeconomic gains into neighbourhood improvement, which suggests that housing market discrimination and/or preference for residing in minority-dense areas may be at play (Auspurg et al., 2019; Bolt et al., 2010).

Based on theory and previous empirical findings, we expect differences between second-generation migrants and the majority group to vary across life domains and origin groups. We anticipate discrepancies between educational attainment and labour market outcomes for origin groups at risk of employer discrimination. Socioeconomic attainment and social outcomes are expected to be related, but preferences and structural constraints are also likely to influence the extent to which the two dimensions are linked. Finally, as neighbourhoods are spheres of potential interaction, residential outcomes are expected to be related to social outcomes. Residential outcomes are also expected to be connected with socioeconomic attainment, though preferences and structural constraints may engender differences across origin groups.
<figure><img src="image_5.png" /><figcaption>**Fig. 3.** Average marginal effects from logistic regressions on social outcomes. *Notes*. All origin groups are compared to the Swedish majority group, whose outcomes are indicated by the horizontal line. The baseline model (circles) differentiates between region-of-origin groups. The model that controls for parental SES (diamonds) includes the variables: parental educational attainment, parental employment status and mother's age in 1990. The model that controls for individual characteristics (triangles) additionally includes gender, age, educational attainment, municipality of residence and average income in the neighbourhood of residence in 2015. Corresponding results are provided in Tables A5–A6 in the Appendix.</figcaption></figure>

# 4. Data and methods

We use Swedish individual-level register data covering the period 1990–2015, which includes a wide range of socioeconomic, demographic and residential variables.<fnref n="3" /> Multigenerational linkages allow

us to distinguish between second-generation migrants, that is individuals born in Sweden with two foreign-born parents, and the Swedish majority group including individuals born in Sweden with two Swedish-born parents. Multigenerational linkages also enable us to account for differences in parental socioeconomic status among second-generation migrants and the majority group.

## 4.1. Sample restrictions

Considering our interest in second-generation migrants’ outcomes across a number of life domains including educational attainment,

<footnote n="3">³ The data comprise total population administrative register data. Access to pseudonymized data is regulated through ethical and legal vetting instead of informed consent. The Ethical Review Board represents the interests of the general public in this process. The use of data for research purposes was approved by the Regional Ethical Review Board (Dnr 2017/1980-31/5).</footnote>
<figure><img src="image_6.png" /><figcaption>**Fig. 4.** Average marginal effects from logistic regressions on residential attainment. *Notes*. All origin groups are compared to the Swedish majority group, whose outcomes are indicated by the horizontal line. The baseline model (circles) differentiates between region-of-origin groups. The model that controls for parental SES (diamonds) includes the variables: parental educational attainment, parental employment status and mother's age in 1990. The model that controls for individual characteristics (triangles) additionally includes gender, age, educational attainment, municipality of residence and average income in the neighbourhood of residence in 2015. Corresponding results are provided in Tables A7–A9 in the Appendix.</figcaption></figure>

labour market outcomes and family formation, we restrict the popula-
tion to the age range 30–40 in 2015 when we can expect that most have
completed their schooling, entered the labour market and got married.
We control for parental socioeconomic status in 1990, when parents
were of similar ages as their children in 2015 (see Table A1 in the Ap-
pendix for descriptive statistics of second-generation migrants and their
parents). This allows us not only to compare the outcomes of second-
generation migrants to those of the Swedish majority group, but also
to assess differences in educational attainment and employment rates
across generations in descriptive analyses.

We also restrict our analysis to first-generation parents who arrived
between 1975 and 1985, given that the duration of residence in the
country is strongly related to migrants’ outcomes. Furthermore, we
exclude all individuals whose parents are not observed in the register
data in 1990 from the sample, since information on parental socioeco-
nomic status is important for understanding the outcomes of second-
generation migrants (Heath et al., 2008).<fnref n="4" /> Fig. 1 illustrates the sample
restrictions.

Our analysis focuses on the six largest second-generation migrant
groups in Sweden who were between 30 and 40 years of age by 2015
(N = 10,450). The countries/regions of origin included are: Finland
(N = 2,254), Poland (N = 733), ex-Yugoslavia (N = 569), Turkey
(N = 3,583), Middle East (N = 1,627), and Latin America (N = 1,684).<fnref n="5" />
The Swedish majority group comprises 807,067 individuals, i.e.
Swedish-born individuals with two Swedish-born parents who were
between 30 and 40 years of age in 2015. It is important to note that these
countries comprise multiple ethnic groups, and these may differ in their
socioeconomic status. For example, first-generation migrants from
Finland include ethnic Finns but also Swedish-speaking Finns, an ethnic
minority that constitutes about 5% of the Finnish population (Weber &
Saarela, 2019). Likewise, migrants from Turkey can be ethnic Turks,
ethnic Kurds or Syriac/Assyrians (Westin, 2003). Given that Swedish
registers do not contain information on ethnicity, the country/region of
birth is the best available way to construct origin groups in this study.

4.2. Context of arrival

First-generation parents in our study arrived after the oil shock of
1973 when labour migration was largely stopped in Northern Europe,
but immigration due to family reunion continued. This mode of arrival
probably concerned the first-generation from ex-Yugoslavia in our
study. Citizens from Finland could move freely to Sweden within the
common Nordic labour market, which was established in 1954. In
addition, from the 1970s onwards, increasing numbers of people sought
asylum in Sweden. In our study, first-generation migrants from Poland,
Turkey, the Middle East and Latin America were refugees seeking to
escape political and religious persecution. During the period 1975–85,
Sweden received Syriac/Assyrian and Kurdish refugees from Turkey and
the Middle East as well as Chileans fleeing the military coup in 1973
(Westin, 2003). Polish migrants, who came to Sweden in the early
1980s, arrived as refugees escaping the communist regime (Andersson,
2015; Lubińska, 2013).

4.3. Outcomes and methods

In this study, we focus on three life domains—socioeconomic, social and residential, each domain being measured by several specific outcomes. Socioeconomic outcomes pertain to the binary indicators of whether individuals have completed tertiary education, whether they

<footnote n="4">⁴ This concerns 0.19% of Swedish-born individuals who are 30–40 years of age in 2015.</footnote>

<footnote n="5">⁵ Ex-Yugoslavia refers to former Yugoslavia, Bosnia and Herzegovina, Croatia and Slovenia. The Middle East includes Iran, Iraq, Syria and the rest of the Middle East. Latin America includes Central America, Chile and South America.</footnote>
<table><caption>**Table 5**
Average marginal effects from logistic regressions on the residential attainment of second-generation migrants in 2015.</caption><thead><tr><th></th><th>Vulnerable neighbourhood</th><th>Migrant-dense neighbourhood</th><th>Homeownership</th></tr></thead><tbody><tr><td><strong>Region of origin (ref. Finland)</strong></td><td></td><td></td><td></td></tr><tr><td>Poland</td><td>0.062 ***</td><td>0.193 ***</td><td>0.002</td></tr><tr><td>ex-Yugoslavia</td><td>0.037 **</td><td>0.185 ***</td><td>0.036</td></tr><tr><td>Turkey</td><td>0.078 ***</td><td>0.260 ***</td><td>0.112 ***</td></tr><tr><td>Middle East</td><td>0.058 ***</td><td>0.254 ***</td><td>0.023</td></tr><tr><td>Latin America</td><td>0.043 ***</td><td>0.246 ***</td><td>-0.115 ***</td></tr><tr><td><strong>Parental socioeconomic status</strong></td><td></td><td></td><td></td></tr><tr><td>Parental educational attainment<br>(ref. Both parents have compulsory educ.)</td><td></td><td></td><td></td></tr><tr><td>One parent has compulsory educ.</td><td>0.005</td><td>0.015</td><td>-0.010</td></tr><tr><td>Neither parent has compulsory educ.</td><td>-0.020 **</td><td>0.016</td><td>-0.002</td></tr><tr><td>Parental employment status<br>(ref. Both parents are employed)</td><td></td><td></td><td></td></tr><tr><td>One parent is employed</td><td>-0.001</td><td>-0.014</td><td>-0.029 **</td></tr><tr><td>Neither parent is employed</td><td>-0.002</td><td>-0.038</td><td>-0.073 ***</td></tr><tr><td>Mother's age</td><td>-0.001</td><td>-0.002 **</td><td>-0.001</td></tr><tr><td>Mother's duration of residence in Sweden</td><td>0.001</td><td>-0.001</td><td>0.006 **</td></tr><tr><td>Co-ethnic neighbourhood (terciles)</td><td></td><td></td><td></td></tr><tr><td>tercile 2</td><td>0.012</td><td>0.055 ***</td><td>0.003</td></tr><tr><td>tercile 3 (highest)</td><td>0.042 ***</td><td>0.171 ***</td><td>0.034 **</td></tr><tr><td><strong>Individual characteristics</strong></td><td></td><td></td><td></td></tr><tr><td>Female</td><td>0.005</td><td>0.003</td><td>-0.004</td></tr><tr><td>Age</td><td>0.001</td><td>-0.005 **</td><td>0.007 ***</td></tr><tr><td>Educational attainment<br>(ref. Compulsory education)</td><td></td><td></td><td></td></tr><tr><td>Upper secondary educ.</td><td>-0.008</td><td>-0.027 *</td><td>0.079 ***</td></tr><tr><td>Tertiary educ.</td><td>-0.034 ***</td><td>-0.022</td><td>0.160 ***</td></tr><tr><td>Unknown</td><td>0.007</td><td>-0.079</td><td>0.007</td></tr><tr><td>Municipality of residence<br>(ref. Greater Stockholm)</td><td></td><td></td><td></td></tr><tr><td>Greater Gothenburg</td><td>-0.017</td><td></td><td>-0.021 ***</td></tr><tr><td>Greater Malmö</td><td>-0.128 ***</td><td></td><td>-0.041</td></tr><tr><td>Medium-sized city</td><td>-0.148 ***</td><td></td><td>0.054</td></tr><tr><td>Small city or rural</td><td>N.A.</td><td></td><td>0.171 ***</td></tr><tr><td>Average income in neighbourhood (terciles)</td><td></td><td></td><td></td></tr><tr><td>tercile 2</td><td>-0.292 ***</td><td>-0.202 ***</td><td>0.229 ***</td></tr><tr><td>tercile 3 (highest)</td><td>-0.303 ***</td><td>-0.207 ***</td><td>0.289 ***</td></tr><tr><td>McFadden's Adj. R<sup>2</sup></td><td>0.428</td><td>0.132</td><td>0.101</td></tr><tr><td>N</td><td>10 450</td><td>10 450</td><td>10 450</td></tr></tbody></table>

Notes. The logistic regression on the likelihood to live in a migrant-dense neighbourhood does not control for municipality of residence due to high correlation between the dependent variable and the control variable (Pearson's r is 0.47). Robust standard errors at the individual level in parentheses. * p < 0.05; ** p < 0.01; *** p < 0.001 (two-tailed).

<table><caption>**Table 6**
Summary table of the degree of similarity in outcomes between second-generation migrants and the Swedish majority population in 2015.</caption><thead><tr><th></th><th>Socio-economic</th><th>Social</th><th>Residential</th></tr></thead><tbody><tr><td>Finland</td><td>low</td><td>high</td><td>high</td></tr><tr><td>Poland</td><td>medium</td><td>high</td><td>high</td></tr><tr><td>ex-Yugoslavia</td><td>high</td><td>medium</td><td>high</td></tr><tr><td>Turkey</td><td>high</td><td>low</td><td>medium</td></tr><tr><td>Middle East</td><td>high</td><td>low</td><td>low</td></tr><tr><td>Latin America</td><td>low</td><td>medium</td><td>low</td></tr></tbody></table>

are employed, and whether they are in the top income quartile; in other words, whether individuals have an income of about 346,000 SEK or more in 2015. We consider two measures of social outcomes: intermarriage, i.e. whether migrants are married to a Swedish partner (Swedish-born with two Swedish-born parents), and whether individuals work in migrant-dense workplaces.<fnref n="6" /> In particular, we focus on the binary outcome of being in the top tercile or in workplaces with many first- or second-generation workers on a relative scale. Residential outcomes are assessed using three binary variables: 1) whether second-generation migrants live in a vulnerable neighbourhood (corresponding to

'vulnerable' or 'particularly vulnerable' according to the classification by the Swedish Police, 2017), 2) whether they live in migrant-dense neighbourhoods (from the first and second generation), defined as the DeSO area<fnref n="7" /> (top tercile), and 3) whether they are homeowners.<fnref n="8" />

We analyse these outcomes using logistic regression techniques. Considering the methodological issues in comparing odds ratios across models, groups, samples and years (Mood, 2010), we present average marginal effects in Figs. 2–4. These allow us to interpret the size of the coefficients as percentage point differences. Point estimates with their corresponding standard errors are provided in Tables A2-A9 in the Appendix. We show results from three models which compare the outcomes of second-generation migrants to those of the Swedish majority group.<fnref n="9" /> The baseline model distinguishes between the different regions

<footnote n="6">⁶ These are identified using unique identifiers (or CFAR numbers) for all company workplaces provided in Swedish register data. Another identifier, which focuses on companies (PeOrgNr), provides similar results.</footnote>

<footnote n="7">⁷ DeSOs (Demografiska Statistikområden) consist of geographical units that are rather homogeneous in terms of population size and take physical barriers into account (Statistics Sweden, 2019).</footnote>

<footnote n="8">⁸ The housing tenure variable in Swedish register data indicates whether a dwelling is rented or owned. As it relates to the dwelling rather than to the individual, it cannot show whether an owned dwelling is sub-rented.</footnote>

<footnote n="9">⁹ This approach follows the practice of comparing averages between migrant and non-migrant groups (Alba & Foner, 2016; OECD/EU, 2019). It therefore differs from comparisons between children and their parents (Bratu & Bolotnyy, 2022; Hermansen, 2016; Li & Heath, 2016), and comparisons between migrants and different strata of the majority society (Portes & Zhou, 1993).</footnote>
of origin. The second model adds controls for parental socioeconomic status. Parental characteristics include educational attainment (which differentiates among both, one or neither of the parents having only compulsory education in 1990), employment status (again differentiating among both, one or neither of the parents being employed in 1990) and the age of the mother. The third model additionally controls for individual characteristics. These include basic demographic characteristics (gender and age), educational attainment and the type of municipality of residence in 2015 (Greater Stockholm, Greater Gothenburg, Greater Malmö, medium-sized city, small city or rural), based on the 2017 classification of municipalities by the Swedish Association of Local Authorities and Regions. This model also accounts for the average income in the neighbourhood (DeSO) of residence in 2015. This measure allows us to control for residential segregation in adulthood, which contributes to differences between migrants and the majority group.<fnref n="10" />

Considering that this analysis compares second-generation migrants and the Swedish majority group, we cannot control for duration of residence in Sweden. However, since we restrict the sample to a 10-year window of arrival, and migration is most common in early adulthood, we expect that accounting for the mother's age in 1990 provides a reasonable proxy of time since arrival among foreign-born parents (Wingens et al., 2011).

In order to account for the parents' length of stay in Sweden, we additionally present average marginal effects from logistic regressions that focus on second-generation migrants (Tables 3–5). These models moreover allow us to assess the impacts of growing up in a predominantly co-ethnic neighbourhood. We compare all origin groups to Finnish second-generation migrants and account for the same variables as in the third model (parental socioeconomic status and individual characteristics) as well as mother's duration of residence in Sweden, and proximity to co-ethnic first-generation migrants in the mother's neighbourhood (DeSO) of residence in 1990.<fnref n="11" /> Considering that the variable proximity to co-ethnics in the mother's neighbourhood is highly skewed, we account for it in terciles. This allows us to distinguish between living in neighbourhoods with low, intermediate and high proportions of co-ethnics on a relative scale.

# 5. Disparities between second-generation migrants and the Swedish majority population

Below we present both descriptive and regression analysis results for the socioeconomic, social and residential outcomes of second-generation migrants compared to the Swedish majority group.

## 5.1. Socioeconomic attainment

Our descriptive analysis in Table 1 shows that the Swedish majority group tends to have higher educational attainment than second-generation migrants. The proportion of individuals with tertiary education is 46% among the Swedish majority group, as compared to 34% among second-generation migrants. Second-generation migrants from Poland are an exception, with 54% having completed tertiary education. Tertiary education is the least common among second-generation migrants from Finland, ex-Yugoslavia and Turkey. The proportion of individuals with only compulsory education is also highest among Turkish second-generation migrants. Still, when compared to their parents, second-generation migrants have substantially higher rates of tertiary education (see Table 2). The largest differences between first- and second-generation migrants can be found among migrants from Turkey,

ex-Yugoslavia and the Middle East. For example, 30% of second-generation Turks have tertiary education in 2015, whereas the corresponding proportion is 1% among their first-generation mothers and 4% among their first-generation fathers. Among first-generation migrants, Poles are the most likely group to have completed tertiary education (31%), even exceeding that of the parents of the Swedish majority group. Still, second-generation Poles are more likely to have tertiary education than their parents, similar to the other groups.

Our regression analysis in Fig. 2 shows that the raw gaps observed in the baseline model (indicated by circles) decrease when we control for differences in parental socioeconomic status in the second model (indicated by diamonds). This finding is the most pronounced among second-generation migrants from ex-Yugoslavia, Turkey and the Middle East. These origin groups have a lower likelihood of completing tertiary education than the Swedish majority group in the baseline model. Yet, when we account for parental socioeconomic status, Turkish and Middle Eastern second-generation migrants' likelihood of having completed tertiary education slightly surpasses that of the Swedish majority. This suggests that the lower educational attainment observed in these groups in the baseline model is largely attributable to a disadvantaged socioeconomic background. By contrast, the likelihood of having completed tertiary education among Finnish and Latin American second-generation migrants remains significantly lower even when we control for socioeconomic background. Finnish and Latin American second-generation migrants are about nine percentage points less likely to have completed tertiary education than the Swedish majority group. These are non-trivial differences when compared to the average probability of having completed tertiary education of 46% (see Table 1). The final model additionally controls for individual characteristics (indicated by triangles). However, these do not appear to substantially change the results from the model that only accounted for parental socioeconomic status (indicated by diamonds). Additional analyses including information on the proportion of co-ethnics in mothers' neighbourhood of residence in 1990 show that growing up in a neighbourhood with a high proportion of co-ethnics is negatively related to the likelihood of completing tertiary education among second-generation migrants (see Table 3).

Regarding employment, we find that second-generation migrants are less frequently employed (88%) than the Swedish majority group (93%) as shown in the descriptive analysis presented in Table 1. The lowest employment rates (i.e. 86%) are observed among second-generation migrants from Poland and Latin America. Among second-generation migrants from Finland, Poland and ex-Yugoslavia, the employment rate in 2015 is similar to that of their fathers in 1990 (see Table 2). Fathers and especially mothers from Turkey and the Middle East tend to have lower employment rates than their children. By contrast, Latin American second-generation migrants have lower employment rates in 2015 than both their parents had in 1990. That is, second-generation Latin Americans have an employment rate of 86%, while the proportion is 90% among their first-generation mothers and 92% among their first-generation fathers.

Our regression analysis reveals that differences in the likelihood of being employed are small (between two and five percentage points), but significant when we control for parental socioeconomic status and individual characteristics (see Fig. 2). Second-generation migrants from Turkey constitute an exception, having a similar likelihood of being employed as the Swedish majority group in the adjusted models. These average marginal effects point to small differences in the likelihood of being employed, given the average employment rate of 93% (see Table 1). Still, considering that second-generation migrants from Poland, ex-Yugoslavia, Turkey and the Middle East have an educational attainment commensurate with the Swedish majority group, the results suggest difficulties may be experienced in translating educational attainments into professional achievements. Additionally, accounting for parental socioeconomic status seems to make a smaller difference for estimates of the likelihood of being employed than for the likelihood of

<footnote n="10">¹⁰ We also estimated the models presented in Figs. 2–4 using neighbourhood fixed effects (DeSO of residence in 2015) and found similar results.</footnote>

<footnote n="11">¹¹ As previously mentioned, countries of birth and aggregations thereof are imperfect proxies for ethnicity, but they are the best option available, based on our study data.</footnote>
completing tertiary education.

Turning to *disposable income*, we find that second-generation migrants have a lower median disposable income than the Swedish majority group (see Table 1). Second-generation migrants from Poland and ex-Yugoslavia are the groups with the highest median income (after the Swedish majority group). Still, their median income is about 15,000 SEK below that of the Swedish majority group. The lowest median income is observed for Latin Americans (about 230,000 SEK). The regression results in Fig. 2 show that second-generation migrants from Latin America are ten percentage points less likely to be in the top income quartile than the Swedish majority group. This indicates that even after accounting for parental socioeconomic status and individual characteristics, the lower disposable income observed in this group persists. We also find that Finnish second-generation migrants are about two percentage points less likely to be in the top income quartile than the majority group. Other migrant groups have a similar likelihood of being in the top income quartile as the Swedish majority group, with the exception of Turkish and Middle Eastern second-generation migrants who are five and three percentage points more likely to be in the top income quartile, respectively. Additional analyses reveal that these groups also have a higher likelihood of earning a low income than the Swedish majority group (see Table A10 in the Appendix). By contrast, Latin American and Finnish second-generation migrants are less likely to have a high income and more likely to have a low income than the majority group. Apart from the notable difference for Latin Americans, differences are rather small when compared to the average likelihood to be in the top income quartile of 25%.

Taken together, we observe relatively small disparities in socioeconomic outcomes between second-generation migrants and the Swedish majority group once we account for parental socioeconomic status and individual characteristics. However, Latin Americans appear to have lower socioeconomic attainment than the Swedish majority group and other origin groups, and despite cultural and geographic proximity, Finns have relatively low socioeconomic achievements.

## 5.2. Social outcomes

In our analysis of social disparities, we focus on the likelihood of having a Swedish spouse (born in Sweden with two Swedish-born parents) and the likelihood of being in a workplace with a high proportion of migrants on a relative scale. The descriptive results in Table 1 show that second-generation migrants are less likely to have a *Swedish spouse* (15%) than the Swedish majority group (49%, with 40% being unmarried and the remaining 10% married to a spouse of another ethnicity). Moreover, we find substantial variation across origin groups. Over a third of Finnish second-generation migrants have a Swedish spouse, followed by Poles and Latin Americans. The proportions are the lowest among second-generation migrants from Turkey and the Middle East, among whom 6% and 9% have a Swedish spouse. In line with this, over a third of Turkish second-generation migrants have a co-ethnic spouse. Considering that the mechanisms of marrying someone from the Swedish majority group differ for native Swedes and individuals with a foreign background, it is arguably more relevant to compare the likelihood of intermarriage between different origin groups. Here, we use Finnish second-generation migrants as the reference group and provide results including the Swedish majority group for completeness. The regression results in Table 4 show that, among those who are married, Finnish second-generation migrants are the most likely group to intermarry. Turkish and Middle Eastern second-generation migrants are 50 and 40 percentage points less likely to have a Swedish spouse than Finns, respectively. Differences to Finnish second-generation migrants are smaller among Polish (11 percentage points) and Latin American migrants (22 percentage points). Still, these differences are also considerable when compared to the average probability to have a Swedish spouse of 31%. These results also show that growing up in a neighbourhood with a high proportion of co-ethnics is negatively related to

the likelihood of having a Swedish spouse. In analyses provided in Fig. 3, we find similar patterns where Turkish and Middle Eastern second-generation migrants are less likely to have a Swedish spouse than the other origin groups.

Turning to the *ethnic composition of the workplace*, the descriptive analysis in Table 1 shows that the median proportion of migrant co-workers (from the first and second generations) is 34% among second-generation migrants as compared to 22% among the Swedish majority group. Turkish second-generation migrants tend to have the highest proportion of migrant co-workers (42%), followed by second-generation migrants from the Middle East (36%). Accordingly, the regression analysis in Fig. 3 shows that, among those who are employed, Turkish second-generation migrants are the most likely to work in migrant-dense workplaces, followed by Middle Eastern and Latin American migrants. Controlling for individual characteristics decreases differences between second-generation migrants and the Swedish majority group. Still, Turkish second-generation continue to be 38 percentage points more likely to work in migrant-dense workplaces than the Swedish majority group in the final model. Differences are smaller among Finnish, Polish and ex-Yugoslav second-generation migrants, but they are also about 25 percentage points more likely to work in migrant-dense workplaces than the majority group. These differences are substantial when compared to the average likelihood of working in a migrant-dense workplace of 29%. In addition, our study shows that among second-generation migrants, growing up in a neighbourhood with a high proportion of co-ethnics is positively related to the likelihood of working in a migrant-dense workplace (see Table 4).

In sum, social disparities seem to be more pronounced than socioeconomic disparities both when we compare outcomes across origin groups and to the majority population. Furthermore, both geographic and cultural distance appear to play a substantial role for the social outcomes of second-generation migrants in Sweden.

## 5.3. Residential attainment

The third dimension addressed comprises residential attainment, which is assessed using three outcomes: residence in a vulnerable neighbourhood, proximity to migrants (from the first and second generations) in the neighbourhood, and homeownership. Our descriptive analysis reveals that 13% of second-generation migrants live in a *vulnerable neighbourhood* as compared to 1% among the Swedish majority group (see Table 1). About a fifth of second-generation Turks live in a vulnerable neighbourhood. Residence in vulnerable neighbourhoods is also relatively frequent among second-generation migrants from the Middle East and Latin America (with 14% and 11% living in such areas, respectively). The regression results in Fig. 4 show that all second-generation migrants have a higher likelihood of living in a vulnerable neighbourhood than the Swedish majority group. Controlling for parental socioeconomic status and individual characteristics reduces differences to the Swedish majority group, but they remain significant. Turkish and Middle Eastern migrants continue to have the highest likelihood of living in a vulnerable neighbourhood and are about two percentage points more likely to live in such areas than the Swedish majority group. This is a sizable difference when compared to the average likelihood to live in a vulnerable neighbourhood of 1% (see Table 1). Table 5 also shows that growing up in a neighbourhood with a high proportion of co-ethnics is positively related to living in a vulnerable neighbourhood.

When it comes to *living in migrant-dense neighbourhoods*, descriptive analyses reveal that the Swedish majority group tends to reside in neighbourhoods where a median of 22% of residents are migrants (from the first and second generations), while second-generation migrants often reside in neighbourhoods where the median share of migrants is 39% (see Table 1). The median proportion of first- and second-generation migrants in the neighbourhood is highest among Turks (47%). The migrant groups with the lowest proportion of migrant
neighbours are Finns and Poles. Accordingly, the regression results indicate that the likelihood of living in a top third neighbourhood in terms of the proportion of migrant residents (first- and second-generation) is higher among second-generation migrants when compared to the Swedish majority group (see Fig. 4). Turkish and Middle Eastern second-generation migrants are about 50 percentage points more likely to live in such neighbourhoods than the Swedish majority group. By contrast, among second-generation migrants, Finns and Poles are the least likely to do so. Still, relative to the average likelihood of living in migrant-dense neighbourhoods of 33%, we also observe notable differences in these groups (about 27 percentage points). Moreover, additional analyses show that growing up in a neighbourhood with a high proportion of co-ethnics is positively related to living in a migrant-dense neighbourhood (see Table 5).

Regarding the type of housing tenure, our descriptive results show that homeownership tends to be less frequent among second-generation migrants (61%) than the Swedish majority group (77%). Among second-generation migrants, the highest share of homeowners is observed among Turks (68%). The lowest proportion of homeowners can be found among second-generation Latin Americans (45%). The regression results show that controlling for parental socioeconomic status and individual characteristics decreases differences in the likelihood of homeownership between second-generation migrant groups and the Swedish majority group. Yet, among Latin Americans the likelihood of being a homeowner remains 16 percentage points lower, even after controlling for relevant variables (see Fig. 4). As in the descriptive analysis, Turkish second-generation migrants have a higher likelihood of being a homeowner than the other origin groups. Once parental socioeconomic status and individual characteristics are accounted for, the likelihood of being a homeowner among Turks exceeds that of the Swedish majority group by about six percentage points. This is a moderate difference considering the average probability of being a homeowner of 77% (see Table 1). Table 5 shows that growing up in a neighbourhood with a high share of co-ethnics is positively related to homeownership.

All in all, there are notable disparities regarding residential attainment across origin groups and in relation to the Swedish majority group, similar to what we observed for social outcomes.

We also find interesting distinctions across residential outcomes. In particular, Turkish migrants have both high and low levels of residential attainment across the set of outcomes analysed. Table A11 in the Appendix presents a cross-tabulation of homeownership and neighbourhood characteristics. It shows that a higher proportion of second-generation homeowners live in a vulnerable neighbourhood than homeowners from the Swedish majority group. Among Turkish and Middle Eastern homeowners, the proportion living in a vulnerable neighbourhood is particularly high. We observe similar patterns for migrant-dense neighbourhoods. Specifically, a higher proportion of Turkish and Middle Eastern homeowners live in a migrant-dense neighbourhood when compared to homeowners from the Swedish majority group and other origin groups.

## 5.4. Robustness checks

We have run a number of checks to ensure that our results are robust to different modelling strategies. Since a considerable proportion of the outcomes analysed in this study are binary, we run logistic regressions and dichotomise outcomes that are continuous or categorical. We present average marginal effects due to issues in comparing odds ratios across models (Mood, 2010). In the Appendix, we also provide linear probability models (Figs. A1-A3) and ordinary least squares models for continuous outcomes (Fig. A4). Linear probability models reveal similar patterns, with the exception of the likelihood of living in a vulnerable neighbourhood. Whereas average marginal effects indicate a notable decrease in the migrant-native gap when parental socioeconomic status and individual characteristics are controlled for (Fig. 4), linear

probability estimates point to gaps of similar size across models (Fig. A3). This may be due to the low prevalence of living in a vulnerable neighbourhood (1%). Overall patterns are, however, similar across alternative model specifications. Likewise, ordinary least squares models provide similar patterns of origin-group differences, though it is difficult to assess if these models suggest larger or smaller differences compared to the logistic models as the coefficients are expressed on a different scale.

We further assess heterogeneity in the results. First, Table A10 in the Appendix provides results on income cut-offs based on quintiles, with the aim of assessing how migrants fare with respect to different strata of the majority population (Portes & Zhou, 1993). It shows that all origin groups are more likely to be in the bottom income quintile (quintile 1) than the Swedish majority population. Second-generation migrants are less likely to be in quintile 2, while group-level differences are relatively small in quintiles 3 and 4. In the top income quintile, we observe pronounced differences between origin groups. Turkish and Middle Eastern migrants are more likely to be in the top income quintile than the Swedish majority group, while they were also more likely to be in the bottom income quintile. In contrast, Finnish and Latin American migrants are less likely to be in the top income quintile, and they were more likely to be in the bottom income quintile than the majority group.

Second, we present stratified analyses by gender (Figs. A5-A7 in the Appendix). The figures indicate the largest gender differences for social outcomes. The difference between second-generation migrants and the Swedish majority group in the likelihood of being in a migrant-dense workplace is somewhat larger for men than for women. However, the difference in terms of intermarriage is more pronounced for women. As expected, gender differences in residential attainment are small. When it comes to socioeconomic attainment, we find that among Latin Americans, the difference in the likelihood of being in the top income quartile is larger for men than for women.

In a last step, we assess different sample restrictions. We run analyses including second-generation migrants with only one foreign-born parent and parent origin mixes (for example, one parent from Finland and the other from Denmark). This set-up provides us with larger sample sizes. However, as some of the parents are consequently from Sweden, we lose observations when controlling for migration-related characteristics (co-ethnic neighbourhood and duration in Sweden). As expected, marrying a Swedish spouse is more common in this sample, but for the other outcomes the patterns are similar. We also use a longer immigration period for the parents. This leads to larger sample sizes but introduces variation that could be driving differences between groups. Considering the amount of research on the importance of the duration of residence in the host country for parental and their children's outcomes and the large sample sizes provided in Swedish register data, we show results for a group of first-generation parents with a relatively narrow arrival period, largely consisting of early refugees. It is important to keep these restrictions in mind when interpreting the results, as patterns may differ for other migrant groups and their descendants.

# 6. Discussion

Our results highlight asymmetries in outcomes across life domains—socioeconomic, social and residential—and origin groups. Table 6 summarizes the patterns for all origin groups, showing that none of the groups display a uniform pattern with the same degree of similarity to the Swedish majority group across the three dimensions. Still, we find overall consistency across dimensions for Polish, ex-Yugoslav and Latin American second-generation migrants, whereas Turkish, Middle Eastern and Finnish second-generation migrants display distinct levels of attainment across dimensions.

Results reveal that Polish and ex-Yugoslav second-generation migrants have relatively high levels of similarity in their socioeconomic, social and residential attainment when compared to the Swedish majority population. In contrast, Latin American second-generation
migrants have lower socioeconomic outcomes, and relatively low social and residential attainment. During the period when the parental generation arrived in Sweden (1975–85), Polish migrants predominantly had high levels of education (Engzell, 2019). This parental background may contribute to the favourable socioeconomic outcomes observed among the second generation from this country. The geographic and cultural proximity between Poland, ex-Yugoslavia and Sweden may also relate to the groups' high levels of social and residential attainment by lowering the threshold to intermarriage and reducing the likelihood of discrimination in the housing market. In line with our findings regarding second-generation migrants from Latin America, previous research has reported overall low socioeconomic attainment (R. Andersson, 2011; Behtoui & Olsson, 2014). The parents of this group predominantly arrived as refugees from Chile. Previous research has found that a considerable share of Chilean refugees returned due to political and economic changes in the origin country, especially those who had the economic means to do so. Staying in Sweden was associated with lower economic outcomes (Klinthäll, 2007). This pattern of consistency across life domains goes in line with the neo-assimilation theory, which envisions an overall trend of decreasing disparities while recognising the possibility of divergence across life domains and migrant groups (Alba & Nee, 1997, 2003).

In contrast, the remaining three origin groups–Turkish, Middle Eastern and Finnish second-generation migrants–display considerable differences in outcomes across life domains. For these origin groups, similarity to the Swedish majority group in one life domain does not necessarily imply similarity in another domain. Second-generation Turkish and Middle Eastern migrants tend to have socioeconomic outcomes that are similar to the Swedish majority group, while we observe considerable disparities in social and residential outcomes. In contrast, second-generation Finns have similar social and residential outcomes to the Swedish majority, but lower socioeconomic attainment.

Distinctions between life domains may be due to preferences and/or discrimination. Turkish and Middle Eastern second-generation migrants may prefer to marry a co-ethnic spouse as well as to live in proximity to other migrants even when they can afford a residence in wealthier and majority-dominated areas. Among these groups, previous research has found residence in migrant-dense areas to be positively associated with labour market performance, due to the access to informal contacts that can be mobilised to enhance professional careers (Ali & Fokkema, 2015; L. Andersson L, 2015; Kalter, 2011; Klinthäll & I Urban, 2016). Among Finnish migrants, the lower socioeconomic attainment of the second generation may reflect the socioeconomic status of their parents, who predominantly arrived as labour migrants to work in blue-collar occupations during the period analysed (Korkiasaari & Söderling, 2003). In contrast, geographic and cultural proximity between Swedes and Finns may explain why these groups are more inclined to intermarry (Haan-drikman, 2014). This diversity in patterns across life domains resonates with the idea put forward by segmented assimilation theory (Portes & Zhou, 1993) that different dimensions of integration do not necessarily coincide, though neo-assimilation theory also acknowledges this as a possibility (Alba & Nee, 1997, 2003). These findings also echo recent research on migrant integration showing that some dimensions of integration are positively though not necessarily strongly related, while other dimensions, such as socioeconomic and social outcomes, are relatively independent (Fajth & Lessard-Phillips, 2022; Lessard-Phillips, 2017; Safi, 2008; Wallace et al., 2022).

We also find indications of heterogeneity within life domains and outcomes. Across the residential outcomes analysed, we observe both small and big disparities between Turkish second-generation migrants and the Swedish majority group. While second-generation Turks have a high likelihood of living in a vulnerable neighbourhood, they also have high propensities of homeownership. Our analyses also reveal that a higher proportion of Turkish and Middle Eastern migrants who own their home live in vulnerable and/or migrant-dense neighbourhoods. This suggests that homeownership may have a different significance for

some second-generation migrant groups. Our robustness checks also indicate heterogeneity across different levels of income. Turkish and Middle Eastern second-generation migrants are both more likely to have low and high incomes than the Swedish majority group. Other outcomes analysed may include heterogeneity that we were unable to observe. For example, workplaces with a high share of migrants may both imply a high proportion of unskilled workers or highly trained professionals that are recruited internationally.

The results of this study point to the importance of parental socioeconomic status and individuals' socioeconomic and residential characteristics, as put forward by segmented assimilation theory (Zhou & Gonzales, 2019). Parental socioeconomic status appears to play an important role for educational attainment (Engzell, 2019; Jonsson & Rudolphi, 2011). Individuals' demographic, socioeconomic and residential characteristics also reduce differences in the social and residential outcomes of second-generation migrants and the Sweden majority group (Alm Fjellborg, 2021; Chihaya et al., 2022). Residence in a neighbourhood with a high proportion of co-ethnics when growing up is negatively related with educational attainment and intermarriage, while it increases the likelihood of working in a migrant-dense workplace, residing in a vulnerable and migrant-dense neighbourhood, and homeownership.

Our analysis of multiple life domains highlights the interlinkages between domains and emphasises the need for an analysis that incorporates multiple aspects of life. However, different outcomes may have distinct implications for migrants' well-being in the host country and differently impact the attitudes of the majority population. Arguably, most individuals aim to find employment, while interaction with the majority population in the workplace, neighbourhood or through intermarriage depends more strongly on preference. Here, both the preferences of migrants and the majority population play a role. As pointed out by Drouhot and Nee (2019), "integration does not imply homogenisation of immigrant identity and culture toward a specific core as a necessary endpoint, although such homogenisation may occur." Indeed, there is no agreement on how to conceptualise and measure integration (Fajth & Lessard-Phillips, 2022; Heath & Schneider, 2021). For instance, there is some debate as to whether intermarriage is a relevant indicator of integration. First, intermarriage does not necessarily entail the elimination of prejudice and overall acceptance in the mainstream society, and second it also reshapes the mainstream, contributing to creating an increasingly diverse and hybrid society (Song, 2009). While keeping these considerations in mind, we have aimed to provide a more comprehensive and nuanced understanding of the life situation of second-generation migrants by studying socioeconomic, social and residential outcomes together.

## 7. Conclusion

This study has provided an overarching account of disparities between second-generation migrants and the Swedish majority group across multiple life domains–socioeconomic, social and residential. Our research revealed substantial heterogeneity across life domains for some origin groups, while others displayed overall consistent patterns across life domains. From a policy perspective, our results underline the importance of having a comprehensive understanding of migrants' outcomes, across multiple dimensions, when designing integration policies.

Future studies should assess the interplay between these different life domains in more detail by using longitudinal analysis to assess the temporality of migrants' social, economic and residential trajectories in the host country. While this study analysed outcomes across multiple life domains by assessing one domain at a time, cluster and latent class analysis are promising tools for identifying typical trajectories using a large range of variables from multiple domains. Moreover, there is a vibrant discussion regarding which frame of reference is most relevant to use when analysing the life outcomes of the children of migrants
(White & Glick, 2009; Zhou & Gonzales, 2019). In this study, we compared second-generation migrant groups to the majority population and to each other. Other fruitful approaches would be to compare the children of migrants to their parents, or to certain segments of the majority population. Finally, other dimensions of integration should also be addressed, including political and cultural adaptation, as well as additional outcomes, such as friendships with members of the majority group to assess the social outcomes of second-generation migrants.

## Funding

This work was supported by the Swedish Research Council for Health, Working life and Welfare (Forskningsrådet om Hälsa, Arbetsliv och Välfärd) [grant numbers 2016-07105, 2021-00026] (R.W. and L.V.); the Åbo Akademi University Foundation's funding of the DemSwed Internal Centre of Excellence 2019-2024 (R.W.); the Foundation for Baltic and East European Studies (Östersjöstiftelsen) (R.W.); and the Swedish Foundation for Humanities and Social Sciences (Riksbankens Jubileumsfond, RJ) [grant number M18-0214:1] (L.V.).

## Declaration of Competing Interest

The authors declare that they have no known competing financial

interests or personal relationships that could have appeared to influence the work reported in this paper.

## Data Availability

The analysis presented in the study is based on Swedish register data. The data are considered sensitive and were made available to the project on the condition that there cannot be further distribution of the data. For access to the underlying data, interested researchers are asked to contact the Swedish national statistics agency.

## Acknowledgements

We are grateful to Ben Wilson and Matthew Wallace for their comments and feedback. We would also like to thank participants at the Stockholm Sessions of Migration and the two anonymous reviewers for their helpful comments.

## Appendix A

See Appendix Tables A1–A11 and Figs. A1–A7 here.

<caption>**Table A1**</caption>

Basic descriptive statistics of second-generation migrants and their mothers and fathers.

<table><thead><tr><th rowspan="2"></th><th rowspan="2">Swedish majority group</th><th rowspan="2">All second-generation migrants</th><th colspan="6">Second-generation migrants by region of origin</th><th rowspan="2">Total</th></tr><tr><th>Finland</th><th>Poland</th><th>ex-Yugoslavia</th><th>Turkey</th><th>Middle East</th><th>Latin America</th></tr></thead><tbody><tr><td>Female</td><td>49</td><td>48</td><td>47</td><td>48</td><td>49</td><td>49</td><td>49</td><td>48</td><td>49</td></tr><tr><td>Median age in 2015</td><td>35</td><td>33</td><td>34</td><td>32</td><td>34</td><td>34</td><td>32</td><td>33</td><td>35</td></tr><tr><td>Municipality of residence</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Greater Stockholm</td><td>21</td><td>54</td><td>42</td><td>48</td><td>29</td><td>60</td><td>63</td><td>57</td><td>22</td></tr><tr><td>Greater Gothenburg</td><td>11</td><td>10</td><td>8</td><td>11</td><td>19</td><td>10</td><td>9</td><td>10</td><td>11</td></tr><tr><td>Greater Malmö</td><td>5</td><td>5</td><td>1</td><td>18</td><td>16</td><td>1</td><td>4</td><td>11</td><td>5</td></tr><tr><td>Medium-sized city</td><td>38</td><td>25</td><td>33</td><td>17</td><td>25</td><td>26</td><td>21</td><td>19</td><td>38</td></tr><tr><td>Small city or rural</td><td>25</td><td>6</td><td>16</td><td>6</td><td>11</td><td>2</td><td>3</td><td>3</td><td>25</td></tr><tr><td>Average income in neighbourhood (in 100 SEK, median)</td><td>2 654</td><td>2 616</td><td>2 580</td><td>2 880</td><td>2 574</td><td>2 610</td><td>2 658</td><td>2 554</td><td>2 653</td></tr><tr><td>N second-generation migrants</td><td>807 067</td><td>10 450</td><td>2 254</td><td>733</td><td>569</td><td>3 583</td><td>1 627</td><td>1 684</td><td>817 517</td></tr><tr><td>Mothers' characteristics</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Median age in 1990</td><td>38</td><td>34</td><td>34</td><td>36</td><td>33</td><td>34</td><td>33</td><td>36</td><td>38</td></tr><tr><td>Median age at immigration</td><td>N.A.</td><td>23</td><td>22</td><td>27</td><td>21</td><td>21</td><td>23</td><td>25</td><td>N.A.</td></tr><tr><td>Median year of immigration</td><td>N.A.</td><td>1978</td><td>1977</td><td>1981</td><td>1978</td><td>1977</td><td>1980</td><td>1979</td><td>N.A.</td></tr><tr><td>N mothers</td><td>807 067</td><td>10 450</td><td>2 254</td><td>733</td><td>569</td><td>3 583</td><td>1 627</td><td>1 684</td><td>817 517</td></tr><tr><td>Fathers' characteristics</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Median age in 1990</td><td>40</td><td>37</td><td>37</td><td>39</td><td>37</td><td>36</td><td>40</td><td>39</td><td>40</td></tr><tr><td>Median age at immigration</td><td>N.A.</td><td>26</td><td>24</td><td>28</td><td>24</td><td>23</td><td>29</td><td>28</td><td>N.A.</td></tr><tr><td>Median year of immigration</td><td>N.A.</td><td>1977</td><td>1977</td><td>1980</td><td>1977</td><td>1977</td><td>1979</td><td>1979</td><td>N.A.</td></tr><tr><td>N fathers</td><td>807 067</td><td>10 450</td><td>2 254</td><td>733</td><td>569</td><td>3 583</td><td>1 627</td><td>1 684</td><td>817 517</td></tr></tbody></table>

Notes. Within origin-group percentages are presented.

<caption>**Table A2**</caption>

Average marginal effects from logistic regressions on the likelihood of having completed tertiary education among second-generation migrants and the Swedish majority population in 2015.

<table><thead><tr><th rowspan="2">Region of origin (ref. Sweden)</th><th colspan="2">Tertiary education</th><th colspan="2">(2)</th><th colspan="2">(3)</th></tr><tr><th>(1)</th><th></th><th>(2)</th><th></th><th>(3)</th><th></th></tr></thead><tbody><tr><td>Finland</td><td>-0.165 ***</td><td>(0.010)</td><td>-0.083 ***</td><td>(0.011)</td><td>-0.087 ***</td><td>(0.010)</td></tr><tr><td>Poland</td><td>0.083 ***</td><td>(0.018)</td><td>0.048 **</td><td>(0.017)</td><td>-0.003</td><td>(0.017)</td></tr><tr><td>ex-Yugoslavia</td><td>-0.139 ***</td><td>(0.020)</td><td>0.006</td><td>(0.022)</td><td>-0.023</td><td>(0.021)</td></tr><tr><td>Turkey</td><td>-0.153 ***</td><td>(0.008)</td><td>0.065 ***</td><td>(0.009)</td><td>0.028 ***</td><td>(0.009)</td></tr><tr><td>Middle East</td><td>-0.069 ***</td><td>(0.012)</td><td>0.067 ***</td><td>(0.013)</td><td>0.025 *</td><td>(0.012)</td></tr><tr><td>Latin America</td><td>-0.100 ***</td><td>(0.012)</td><td>-0.086 ***</td><td>(0.012)</td><td>-0.100 ***</td><td>(0.011)</td></tr></tbody></table>

(continued on next page)
<table><caption>Table A2 (continued)</caption><thead><tr><th></th><th colspan="3" style="text-align: center;">Tertiary education</th></tr><tr><th></th><th style="text-align: center;">(1)</th><th style="text-align: center;">(2)</th><th style="text-align: center;">(3)</th></tr></thead><tbody><tr><td colspan="4"><strong>Parental socioeconomic status</strong></td></tr><tr><td colspan="4"><em>Parental educational attainment</em><br>(ref. Both parents have compulsory educ.)</td></tr><tr><td>One parent has compulsory educ.</td><td></td><td>0.112 ***</td><td>(0.002)</td><td>0.101 ***</td><td>(0.002)</td></tr><tr><td>Neither parent has compulsory educ.</td><td></td><td>0.324 ***</td><td>(0.002)</td><td>0.281 ***</td><td>(0.002)</td></tr><tr><td colspan="4"><em>Parental employment status</em><br>(ref. Both parents are employed)</td></tr><tr><td>One parent is employed</td><td></td><td>-0.094 ***</td><td>(0.002)</td><td>-0.081 ***</td><td>(0.002)</td></tr><tr><td>Neither parent is employed</td><td></td><td>-0.158 ***</td><td>(0.007)</td><td>-0.146 ***</td><td>(0.007)</td></tr><tr><td>Mother's age</td><td></td><td>0.012 ***</td><td>(0.001)</td><td>0.012 ***</td><td>(0.001)</td></tr><tr><td colspan="4"><strong>Individual characteristics</strong></td></tr><tr><td>Female</td><td></td><td></td><td></td><td>0.162 ***</td><td>(0.001)</td></tr><tr><td>Age</td><td></td><td></td><td></td><td>-0.006 ***</td><td>(0.001)</td></tr><tr><td colspan="4"><em>Municipality of residence</em><br>(ref. Greater Stockholm)</td></tr><tr><td>Greater Gothenburg</td><td></td><td></td><td></td><td>0.040 ***</td><td>(0.002)</td></tr><tr><td>Greater Malmö</td><td></td><td></td><td></td><td>0.074 ***</td><td>(0.003)</td></tr><tr><td>Medium-sized city</td><td></td><td></td><td></td><td>-0.019 ***</td><td>(0.002)</td></tr><tr><td>Small city or rural</td><td></td><td></td><td></td><td>-0.064 ***</td><td>(0.002)</td></tr><tr><td>Average income in neighbourhood (terciles)</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>tercile 2</td><td></td><td></td><td></td><td>0.090 ***</td><td>(0.001)</td></tr><tr><td>tercile 3 (highest)</td><td></td><td></td><td></td><td>0.184 ***</td><td>(0.001)</td></tr><tr><td>McFadden's Adj. R<sup>2</sup></td><td>0.001</td><td>0.067</td><td></td><td>0.118</td><td></td></tr><tr><td>N</td><td>817 517</td><td>817 517</td><td></td><td>817 517</td><td></td></tr></tbody></table>

Notes. Robust standard errors at the individual level in parentheses. * p < 0.05; ** p < 0.01; *** p < 0.001 (two-tailed).

<caption>Table A3</caption>

Average marginal effects from logistic regressions on the likelihood of being employed among second-generation migrants and the Swedish majority population in 2015.

<table><thead><tr><th></th><th colspan="3" style="text-align: center;">Employed</th></tr><tr><th></th><th style="text-align: center;">(1)</th><th style="text-align: center;">(2)</th><th style="text-align: center;">(3)</th></tr></thead><tbody><tr><td colspan="4"><strong>Region of origin (ref. Sweden)</strong></td></tr><tr><td>Finland</td><td>-0.055 ***</td><td>(0.007)</td><td>-0.036 ***</td><td>(0.006)</td><td>-0.021 ***</td><td>(0.005)</td></tr><tr><td>Poland</td><td>-0.078 ***</td><td>(0.013)</td><td>-0.064 ***</td><td>(0.012)</td><td>-0.053 ***</td><td>(0.011)</td></tr><tr><td>ex-Yugoslavia</td><td>-0.065 **</td><td>(0.014)</td><td>-0.032 **</td><td>(0.011)</td><td>-0.020 *</td><td>(0.010)</td></tr><tr><td>Turkey</td><td>-0.041 ***</td><td>(0.005)</td><td>0.002</td><td>(0.003)</td><td>0.003</td><td>(0.003)</td></tr><tr><td>Middle East</td><td>-0.059 ***</td><td>(0.008)</td><td>-0.020 ***</td><td>(0.006)</td><td>-0.020 ***</td><td>(0.006)</td></tr><tr><td>Latin America</td><td>-0.076 ***</td><td>(0.009)</td><td>-0.066 ***</td><td>(0.008)</td><td>-0.029 ***</td><td>(0.006)</td></tr><tr><td colspan="4"><strong>Parental socioeconomic status</strong></td></tr><tr><td colspan="4"><em>Parental educational attainment</em><br>(ref. Both parents have compulsory educ.)</td></tr><tr><td>One parent has compulsory educ.</td><td></td><td>0.011 ***</td><td>(0.001)</td><td>-0.002 *</td><td>(0.001)</td></tr><tr><td>Neither parent has compulsory educ.</td><td></td><td>0.022 ***</td><td>(0.001)</td><td>-0.009 ***</td><td>(0.001)</td></tr><tr><td colspan="4"><em>Parental employment status</em><br>(ref. Both parents are employed)</td></tr><tr><td>One parent is employed</td><td></td><td>-0.051 ***</td><td>(0.001)</td><td>-0.028 ***</td><td>(0.001)</td></tr><tr><td>Neither parent is employed</td><td></td><td>-0.142 ***</td><td>(0.006)</td><td>-0.077 ***</td><td>(0.004)</td></tr><tr><td>Mother's age</td><td></td><td>0.001 ***</td><td>(0.001)</td><td>-0.001 ***</td><td>(0.001)</td></tr><tr><td colspan="4"><strong>Individual characteristics</strong></td></tr><tr><td>Female</td><td></td><td></td><td></td><td>-0.020 ***</td><td>(0.001)</td></tr><tr><td>Age</td><td></td><td></td><td></td><td>0.002 ***</td><td>(0.001)</td></tr><tr><td colspan="4"><em>Educational attainment</em><br>(ref. Compulsory education)</td></tr><tr><td>Upper secondary educ.</td><td></td><td></td><td></td><td>0.145 ***</td><td>(0.002)</td></tr><tr><td>Tertiary educ.</td><td></td><td></td><td></td><td>0.183 ***</td><td>(0.002)</td></tr><tr><td>Unknown</td><td></td><td></td><td></td><td>-0.613 ***</td><td>(0.006)</td></tr><tr><td colspan="4"><em>Municipality of residence</em><br>(ref. Greater Stockholm)</td></tr><tr><td>Greater Gothenburg</td><td></td><td></td><td></td><td>-0.006 ***</td><td>(0.001)</td></tr><tr><td>Greater Malmö</td><td></td><td></td><td></td><td>-0.028 ***</td><td>(0.002)</td></tr><tr><td>Medium-sized city</td><td></td><td></td><td></td><td>-0.002 **</td><td>(0.001)</td></tr><tr><td>Small city or rural</td><td></td><td></td><td></td><td>0.004 ***</td><td>(0.001)</td></tr><tr><td>Average income in neighbourhood (terciles)</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>tercile 2</td><td></td><td></td><td></td><td>0.034 ***</td><td>(0.001)</td></tr><tr><td>tercile 3 (highest)</td><td></td><td></td><td></td><td>0.041 ***</td><td>(0.001)</td></tr><tr><td>McFadden's Adj. R<sup>2</sup></td><td>0.001</td><td>0.013</td><td></td><td>0.125</td><td></td></tr><tr><td>N</td><td>817 517</td><td>817 517</td><td></td><td>817 517</td><td></td></tr></tbody></table>

Notes. Robust standard errors at the individual level in parentheses. * p < 0.05; ** p < 0.01; *** p < 0.001 (two-tailed).
<caption>Table A4</caption>

Average marginal effects from logistic regressions on the likelihood of being in the top income quartile among second-generation migrants and the Swedish majority population in 2015.

<table><thead><tr><th></th><th colspan="6">Top income quartile</th></tr><tr><th></th><th>(1)</th><th>(2)</th><th>(3)</th><th></th><th></th><th></th></tr></thead><tbody><tr><td><strong>Region of origin (ref. Sweden)</strong></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Finland</td><td>-0.063 ***</td><td>(0.008)</td><td>-0.018</td><td>(0.010)</td><td>-0.022 **</td><td>(0.009)</td></tr><tr><td>Poland</td><td>-0.006</td><td>(0.016)</td><td>-0.006</td><td>(0.016)</td><td>-0.023</td><td>(0.014)</td></tr><tr><td>ex-Yugoslavia</td><td>-0.055 ***</td><td>(0.017)</td><td>0.024</td><td>(0.021)</td><td>0.016</td><td>(0.018)</td></tr><tr><td>Turkey</td><td>-0.008</td><td>(0.007)</td><td>0.115 ***</td><td>(0.009)</td><td>0.054 ***</td><td>(0.007)</td></tr><tr><td>Middle East</td><td>-0.006</td><td>(0.011)</td><td>0.077 ***</td><td>(0.013)</td><td>0.030 **</td><td>(0.011)</td></tr><tr><td>Latin America</td><td>-0.112 ***</td><td>(0.008)</td><td>-0.103 ***</td><td>(0.009)</td><td>-0.098 ***</td><td>(0.009)</td></tr><tr><td><strong>Parental socioeconomic status</strong></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td><em>Parental educational attainment</em><br>(ref. Both parents have compulsory educ.)</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>One parent has compulsory educ.</td><td></td><td></td><td>0.041 ***</td><td>(0.002)</td><td>0.017 ***</td><td>(0.002)</td></tr><tr><td>Neither parent has compulsory educ.</td><td></td><td></td><td>0.118 ***</td><td>(0.001)</td><td>0.043 ***</td><td>(0.002)</td></tr><tr><td><em>Parental employment status</em><br>(ref. Both parents are employed)</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>One parent is employed</td><td></td><td></td><td>-0.060 ***</td><td>(0.002)</td><td>-0.028 ***</td><td>(0.002)</td></tr><tr><td>Neither parent is employed</td><td></td><td></td><td>-0.085 ***</td><td>(0.006)</td><td>-0.040 ***</td><td>(0.006)</td></tr><tr><td>Mother's age</td><td></td><td></td><td>0.009 ***</td><td>(0.001)</td><td>0.001 *</td><td>(0.001)</td></tr><tr><td><strong>Individual characteristics</strong></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Female</td><td></td><td></td><td></td><td></td><td>-0.196 ***</td><td>(0.001)</td></tr><tr><td>Age</td><td></td><td></td><td></td><td></td><td>0.018 ***</td><td>(0.001)</td></tr><tr><td><em>Educational attainment</em><br>(ref. Compulsory education)</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Upper secondary educ.</td><td></td><td></td><td></td><td></td><td>0.065 ***</td><td>(0.002)</td></tr><tr><td>Tertiary educ.</td><td></td><td></td><td></td><td></td><td>0.172 ***</td><td>(0.002)</td></tr><tr><td>Unknown</td><td></td><td></td><td></td><td></td><td>-0.119 ***</td><td>(0.003)</td></tr><tr><td><em>Municipality of residence</em><br>(ref. Greater Stockholm)</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Greater Gothenburg</td><td></td><td></td><td></td><td></td><td>-0.076 ***</td><td>(0.002)</td></tr><tr><td>Greater Malmö</td><td></td><td></td><td></td><td></td><td>-0.072 ***</td><td>(0.002)</td></tr><tr><td>Medium-sized city</td><td></td><td></td><td></td><td></td><td>-0.099 ***</td><td>(0.001)</td></tr><tr><td>Small city or rural</td><td></td><td></td><td></td><td></td><td>-0.099 ***</td><td>(0.002)</td></tr><tr><td>Average income in neighbourhood (terciles)</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>tercile 2</td><td></td><td></td><td></td><td></td><td>0.078 ***</td><td>(0.001)</td></tr><tr><td>tercile 3 (highest)</td><td></td><td></td><td></td><td></td><td>0.190 ***</td><td>(0.001)</td></tr><tr><td>McFadden's Adj. R<sup>2</sup></td><td>0.001</td><td></td><td>0.025</td><td></td><td>0.158</td><td></td></tr><tr><td>N</td><td>817 517</td><td></td><td>817 517</td><td></td><td>817 517</td><td></td></tr></tbody></table>

Notes. Robust standard errors at the individual level in parentheses. * p < 0.05; ** p < 0.01; *** p < 0.001 (two-tailed).

<caption>Table A5</caption>

Average marginal effects from logistic regressions on the likelihood of having a Swedish spouse among second-generation migrants and the Swedish majority population in 2015.

<table><thead><tr><th></th><th colspan="6">Swedish spouse</th></tr><tr><th></th><th>(1)</th><th>(2)</th><th>(3)</th><th></th><th></th><th></th></tr></thead><tbody><tr><td><strong>Region of origin (ref. Sweden)</strong></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Finland</td><td>-0.180 ***</td><td>(0.014)</td><td>-0.182 ***</td><td>(0.014)</td><td>-0.140 ***</td><td>(0.014)</td></tr><tr><td>Poland</td><td>-0.206 ***</td><td>(0.030)</td><td>-0.194 ***</td><td>(0.030)</td><td>-0.141 ***</td><td>(0.027)</td></tr><tr><td>ex-Yugoslavia</td><td>-0.540 ***</td><td>(0.026)</td><td>-0.544 ***</td><td>(0.026)</td><td>-0.493 ***</td><td>(0.028)</td></tr><tr><td>Turkey</td><td>-0.726 ***</td><td>(0.007)</td><td>-0.726 ***</td><td>(0.007)</td><td>-0.680 ***</td><td>(0.009)</td></tr><tr><td>Middle East</td><td>-0.636 ***</td><td>(0.014)</td><td>-0.636 ***</td><td>(0.014)</td><td>-0.566 ***</td><td>(0.018)</td></tr><tr><td>Latin America</td><td>-0.390 ***</td><td>(0.019)</td><td>-0.387 ***</td><td>(0.019)</td><td>-0.296 ***</td><td>(0.019)</td></tr><tr><td><strong>Parental socioeconomic status</strong></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td><em>Parental educational attainment</em><br>(ref. Both parents have compulsory educ.)</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>One parent has compulsory educ.</td><td></td><td></td><td>-0.002</td><td>(0.002)</td><td>0.001</td><td>(0.002)</td></tr><tr><td>Neither parent has compulsory educ.</td><td></td><td></td><td>-0.017 ***</td><td>(0.002)</td><td>-0.006 ***</td><td>(0.002)</td></tr><tr><td><em>Parental employment status</em><br>(ref. Both parents are employed)</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>One parent is employed</td><td></td><td></td><td>-0.017 ***</td><td>(0.002)</td><td>-0.017 ***</td><td>(0.002)</td></tr><tr><td>Neither parent is employed</td><td></td><td></td><td>-0.051 ***</td><td>(0.009)</td><td>-0.041 ***</td><td>(0.009)</td></tr><tr><td>Mother's age</td><td></td><td></td><td>-0.001 ***</td><td>(0.001)</td><td>-0.001</td><td>(0.001)</td></tr><tr><td><strong>Individual characteristics</strong></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Female</td><td></td><td></td><td></td><td></td><td>0.001</td><td>(0.001)</td></tr><tr><td>Age</td><td></td><td></td><td></td><td></td><td>0.001</td><td>(0.001)</td></tr><tr><td><em>Educational attainment</em><br>(ref. Compulsory education)</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Upper secondary educ.</td><td></td><td></td><td></td><td></td><td>0.026 ***</td><td>(0.003)</td></tr><tr><td>Tertiary educ.</td><td></td><td></td><td></td><td></td><td>0.037 ***</td><td>(0.003)</td></tr><tr><td>Unknown</td><td></td><td></td><td></td><td></td><td>-0.060 *</td><td>(0.025)</td></tr><tr><td><em>Municipality of residence</em><br>(ref. Greater Stockholm)</td><td></td><td></td><td></td><td></td><td></td><td></td></tr></tbody></table>

(continued on next page)
<table><caption>Table A5 (continued)</caption><thead><tr><th></th><th colspan="3">Swedish spouse</th></tr><tr><th></th><th>(1)</th><th>(2)</th><th>(3)</th></tr></thead><tbody><tr><td>Greater Gothenburg</td><td></td><td></td><td>0.067 ***</td></tr><tr><td>Greater Malmö</td><td></td><td></td><td>0.049 ***</td></tr><tr><td>Medium-sized city</td><td></td><td></td><td>0.113 ***</td></tr><tr><td>Small city or rural</td><td></td><td></td><td>0.152 ***</td></tr><tr><td>Average income in neighbourhood (terciles)</td><td></td><td></td><td></td></tr><tr><td>tercile 2</td><td></td><td></td><td>0.023 ***</td></tr><tr><td>tercile 3 (highest)</td><td></td><td></td><td>0.038 ***</td></tr><tr><td>McFadden's Adj. R<sup>2</sup></td><td>0.017</td><td>0.018</td><td>0.034</td></tr><tr><td>N</td><td>486 674</td><td>486 674</td><td>486 674</td></tr></tbody></table>

Notes. In these analyses, the sample is restricted to married individuals. Robust standard errors at the individual level in parentheses. * p < 0.05; ** p < 0.01; *** p < 0.001 (two-tailed).

<caption>Table A6</caption>

Average marginal effects from logistic regressions on the likelihood of working in a migrant-dense workplace among second-generation migrants and the Swedish majority population in 2015.

<table><thead><tr><th></th><th colspan="3">Migrant-dense workplace</th></tr><tr><th></th><th>(1)</th><th>(2)</th><th>(3)</th></tr></thead><tbody><tr><td><strong>Region of origin (ref. Sweden)</strong></td><td></td><td></td><td></td></tr><tr><td>Finland</td><td>0.326 ***</td><td>(0.011)</td><td>0.323 ***</td></tr><tr><td>Poland</td><td>0.361 ***</td><td>(0.019)</td><td>0.348 ***</td></tr><tr><td>ex-Yugoslavia</td><td>0.363 ***</td><td>(0.022)</td><td>0.355 ***</td></tr><tr><td>Turkey</td><td>0.514 ***</td><td>(0.007)</td><td>0.506 ***</td></tr><tr><td>Middle East</td><td>0.468 ***</td><td>(0.012)</td><td>0.457 ***</td></tr><tr><td>Latin America</td><td>0.451 ***</td><td>(0.012)</td><td>0.447 ***</td></tr><tr><td><strong>Parental socioeconomic status</strong></td><td></td><td></td><td></td></tr><tr><td>Parental educational attainment<br>(ref. Both parents have compulsory educ.)</td><td></td><td></td><td></td></tr><tr><td>One parent has compulsory educ.</td><td></td><td>-0.003</td><td>(0.002)</td></tr><tr><td>Neither parent has compulsory educ.</td><td></td><td>0.014 ***</td><td>(0.002)</td></tr><tr><td>Parental employment status<br>(ref. Both parents are employed)</td><td></td><td></td><td></td></tr><tr><td>One parent is employed</td><td></td><td>0.029 ***</td><td>(0.002)</td></tr><tr><td>Neither parent is employed</td><td></td><td>0.079 ***</td><td>(0.008)</td></tr><tr><td>Mother's age</td><td></td><td>-0.001 ***</td><td>(0.001)</td></tr><tr><td><strong>Individual characteristics</strong></td><td></td><td></td><td></td></tr><tr><td>Female</td><td></td><td></td><td>0.051 ***</td></tr><tr><td>Age</td><td></td><td></td><td>-0.003 ***</td></tr><tr><td><strong>Educational attainment</strong></td><td></td><td></td><td></td></tr><tr><td>Compulsory education<br>(ref. Compulsory education)</td><td></td><td></td><td></td></tr><tr><td>Upper secondary educ.</td><td></td><td></td><td>-0.062 ***</td></tr><tr><td>Tertiary educ.</td><td></td><td></td><td>-0.105 ***</td></tr><tr><td>Unknown</td><td></td><td></td><td>0.009</td></tr><tr><td><strong>Municipality of residence</strong></td><td></td><td></td><td></td></tr><tr><td>Greater Stockholm<br>(ref. Greater Stockholm)</td><td></td><td></td><td></td></tr><tr><td>Greater Gothenburg</td><td></td><td></td><td>-0.132 ***</td></tr><tr><td>Greater Malmö</td><td></td><td></td><td>-0.092 ***</td></tr><tr><td>Medium-sized city</td><td></td><td></td><td>-0.251 ***</td></tr><tr><td>Small city or rural</td><td></td><td></td><td>-0.326 ***</td></tr><tr><td>Average income in neighbourhood (terciles)</td><td></td><td></td><td></td></tr><tr><td>tercile 2</td><td></td><td></td><td>-0.031 ***</td></tr><tr><td>tercile 3 (highest)</td><td></td><td></td><td>-0.053 ***</td></tr><tr><td>McFadden's Adj. R<sup>2</sup></td><td>0.008</td><td>0.009</td><td>0.063</td></tr><tr><td>N</td><td>762 687</td><td>762 687</td><td>762 687</td></tr></tbody></table>

Notes. In these analyses, the sample is restricted to employed individuals. Robust standard errors at the individual level in parentheses. * p < 0.05; ** p < 0.01; *** p < 0.001 (two-tailed).

<caption>Table A7</caption>

Average marginal effects from logistic regressions on the likelihood of living in a vulnerable neighbourhood among second-generation migrants and the Swedish majority population in 2015.

<table><thead><tr><th></th><th colspan="3">Vulnerable neighbourhood</th></tr><tr><th></th><th>(1)</th><th>(2)</th><th>(3)</th></tr></thead><tbody><tr><td><strong>Region of origin (ref. Sweden)</strong></td><td></td><td></td><td></td></tr><tr><td>Finland</td><td>0.044 ***</td><td>(0.005)</td><td>0.037 ***</td></tr><tr><td>Poland</td><td>0.049 ***</td><td>(0.009)</td><td>0.045 ***</td></tr><tr><td>ex-Yugoslavia</td><td>0.070 ***</td><td>(0.012)</td><td>0.054 ***</td></tr><tr><td>Turkey</td><td>0.180 ***</td><td>(0.007)</td><td>0.134 ***</td></tr><tr><td>Middle East</td><td>0.124 ***</td><td>(0.009)</td><td>0.096 ***</td></tr><tr><td>Latin America</td><td>0.097 ***</td><td>(0.008)</td><td>0.092 ***</td></tr><tr><td><strong>Parental socioeconomic status</strong></td><td></td><td></td><td></td></tr><tr><td>Parental educational attainment<br>(ref. Compulsory education)</td><td></td><td></td><td></td></tr></tbody></table>

(continued on next page)
<table><caption>Table A7 (continued)</caption><thead><tr><th></th><th colspan="3">Vulnerable neighbourhood</th></tr><tr><th></th><th>(1)</th><th>(2)</th><th>(3)</th></tr></thead><tbody><tr><td>(ref. Both parents have compulsory educ.)</td><td></td><td></td><td></td></tr><tr><td>One parent has compulsory educ.</td><td></td><td>-0.002 ***</td><td>(0.001)</td></tr><tr><td>Neither parent has compulsory educ.</td><td></td><td>-0.003 ***</td><td>(0.001)</td></tr><tr><td>Parental employment status<br>(ref. Both parents are employed)</td><td></td><td></td><td></td></tr><tr><td>One parent is employed</td><td></td><td>0.005 ***</td><td>(0.001)</td></tr><tr><td>Neither parent is employed</td><td></td><td>0.014 ***</td><td>(0.002)</td></tr><tr><td>Mother's age</td><td></td><td>-0.001 ***</td><td>(0.001)</td></tr><tr><td>Individual characteristics</td><td></td><td></td><td></td></tr><tr><td>Female</td><td></td><td></td><td>-0.001</td></tr><tr><td>Age</td><td></td><td></td><td>-0.001 ***</td></tr><tr><td>Educational attainment<br>(ref. Compulsory education)</td><td></td><td></td><td></td></tr><tr><td>Upper secondary educ.</td><td></td><td></td><td>-0.003 ***</td></tr><tr><td>Tertiary educ.</td><td></td><td></td><td>-0.005 ***</td></tr><tr><td>Unknown</td><td></td><td></td><td>0.002</td></tr><tr><td>Municipality of residence<br>(ref. Greater Stockholm)</td><td></td><td></td><td></td></tr><tr><td>Greater Gothenburg</td><td></td><td></td><td>-0.048 ***</td></tr><tr><td>Greater Malmö</td><td></td><td></td><td>-0.076 ***</td></tr><tr><td>Medium-sized city</td><td></td><td></td><td>-0.084 ***</td></tr><tr><td>Small city or rural</td><td></td><td></td><td>-0.090 ***</td></tr><tr><td>Average income in neighbourhood (terciles)</td><td></td><td></td><td></td></tr><tr><td>tercile 2</td><td></td><td></td><td>-0.066 ***</td></tr><tr><td>tercile 3 (highest)</td><td></td><td></td><td>-0.071 ***</td></tr><tr><td>McFadden's Adj. R<sup>2</sup></td><td>0.033</td><td>0.037</td><td>0.365</td></tr><tr><td>N</td><td>817 517</td><td>817 517</td><td>817 517</td></tr></tbody></table>

Notes. Robust standard errors at the individual level in parentheses. * p < 0.05; ** p < 0.01; *** p < 0.001 (two-tailed).

<caption>Table A8</caption>

Average marginal effects from logistic regressions on the likelihood of living in a migrant-dense neighbourhood among second-generation migrants and the Swedish majority population in 2015.

<table><thead><tr><th></th><th colspan="3">Migrant-dense neighbourhood</th></tr><tr><th></th><th>(1)</th><th>(2)</th><th>(3)</th></tr></thead><tbody><tr><td>Region of origin (ref. Sweden)</td><td></td><td></td><td></td></tr><tr><td>Finland</td><td>0.270 ***</td><td>(0.010)</td><td>0.283 ***</td></tr><tr><td>Poland</td><td>0.345 ***</td><td>(0.017)</td><td>0.322 ***</td></tr><tr><td>ex-Yugoslavia</td><td>0.389 ***</td><td>(0.019)</td><td>0.405 ***</td></tr><tr><td>Turkey</td><td>0.503 ***</td><td>(0.006)</td><td>0.520 ***</td></tr><tr><td>Middle East</td><td>0.499 ***</td><td>(0.009)</td><td>0.506 ***</td></tr><tr><td>Latin America</td><td>0.463 ***</td><td>(0.010)</td><td>0.461 ***</td></tr><tr><td>Parental socioeconomic status</td><td></td><td></td><td></td></tr><tr><td>Parental educational attainment<br>(ref. Both parents have compulsory educ.)</td><td></td><td></td><td></td></tr><tr><td>One parent has compulsory educ.</td><td></td><td>0.020 ***</td><td>(0.002)</td></tr><tr><td>Neither parent has compulsory educ.</td><td></td><td>0.080 ***</td><td>(0.002)</td></tr><tr><td>Parental employment status<br>(ref. Both parents are employed)</td><td></td><td></td><td></td></tr><tr><td>One parent is employed</td><td></td><td>0.011 ***</td><td>(0.002)</td></tr><tr><td>Neither parent is employed</td><td></td><td>0.081 ***</td><td>(0.007)</td></tr><tr><td>Mother's age</td><td></td><td>0.001 ***</td><td>(0.001)</td></tr><tr><td>Individual characteristics</td><td></td><td></td><td></td></tr><tr><td>Female</td><td></td><td></td><td>-0.022 ***</td></tr><tr><td>Age</td><td></td><td></td><td>-0.011 ***</td></tr><tr><td>Educational attainment<br>(ref. Compulsory education)</td><td></td><td></td><td></td></tr><tr><td>Upper secondary educ.</td><td></td><td></td><td>-0.070 ***</td></tr><tr><td>Tertiary educ.</td><td></td><td></td><td>-0.007 **</td></tr><tr><td>Unknown</td><td></td><td></td><td>-0.023 ***</td></tr><tr><td>Municipality of residence<br>(ref. Greater Stockholm)</td><td></td><td></td><td></td></tr><tr><td>Greater Gothenburg</td><td></td><td></td><td>-0.178 ***</td></tr><tr><td>Greater Malmö</td><td></td><td></td><td>-0.074 ***</td></tr><tr><td>Medium-sized city</td><td></td><td></td><td></td></tr><tr><td>Small city or rural</td><td></td><td></td><td></td></tr><tr><td>Average income in neighbourhood (terciles)</td><td></td><td></td><td></td></tr><tr><td>tercile 2</td><td></td><td></td><td>-0.074 ***</td></tr><tr><td>tercile 3 (highest)</td><td></td><td></td><td>-0.074 ***</td></tr><tr><td>McFadden's Adj. R<sup>2</sup></td><td>0.008</td><td>0.012</td><td>0.039</td></tr><tr><td>N</td><td>817 517</td><td>817 517</td><td>817 517</td></tr></tbody></table>

Notes. The regression does not control for municipality of residence due to the high correlation between the dependent and control variable (Pearson's r is 0.47). Robust standard errors at the individual level in parentheses. * p < 0.05; ** p < 0.01; *** p < 0.001 (two-tailed).
<caption>**Table A9**</caption>

Average marginal effects from logistic regressions on the likelihood of being a homeowner among second-generation migrants and the Swedish majority population in 2015.

<table><thead><tr><th rowspan="2"></th><th colspan="6">Homeownership</th></tr><tr><th>(1)</th><th>(2)</th><th>(3)</th></tr></thead><tbody><tr><td><strong>Region of origin (ref. Sweden)</strong></td><td></td><td></td><td></td></tr><tr><td>Finland</td><td>-0.146 ***</td><td>(0.010)</td><td>-0.110 ***</td><td>(0.010)</td><td>-0.054 ***</td><td>(0.008)</td></tr><tr><td>Poland</td><td>-0.146 ***</td><td>(0.018)</td><td>-0.125 ***</td><td>(0.017)</td><td>-0.058 ***</td><td>(0.015)</td></tr><tr><td>ex-Yugoslavia</td><td>-0.150 ***</td><td>(0.020)</td><td>-0.091 ***</td><td>(0.019)</td><td>-0.023</td><td>(0.017)</td></tr><tr><td>Turkey</td><td>-0.086 ***</td><td>(0.008)</td><td>-0.015 *</td><td>(0.007)</td><td>0.058 ***</td><td>(0.005)</td></tr><tr><td>Middle East</td><td>-0.173 ***</td><td>(0.012)</td><td>-0.107 ***</td><td>(0.011)</td><td>-0.020 *</td><td>(0.010)</td></tr><tr><td>Latin America</td><td>-0.315 ***</td><td>(0.012)</td><td>-0.299 ***</td><td>(0.012)</td><td>-0.163 ***</td><td>(0.011)</td></tr><tr><td><strong>Parental socioeconomic status</strong></td><td></td><td></td><td></td></tr><tr><td><em>Parental educational attainment</em><br>(ref. Both parents have compulsory educ.)</td><td></td><td></td><td></td></tr><tr><td>One parent has compulsory educ.</td><td></td><td></td><td>0.013 ***</td><td>(0.002)</td><td>0.003 *</td><td>(0.002)</td></tr><tr><td>Neither parent has compulsory educ.</td><td></td><td></td><td>0.028 ***</td><td>(0.002)</td><td>0.010 ***</td><td>(0.002)</td></tr><tr><td><em>Parental employment status</em><br>(ref. Both parents are employed)</td><td></td><td></td><td></td></tr><tr><td>One parent is employed</td><td></td><td></td><td>-0.074 ***</td><td>(0.002)</td><td>-0.048 ***</td><td>(0.002)</td></tr><tr><td>Neither parent is employed</td><td></td><td></td><td>-0.169 ***</td><td>(0.007)</td><td>-0.107 ***</td><td>(0.006)</td></tr><tr><td>Mother's age</td><td></td><td></td><td>0.005 ***</td><td>(0.001)</td><td>0.001 ***</td><td>(0.001)</td></tr><tr><td><strong>Individual characteristics</strong></td><td></td><td></td><td></td></tr><tr><td>Female</td><td></td><td></td><td></td></tr><tr><td>Age</td><td></td><td></td><td></td></tr><tr><td><em>Educational attainment</em><br>(ref. Compulsory education)</td><td></td><td></td><td></td></tr><tr><td>Upper secondary educ.</td><td></td><td></td><td></td></tr><tr><td>Tertiary educ.</td><td></td><td></td><td></td></tr><tr><td>Unknown</td><td></td><td></td><td></td></tr><tr><td><em>Municipality of residence</em><br>(ref. Greater Stockholm)</td><td></td><td></td><td></td></tr><tr><td>Greater Gothenburg</td><td></td><td></td><td></td></tr><tr><td>Greater Malmö</td><td></td><td></td><td></td></tr><tr><td>Medium-sized city</td><td></td><td></td><td></td></tr><tr><td>Small city or rural</td><td></td><td></td><td></td></tr><tr><td>Average income in neighbourhood (terciles)</td><td></td><td></td><td></td></tr><tr><td>tercile 2</td><td></td><td></td><td></td></tr><tr><td>tercile 3 (highest)</td><td></td><td></td><td></td></tr><tr><td>McFadden's Adj. R<sup>2</sup></td><td>0.002</td><td></td><td>0.010</td><td></td><td>0.081</td><td></td></tr><tr><td>N</td><td>817 517</td><td></td><td>817 517</td><td></td><td>817 517</td><td></td></tr></tbody></table>

Notes. Robust standard errors at the individual level in parentheses. * p < 0.05; ** p < 0.01; *** p < 0.001 (two-tailed).

<caption>**Table A10**</caption>

Average marginal effects from logistic regressions on the likelihood of being in different income quintiles among second-generation migrants and the Swedish majority population in 2015.

<table><thead><tr><th rowspan="2"></th><th colspan="6">Income quintiles</th></tr><tr><th>Quintile 1 (bottom)</th><th>Quintile 2</th><th>Quintile 3</th></tr></thead><tbody><tr><td><strong>Region of origin (ref. Sweden)</strong></td><td></td><td></td><td></td></tr><tr><td>Finland</td><td>0.023 **</td><td>(0.008)</td><td>-0.001</td><td>(0.008)</td><td>-0.001</td><td>(0.008)</td></tr><tr><td>Poland</td><td>0.087 ***</td><td>(0.016)</td><td>-0.046 ***</td><td>(0.014)</td><td>-0.026</td><td>(0.015)</td></tr><tr><td>ex-Yugoslavia</td><td>0.006</td><td>(0.015)</td><td>-0.030 *</td><td>(0.015)</td><td>0.020</td><td>(0.017)</td></tr><tr><td>Turkey</td><td>0.017 **</td><td>(0.006)</td><td>-0.016 *</td><td>(0.006)</td><td>-0.014 *</td><td>(0.007)</td></tr><tr><td>Middle East</td><td>0.032 ***</td><td>(0.010)</td><td>-0.021 *</td><td>(0.009)</td><td>-0.025 *</td><td>(0.010)</td></tr><tr><td>Latin America</td><td>0.079 ***</td><td>(0.010)</td><td>0.032 **</td><td>(0.010)</td><td>0.002</td><td>(0.010)</td></tr><tr><td><strong>Parental socioeconomic status</strong></td><td></td><td></td><td></td></tr><tr><td><em>Parental educational attainment</em><br>(ref. Both parents have compulsory educ.)</td><td></td><td></td><td></td></tr><tr><td>One parent has compulsory educ.</td><td>0.003 *</td><td>(0.001)</td><td>-0.011 ***</td><td>(0.002)</td><td>-0.006 ***</td><td>(0.002)</td></tr><tr><td>Neither parent has compulsory educ.</td><td>0.016 ***</td><td>(0.001)</td><td>-0.028 ***</td><td>(0.001)</td><td>-0.021 ***</td><td>(0.002)</td></tr><tr><td><em>Parental employment status</em><br>(ref. Both parents are employed)</td><td></td><td></td><td></td></tr><tr><td>One parent is employed</td><td>0.048 ***</td><td>(0.002)</td><td>-0.001</td><td>(0.002)</td><td>-0.013 ***</td><td>(0.002)</td></tr><tr><td>Neither parent is employed</td><td>0.106 ***</td><td>(0.006)</td><td>-0.018 ***</td><td>(0.005)</td><td>-0.035 ***</td><td>(0.005)</td></tr><tr><td>Mother's age</td><td>0.002 ***</td><td>(0.001)</td><td>-0.001 ***</td><td>(0.001)</td><td>-0.001 ***</td><td>(0.001)</td></tr><tr><td><strong>Individual characteristics</strong></td><td></td><td></td><td></td></tr><tr><td>Female</td><td>0.109 ***</td><td>(0.001)</td><td>0.139 ***</td><td>(0.001)</td><td>0.013 ***</td><td>(0.001)</td></tr><tr><td>Age</td><td>-0.015 ***</td><td>(0.001)</td><td>-0.007 ***</td><td>(0.001)</td><td>-0.001</td><td>(0.001)</td></tr><tr><td><em>Educational attainment</em><br>(ref. Compulsory education)</td><td></td><td></td><td></td></tr><tr><td>Upper secondary educ.</td><td>-0.160 ***</td><td>(0.002)</td><td>0.014 ***</td><td>(0.002)</td><td>0.042 ***</td><td>(0.002)</td></tr><tr><td>Tertiary educ.</td><td>-0.228 ***</td><td>(0.002)</td><td>-0.031 ***</td><td>(0.002)</td><td>0.034 ***</td><td>(0.002)</td></tr><tr><td>Unknown</td><td>0.498 ***</td><td>(0.005)</td><td>-0.150 ***</td><td>(0.004)</td><td>-0.147 ***</td><td>(0.002)</td></tr><tr><td><em>Municipality of residence</em></td><td></td><td></td><td></td></tr></tbody></table>

(continued on next page)
<table><caption>Table A10 (continued)</caption><thead><tr><th></th><th colspan="6">Income quintiles</th></tr><tr><th></th><th colspan="2">Quintile 1 (bottom)</th><th colspan="2">Quintile 2</th><th colspan="2">Quintile 3</th></tr></thead><tbody><tr><td>(ref. Greater Stockholm)</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Greater Gothenburg</td><td>0.023 ***</td><td>(0.002)</td><td>0.038 ***</td><td>(0.002)</td><td>0.025 ***</td><td>(0.002)</td></tr><tr><td>Greater Malmö</td><td>0.044 ***</td><td>(0.002)</td><td>0.033 ***</td><td>(0.002)</td><td>0.015 ***</td><td>(0.002)</td></tr><tr><td>Medium-sized city</td><td>0.016 ***</td><td>(0.001)</td><td>0.053 ***</td><td>(0.001)</td><td>0.038 ***</td><td>(0.001)</td></tr><tr><td>Small city or rural</td><td>0.010 ***</td><td>(0.001)</td><td>0.056 ***</td><td>(0.001)</td><td>0.040 ***</td><td>(0.001)</td></tr><tr><td>Average income in neighbourhood (terciles)</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>tercile 2</td><td>-0.069 ***</td><td>(0.001)</td><td>-0.026 ***</td><td>(0.001)</td><td>0.004 ***</td><td>(0.001)</td></tr><tr><td>tercile 3 (highest)</td><td>-0.103 ***</td><td>(0.001)</td><td>-0.073 ***</td><td>(0.001)</td><td>-0.034 ***</td><td>(0.001)</td></tr><tr><td>McFadden's Adj. R<sup>2</sup></td><td></td><td>0.081</td><td></td><td>0.052</td><td></td><td>0.009</td></tr><tr><td>N</td><td></td><td>817 517</td><td></td><td>817 517</td><td></td><td>817 517</td></tr></tbody></table><table><thead><tr><th></th><th colspan="6">Income quintiles</th></tr><tr><th></th><th colspan="2">Quintile 4</th><th colspan="2">Quintile 5 (top)</th><th colspan="2"></th></tr></thead><tbody><tr><td>Region of origin (ref. Sweden)</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Finland</td><td>0.002</td><td></td><td>(0.009)</td><td></td><td>-0.020 *</td><td>(0.008)</td></tr><tr><td>Poland</td><td>-0.011</td><td></td><td>(0.015)</td><td></td><td>-0.010</td><td>(0.013)</td></tr><tr><td>ex-Yugoslavia</td><td>0.014</td><td></td><td>(0.018)</td><td></td><td>0.006</td><td>(0.017)</td></tr><tr><td>Turkey</td><td>-0.007</td><td></td><td>(0.007)</td><td></td><td>0.053 ***</td><td>(0.007)</td></tr><tr><td>Middle East</td><td>-0.004</td><td></td><td>(0.010)</td><td></td><td>0.030 **</td><td>(0.010)</td></tr><tr><td>Latin America</td><td>-0.031 ***</td><td></td><td>(0.010)</td><td></td><td>-0.085 ***</td><td>(0.008)</td></tr><tr><td>Parental socioeconomic status</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Parental educational attainment<br>(ref. Both parents have compulsory educ.)</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>One parent has compulsory educ.</td><td>0.002</td><td></td><td>(0.002)</td><td></td><td>0.016 ***</td><td>(0.002)</td></tr><tr><td>Neither parent has compulsory educ.</td><td>-0.003</td><td></td><td>(0.002)</td><td></td><td>0.041 ***</td><td>(0.001)</td></tr><tr><td>Parental employment status<br>(ref. Both parents are employed)</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>One parent is employed</td><td>-0.025 ***</td><td></td><td>(0.002)</td><td></td><td>-0.021 ***</td><td>(0.002)</td></tr><tr><td>Neither parent is employed</td><td>-0.046 ***</td><td></td><td>(0.005)</td><td></td><td>-0.034 ***</td><td>(0.006)</td></tr><tr><td>Mother's age</td><td>-0.001 ***</td><td></td><td>(0.001)</td><td></td><td>0.001 ***</td><td>(0.001)</td></tr><tr><td>Individual characteristics</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Female</td><td>-0.097 ***</td><td></td><td>(0.001)</td><td></td><td>-0.162 ***</td><td>(0.001)</td></tr><tr><td>Age</td><td>0.005 ***</td><td></td><td>(0.001)</td><td></td><td>0.016 ***</td><td>(0.001)</td></tr><tr><td>Educational attainment<br>(ref. Compulsory education)</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Upper secondary educ.</td><td>0.054 ***</td><td></td><td>(0.002)</td><td></td><td>0.052 ***</td><td>(0.001)</td></tr><tr><td>Tertiary educ.</td><td>0.079 ***</td><td></td><td>(0.002)</td><td></td><td>0.145 ***</td><td>(0.002)</td></tr><tr><td>Unknown</td><td>-0.126 ***</td><td></td><td>(0.002)</td><td></td><td>-0.090 ***</td><td>(0.003)</td></tr><tr><td>Municipality of residence<br>(ref. Greater Stockholm)</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Greater Gothenburg</td><td>0.009 ***</td><td></td><td>(0.002)</td><td></td><td>-0.070 ***</td><td>(0.001)</td></tr><tr><td>Greater Malmö</td><td>-0.001</td><td></td><td>(0.002)</td><td></td><td>-0.066 ***</td><td>(0.002)</td></tr><tr><td>Medium-sized city</td><td>0.007 ***</td><td></td><td>(0.001)</td><td></td><td>-0.091 ***</td><td>(0.001)</td></tr><tr><td>Small city or rural</td><td>0.007 ***</td><td></td><td>(0.001)</td><td></td><td>-0.093 ***</td><td>(0.001)</td></tr><tr><td>Average income in neighbourhood (terciles)</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>tercile 2</td><td>0.041 ***</td><td></td><td>(0.001)</td><td></td><td>0.065 ***</td><td>(0.001)</td></tr><tr><td>tercile 3 (highest)</td><td>0.037 ***</td><td></td><td>(0.001)</td><td></td><td>0.171 ***</td><td>(0.001)</td></tr><tr><td>McFadden's Adj. R<sup>2</sup></td><td></td><td>0.023</td><td></td><td></td><td></td><td>0.161</td></tr><tr><td>N</td><td></td><td>817 517</td><td></td><td></td><td></td><td>817 517</td></tr></tbody></table>

Notes. Robust standard errors at the individual level in parentheses. * p < 0.05; ** p < 0.01; *** p < 0.001 (two-tailed).

<caption>Table A11</caption>

Descriptive results of the crosstabulation between homeownership and neighbourhood characteristics, as well as disposable income.

<table><thead><tr><th rowspan="2"></th><th rowspan="2"></th><th rowspan="2"></th><th rowspan="2">Swedish majority group</th><th rowspan="2">All second-generation migrants</th><th colspan="6">Second-generation migrants by region of origin</th><th rowspan="2">Total</th></tr><tr><th>Finland</th><th>Poland</th><th>ex-Yugoslavia</th><th>Turkey</th><th>Middle East</th><th>Latin America</th></tr></thead><tbody><tr><td rowspan="5">Homeowners</td><td>Vulnerable</td><td>Yes</td><td>1</td><td>9</td><td>2</td><td>2</td><td>4</td><td>16</td><td>10</td><td>6</td><td>1</td></tr><tr><td>neighbourhood</td><td>No</td><td>99</td><td>91</td><td>98</td><td>98</td><td>96</td><td>84</td><td>90</td><td>94</td><td>99</td></tr><tr><td>Migrant-dense</td><td>Yes</td><td>26</td><td>70</td><td>50</td><td>57</td><td>67</td><td>81</td><td>79</td><td>70</td><td>27</td></tr><tr><td>neighbourhood</td><td>No</td><td>74</td><td>30</td><td>50</td><td>43</td><td>33</td><td>19</td><td>21</td><td>30</td><td>73</td></tr><tr><td>Median disposable income<br>(in 100 SEK)</td><td></td><td>2 847</td><td>2 743</td><td>2 788</td><td>2 952</td><td>2 738</td><td>2 712</td><td>2 808</td><td>2 602</td><td>2 846</td></tr><tr><td rowspan="5">Non-homeowners</td><td>Vulnerable</td><td>Yes</td><td>4</td><td>18</td><td>12</td><td>12</td><td>16</td><td>26</td><td>19</td><td>15</td><td>4</td></tr><tr><td>neighbourhood</td><td>No</td><td>97</td><td>82</td><td>88</td><td>88</td><td>84</td><td>74</td><td>81</td><td>85</td><td>96</td></tr><tr><td>Migrant-dense</td><td>Yes</td><td>55</td><td>84</td><td>76</td><td>85</td><td>79</td><td>87</td><td>88</td><td>87</td><td>55</td></tr><tr><td>neighbourhood</td><td>No</td><td>45</td><td>16</td><td>24</td><td>15</td><td>21</td><td>13</td><td>12</td><td>13</td><td>45</td></tr><tr><td>Median disposable income<br>(in 100 SEK)</td><td></td><td>2 342</td><td>2 178</td><td>2 159</td><td>2 012</td><td>2 327</td><td>2 250</td><td>2 223</td><td>2 102</td><td>2 339</td></tr></tbody></table>

Notes. Within origin-group percentages are presented.
<figure><img src="image_7.png" /><figcaption>**Fig. A1.** Coefficients from linear probability models on socioeconomic attainment. *Notes*. All origin groups are compared to the Swedish majority group, whose outcomes are indicated by the horizontal line. The baseline model (circles) differentiates between region-of-origin groups. The model that controls for parental SES (diamonds) includes the variables: parental educational attainment, parental employment status and mother's age in 1990. The model that controls for individual characteristics (triangles) additionally includes gender, age, educational attainment, municipality of residence and average income in the neighbourhood of residence in 2015.</figcaption></figure>
Swedish spouse

<figure><img src="image_8.png" /><figcaption>**Fig. A2.** Coefficients from linear probability models on social outcomes. *Notes*. All origin groups are compared to the Swedish majority group, whose outcomes are indicated by the horizontal line. The baseline model (circles) differentiates between region-of-origin groups. The model that controls for parental SES (diamonds) includes the variables: parental educational attainment, parental employment status and mother's age in 1990. The model that controls for individual characteristics (triangles) additionally includes gender, age, educational attainment, municipality of residence and average income in the neighbourhood of residence in 2015.</figcaption></figure>

Migrant-dense workplace

<figure><img src="image_9.png" /></figure>
<figure><img src="image_10.png" /><figcaption>**Fig. A3.** Coefficients from linear probability models on residential attainment. *Notes*. All origin groups are compared to the Swedish majority group, whose outcomes are indicated by the horizontal line. The baseline model (circles) differentiates between region-of-origin groups. The model that controls for parental SES (diamonds) includes the variables: parental educational attainment, parental employment status and mother's age in 1990. The model that controls for individual characteristics (triangles) additionally includes gender, age, educational attainment, municipality of residence and average income in the neighbourhood of residence in 2015.</figcaption></figure>

<figure><img src="image_11.png" /><figcaption>**Fig. A4.** Coefficients from ordinary least squares models on income and the share of migrants in the workplace and the neighbourhood. *Notes*. All origin groups are compared to the Swedish majority group, whose outcomes are indicated by the horizontal line. The baseline model (circles) differentiates between region-of-origin groups. The model that controls for parental SES (diamonds) includes the variables: parental educational attainment, parental employment status and mother's age in 1990. The model that controls for individual characteristics (triangles) additionally includes gender, age, educational attainment, municipality of residence and average income in the neighbourhood of residence in 2015.</figcaption></figure>
<figure><img src="image_12.png" /><figcaption>**Fig. A5.** Average marginal effects from logistic regressions on socioeconomic attainment, stratified by gender. *Notes*. All origin groups are compared to the Swedish majority group, whose outcomes are indicated by the horizontal line. The baseline model (circles) differentiates between region-of-origin groups. The model that controls for parental SES (diamonds) includes the variables: parental educational attainment, parental employment status and mother's age in 1990. The model that controls for individual characteristics (triangles) additionally includes gender, age, educational attainment, municipality of residence and average income in the neighbourhood of residence in 2015. The black colour indicates regressions for males and the grey colour indicates regressions for females.</figcaption></figure>
Swedish spouse

<figure><img src="image_13.png" /><figcaption>**Fig. A6.** Average marginal effects from logistic regressions on social outcomes, stratified by gender. Notes All origin groups are compared to the Swedish majority group, whose outcomes are indicated by the horizontal line. The baseline model (circles) differentiates between region-of-origin groups. The model that controls for parental SES (diamonds) includes the variables: parental educational attainment, parental employment status and mother's age in 1990. The model that controls for individual characteristics (triangles) additionally includes gender, age, educational attainment, municipality of residence and average income in the neighbourhood of residence in 2015. The black colour indicates regressions for males and the grey colour indicates regressions for females.</figcaption></figure>

Migrant-dense workplace

<figure><img src="image_14.png" /></figure>
<figure><img src="image_15.png" /><figcaption>**Fig. A7.** Average marginal effects from logistic regressions on residential attainment, stratified by gender. *Notes*. All origin groups are compared to the Swedish majority group, whose outcomes are indicated by the horizontal line. The baseline model (circles) differentiates between region-of-origin groups. The model that controls for parental SES (diamonds) includes the variables: parental educational attainment, parental employment status and mother's age in 1990. The model that controls for individual characteristics (triangles) additionally includes gender, age, educational attainment, municipality of residence and average income in the neighbourhood of residence in 2015. The black colour indicates regressions for males and the grey colour indicates regressions for females.</figcaption></figure>

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