Life Satisfaction Among Italian Migrants, Italian Stayers, and Swiss Natives: Who Fares Better? Life Satisfaction Among Italian Migrants, Italian Stayers, and Swiss Natives: Who Fares Better? Iuna Dones Abstract: Although reasons for migration may differ, it can be argued that international migrants have a common goal: improving the living conditions and well-being for themselves and their families. However, we still know relatively little about how older migrants evaluate their well-being and the implications of migration for their life satisfaction. This paper aims to contribute to this body of research. In a fi rst part, we focus on two comparisons: 1) The life satisfaction level of older Italian migrants in Switzerland compared to that of older Swiss natives, and 2) The life satisfaction level of older Italian migrants in Switzerland compared to that of older Italian stayers in Italy. In a second part, we investigate the determinants of life satisfaction in each of these three groups. The article draws on an original survey carried out in Switzerland and Italy (N = 1,654). Against the current comparative literature on older migrants and non-migrants, we hypothesized that older Italian migrants in Switzerland display lower life satisfaction than older Swiss natives, and that older Italian migrants in Switzerland display higher life satisfaction than older stayers in Italy. We expected to observe these differences even when accounting for sociodemographic characteristics. While migrants’ average life satisfaction levels are lower than the levels of Swiss natives, this difference is fully mediated by sociodemographic variables. Migrants also report slightly lower life satisfaction levels than stayers; this difference remains signifi cant at the p<0.1 level but diminishes as we control for sociodemographic characteristics. When investigating the life satisfaction determinants of each group, we fi nd similarities among the three groups: being in good health and being able to make fi nancial ends meet are positively correlated with life satisfaction, while experiencing age-related discrimination is negatively correlated with life satisfaction. Having a partner is only positively correlated with satisfaction for Swiss natives, and religiosity is only positively correlated with satisfaction for stayers. The importance of this paper is threefold: 1) it investigates older migrants’ life satisfaction, an area of research that is underdeveloped, 2) it compares migrants to stayers, a comparison that is seldom found in the current literature but necessary to understand the implications of having a migratory background, and 3) it highlights the importance of policy interventions addressing the socioeconomic inequalities of older migrants. Comparative Population Studies Vol. 48 (2023): 457-492 (Date of release: 21.08.2023) Federal Institute for Population Research 2023 URL: www.comparativepopulationstudies.de DOI: https://doi.org/10.12765/CPoS-2023-18 URN: urn:nbn:de:bib-cpos-2023-18en4 http://www.comparativepopulationstudies.de https://doi.org/10.12765/CPoS-2023-18 • Iuna Dones458 Keywords: Life satisfaction · Older migrants · Migration studies · Quantitative methodology 1 Introduction Migrants are a very heterogeneous group, but they have a similar goal that ties them together: They generally migrate to improve their own lives and that of their families. Migration studies have for long focused on the objective consequences of migration, revealing that migration often results in ameliorated conditions, such as improved economic circumstances (Nikolova/Graham 2015), the possibility of sending remittances to the family in the country of origin (Joarder et al. 2017), and better educational opportunities for children (Zuccotti et al. 2017). However, it is only recently that researchers started studying migrants’ subjective evaluations of their lives. The importance of such focus is rooted in what Graham (2009) calls the “paradox of happy peasants and miserable millionaires”, or the idea that people can lead an objectively good life but still be unhappy (and vice versa). This is because objective measures of well-being do not account for individual differences in the evaluation of objectively similar circumstances (Hendriks/Bartram 2019). In the case of migrants, migration can lead to signifi cant objective improvements, but it can also introduce an array of potentially momentous negative situations in their lives, ranging from separation from social networks in the country of origin, lower socio- economic status in the destination country, discrimination (Hendriks et al. 2018; Hendriks/Bartram 2019), and stress associated with cultural differences (Tabor/ Milfont 2011). These situations may in turn impact migrants’ life satisfaction. Older migrants in particular may experience a series of compounded risks due to age-related issues, migration background (Dowd/Bengtson 1978), and an accumulation of disadvantaged situations throughout their lifetimes (Norman 1985) that may impact their general life satisfaction. Yet, they remain a notably underrepresented population in social science research (Barbiano di Belgiojoso et al. 2022; Baykara-Krumme/Platt 2018). Old age is typically a time when individuals retire or decrease the employment activity for which they fi rst migrated, and it is thus an important period to examine migrants’ material, health, and social conditions, and how these refl ect on their life satisfaction (Baykara-Krumme/Platt 2018). The number of older migrants in European countries is growing (UNDESA 2020), and there is thus increased interest by the scientifi c community in their circumstances (Baykara-Krumme/Platt 2018; Bolzman et al. 2004; Warnes et al. 2004). Here, we focus on older persons in two countries, Switzerland and Italy. After World War II, Switzerland experienced a period of economic expansion and a shortage of local labor, especially of unskilled and semiskilled labor. This led to the establishment of a bilateral agreement with Italy in 1948, which granted for a rotation model in which Italian seasonal workers were allowed to work in Switzerland for a limited period, before returning to Italy. Originally, this labor migration was seen as temporary, but in the 1960s this rotation model was given up, and migrants then Life Satisfaction Among Italian Migrants, Italian Stayers, and Swiss Natives • 459 could settle in Switzerland and could bring over their families (Riaño/Wastl-Walter 2006). Today, Italians aged 65 and older comprise one of the largest groups of foreign resident population in Switzerland (FSO 2020b). Our paper contributes to the literature on older migrant life satisfaction by comparing three groups of older adults: Italian migrants in Switzerland, Swiss natives residing in Switzerland, and Italian stayers residing in Italy. We aim to answer the following research questions: 1) Are there differences in life satisfaction levels between Italian migrants and Swiss natives, and between Italian migrants and Italian stayers? And 2) What are the determinants of life satisfaction among each of these groups? In the next section, we present the theoretical and empirical literature on life satisfaction from which we formulate our hypotheses. We then present the data and our primary results, and discuss the fi ndings. 2 Research on well-being As the world recovered from the physical, social, and psychological devastation brought about by World War II, a new atmosphere arose: one that encouraged commitment to social welfare and a greater appreciation for the individual’s perceptions and viewpoints (Keyes 2006). Movements focused on the importance of personal meaning and concerns about life thus emerged, and subsequently subjective well-being developed as a scientifi c fi eld in the late 1950s when social scientists produced quality of life indicators to observe social change and improve social policy (Keyes 2006). Recent decades have consequently seen a shift in research from negative topics like poverty and illness, to more positive topics like well-being, and a shift from objective to subjective measures of well-being (Bartram 2012). Objective well-being is generally defi ned as “the degree that a life meets explicit standards of the good life, as assessed by an impartial outsider” (Veenhoven 2000: 4), which is generally based on quantifi able indicators like income, health, living conditions, and so on. On the other hand, subjective well-being is defi ned as how people feel about and evaluate their lives, which includes “people’s emotional responses, domain satisfactions, and global judgments of life satisfaction” (Diener et al. 1999: 277). These two variants of well-being are not always correlated, for a person may be in objectively good health but still feel bad (Bartram 2012; Veenhoven 2000). Subjective well-being is further divided into two components: the emotional or affective component, and the cognitive component. The former relates to the extent to which a person experiences pleasant moods and emotions, while the latter relates to the degree to which a person positively evaluates the overall quality of his or her life, and this is commonly referred to as life satisfaction (Veenhoven 2012; Veenhoven/Ehrhardt 1995). In this study, we focus on this latter component – life satisfaction. • Iuna Dones460 2.1 Main factors contributing to life satisfaction Why are people satisfi ed with their lives? Two theoretical approaches have been proposed to explain individual differences in life satisfaction: the top-down approach and the bottom-up approach. The fi rst focuses on the role of individual differences, such as personality traits in life satisfaction, while the second focuses on the role of social contexts, situations, and events in life satisfaction (Erdogan et al. 2012; Heller et al. 2004). In this paper, we adopt the latter perspective, for life satisfaction is linked to the resources individuals develop and access in their lives, to social norms, networks and relationships, and to the social context in which people live (Helliwell/Putnam 2004). More specifi cally, migration – which we will address in more detail below – impacts these sociodemographic characteristics by altering individuals’ networks, affecting their access to resources in the destination country and changing the social context in which they lead their lives. These changes may then infl uence life satisfaction (Hendriks et al. 2018; Hendriks/Bartram 2019). Research on general life satisfaction has shown that income positively correlates to life satisfaction, but only to a certain extent and in certain situations (Bartram 2015; Clark 2011; Clark et al. 2008; de Jong 2015; Deaton 2008). Richard Easterlin (1974; Easterlin/Angelescu 2009) pointed out a paradox in the income-life satisfaction relationship: At one specifi c point in time and in one country, people with higher incomes are on average more satisfi ed with their lives. However, over time, life satisfaction does not increase as the country’s income increases. This is because generally, the life satisfaction gains derived from increases in income are not due to greater purchasing power, but due to an improvement in social status (Bartram 2015; Boyce et al. 2010; Clark et al. 2008). Social comparison thus plays a role, for if everyone’s income increases, there is no gain in social ranking, and thereby no gain in life satisfaction. Another phenomenon that explains Easterlin’s paradox is that of adaptation: Over time, people get habituated to their level of income, so most of the life satisfaction gains from that initial increase disappear (Clark et al. 2018, 2008). Studies have also pointed out that higher levels of education (Cheung/Chan 2009; Clark et al. 2018; Salinas-Jiménez et al. 2011), good health (Clark et al. 2018; Deaton 2008; Helliwell 2003; Helliwell/Putnam 2004; Kööts-Ausmees/Realo 2015), employment (Clark et al. 2018), social capital like marriage and social networks (Amati et al. 2018; Elgar et al. 2011; Helliwell/Putnam 2004), and religiosity (Amit 2010; Clark et al. 2018; Pargament 2002) are positively correlated to life satisfaction. On the other hand, discrimination is negatively correlated to life satisfaction (Bălţătescu 2005; Safi 2010). 2.2 Life satisfaction among migrants Migration can impact income by presenting migrants with better economic opportunities in the destination country, which can positively refl ect on their life satisfaction (Bartram 2011; Hendriks et al. 2018; Nikolova/Graham 2015). Simultaneously, migrants may fi nd themselves in worse socioeconomic conditions than their peers in the host country (Bartram 2011). Over time, migrants may change Life Satisfaction Among Italian Migrants, Italian Stayers, and Swiss Natives • 461 their reference group and may start comparing themselves to wealthier individuals in the host society (Bartram 2011), which can have negative implications for their well-being (Dumludag/Gokdemir 2022). Moreover, migration can disrupt social networks (Arpino/de Valk 2018; Hendriks et al. 2018). Separation from friends and family in the country of origin can result in feelings of loneliness (Cela/Fokkema 2017; Fokkema/Naderi 2013) and social isolation (Hendriks et al. 2018), which are correlated to lower life satisfaction (Ambrosetti/Paparusso 2021; Barbiano di Belgiojoso et al. 2022). Furthermore, having a migratory background can engender discrimination, which has been shown to have deleterious repercussions on migrant well-being (Bălţătescu 2005; Kirmanoğlu/Başlevent 2014; Safi 2010). Migration can also infl uence health (Gerritsen et al. 2013; Lassetter/Callister 2009). Migrants are a self-selected group and are generally in better health than the native-born population, a phenomenon referred to as the “healthy migrant effect” (Domnich et al. 2012; Loi/Hale 2019; Sserwanja/ Kawuki 2020). However, soon after their arrival in the destination country, migrants’ health begins to deteriorate due to the psychological, social and contextual shocks introduced by migration (Domnich et al. 2012; Loi/Hale 2019; McDonald/Kennedy 2004; Sserwanja/Kawuki 2020; Trappolini/Giudici 2021). Migrants’ health can also be impacted by their economic status, as migrants in unfavorable economic conditions report a worse health status compared to migrants in better economic situations (Loi/Hale 2019). Given the complexity of migrants’ situations and the importance of these above- mentioned factors in life satisfaction, the question arises, to what extent and under what circumstances are migrants better off because of migration? 2.2.1 The migrant-native comparison Most studies on adult migrants show that, when comparing life satisfaction of international migrants to that of natives in the destination countries, migrants generally report lower levels than natives, even when accounting for sociodemographic covariates (Arpino/de Valk 2018; Bartram 2011; Hadjar/Backes 2013; Hendriks 2015; Kirmanoğlu/Başlevent 2014; Safi 2010). This can be in part attributed to migrations’ disruptive effect on social relations (Arpino/de Valk 2018), the psycho-social shocks it induces (Safi 2010), as well as migrants’ ability to integrate in the destination country (Hadjar/Backes 2013). Safi (2010) investigated the disparities between fi rst- and second-generation migrants and natives in 13 European countries, and found that second-generation migrants are just as dissatisfi ed as fi rst-generation migrants, and both groups report lower life satisfaction levels than natives. This demonstrates that migrants’ relative dissatisfaction in comparison to natives’ does not diminish over time and across generations. More specifi cally – and relevantly to this paper’s study population – she revealed that, although Switzerland has one of the highest average life satisfaction levels, it is also one of the European countries in which migrants are the least satisfi ed with their lives. This may be due to perception of discrimination and feelings of unfairness. Bartram (2011) focused on migrants in the United States and confi rmed • Iuna Dones462 Safi ’s (2010) fi ndings on the migrant-native difference. Arpino and de Valk (2018) and Hadjar and Beckes (2013) further replicated this migrant-to-native discrepancy across European countries. Furthermore, Hadjar and Beckes (2013) showed that the life satisfaction difference between migrants and natives is higher in countries with a high Gross Domestic Product (GDP) and lower in countries with a higher Migrant Integration Policy Index (MIPEX), suggesting that integration-friendly policies are important to migrant well-being. There are also several studies that found different relationships between life satisfaction and migration status depending on the migration stream and time since migration. Obućina (2013) showed that, in comparison to German natives, Eastern European migrants in Germany are more satisfi ed with their lives, while Turkish-born migrants are less satisfi ed, highlighting the importance of taking into consideration migrants’ heterogeneity. Moreover, some studies revealed that the disparity between native-born Europeans and migrants does not diminish with time or across generations (Amit 2010; Kogan et al. 2018; Safi 2010), while others found that this difference does diminish over generations (Arpino/de Valk 2018). Furthermore, Monteiro and Haan’s (2022) research on migrants in Canada found no difference between the life satisfaction of migrants and that of Canadian natives when controlling for sociodemographic variables, and year of arrival in Canada has no signifi cant effect on life satisfaction. The implications of having a migration background are therefore still unclear, and migration may infl uence life satisfaction differently for different populations. The literature referenced heretofore focuses on migrants of all ages, but there is a particular scarcity in research on the life satisfaction of older migrants (Barbiano di Belgiojoso et al. 2022; Sand/Gruber 2018). The few studies that exist concern people who left their country of origin at different points in their lives and are now aging in their country of destination, and they focus on different migration fl ows as well as different (older) age groups, making it diffi cult to concretely understand the relationship between migration and life satisfaction among this population. Sand and Gruber (2018) found that the difference in life satisfaction levels between older migrants and natives depends on region of origin. They focused on migrants and natives aged 50 and older in 11 European countries and revealed that migrants from Northern and Central Europe have similar satisfaction levels as natives, while Southern European, Eastern European, and non-European migrants report signifi cantly lower levels than the native population, even after controlling for sociodemographic covariates. They also replicated Hadjar and Beckes’ (2013) fi ndings, namely that the migrant-native disparity is larger in countries with low MIPEX scores, one of which is Switzerland; they confi rmed this result among adults aged 50 and over. On the other hand, research by Calvo et al. (2019, 2017), focused on Hispanics and natives aged 60 and older in the United States, showed that older Hispanic migrants in the US report higher life satisfaction levels than both non-Hispanic US natives and Hispanics born in the US, which is in opposition to the majority of the literature comparing migrants and natives. The authors propose that Hispanic migrants compare themselves with peers from their country of origin, which Life Satisfaction Among Italian Migrants, Italian Stayers, and Swiss Natives • 463 explains their higher life satisfaction levels despite their lack of resources vis-à-vis those of US natives and US-born Hispanics. Another explanation is that Hispanic migrants may have strong family support and certain cultural practices that benefi t their life satisfaction. Even though most of the research comparing the life satisfaction of migrants to that of natives shows that migrants display lower life satisfaction levels, these studies often group migrants from several origin countries and migration streams. When differences in migration streams are taken into consideration, research points to more nuanced results, suggesting that the native to migrant comparison is much more complex and needs further investigation. This paper thus aims to add to the limited literature on the life satisfaction of older migrants by analyzing one specifi c migration stream: Italian migrants who migrated to Switzerland early in their lives and who are aging in place. This group of migrants moved to Switzerland primarily between the 1950s and 1970s (Wessendorf 2007), they generally occupied lower-skilled jobs than Swiss natives, have lower education levels, report feeling socially isolated more often, and report a worse health status than natives (Bolzman/Vagni 2018). Based on this and on the existing literature on the relationship between sociodemographic factors and life satisfaction, we expect: (H1a) On average, older Italian migrants in Switzerland have lower life satisfaction levels than older Swiss natives. Moreover, basing ourselves on the migrant-native life satisfaction gap stated in most research to date, and specifi cally on the fi ndings on the larger migrant-to- native disparity in countries with high GDP (Hadjar/Backes 2013) and low MIPEX scores like Switzerland (Hadjar/Backes 2013; Sand/Gruber 2018), as well as the lower life satisfaction levels of migrants from Southern European countries (Sand/ Gruber 2018), we hypothesize that: (H1b) Older Italian migrants in Switzerland display lower life satisfaction levels than older Swiss natives, even when accounting for sociodemographic characteristics. 2.2.2 The migrant-stayer comparison Although comparing life satisfaction of migrants to that of natives is important, some researchers have criticized this comparison, arguing that migrants who move from countries with low life satisfaction levels to countries with higher life satisfaction levels may experience increases in life satisfaction, while remaining below natives’ satisfaction levels (Bartram 2015). The migrant-native comparison thus does not allow for the measurement of change in life satisfaction, and longitudinal data would be optimal to measure this change. However, longitudinal data on international migrants are scarce, so to circumvent this issue, research has compared migrants to • Iuna Dones464 people in the country of origin who did not migrate, referred to as “stayers” (Gruber/ Sand 2022; Hendriks 2015). Hendriks and colleagues (2018) approached the migrant-stayer comparison by matching migrants with demographically similar people in their country of origin who wished to migrate, as well as with demographically similar stayers who had no such desire. They found that most migrants report higher life satisfaction levels post-migration, and that these levels tend to converge to those of natives in the country of destination, though remaining below that of natives. However, their research also demonstrated that for several migration streams, migrants’ life satisfaction did not improve following migration. Erlinghagen (2011) also found that German migrants across Europe show increased life satisfaction levels compared to German stayers. Nikolova and Graham (2015) and Bartram (2013) presented similar results on the migrant-stayer gap, suggesting that migration does improve life satisfaction. Yet, research by the International Organization for Migration (IOM) found that the migrant-stayer comparison is more complex. According to the IOM (2013), migrants who move towards or between developing countries become, in general, less satisfi ed with life. On the other hand, those who move to or between developed countries become more satisfi ed with life. Once again, aforementioned studies focus mainly on younger, working-age migrants, and very few compare older migrants to stayers. Baykara-Krumme and Platt (2018) revealed that older Turkish labor migrants who are now aging in place in several European countries experience higher life satisfaction levels than stayers. Gruber and Sand (2022) similarly reported that migrants from less affl uent to more affl uent European countries are better off than stayers. Despite these two similar results on older migrants, results on the life satisfaction of this population are still sparse, and due to the expanding number of older migrants in Europe, there needs to be further research on their circumstances. Notwithstanding the inconsistent results on the migrant-stayer comparison, considering the two studies focused on older migrants, we hypothesize that: (H2) Older Italian migrants in Switzerland report higher life satisfaction levels than older Italian stayers, even when accounting for sociodemographic variables. 2.2.3 Differences in determinants of life satisfaction In view of the aforementioned studies on the relationship between various socioeconomic characteristics and life satisfaction, we expect similarities in the determinants of life satisfaction among migrants, natives, and stayers. We hypothesize that: (H3) Being in good health is positively correlated with life satisfaction among all three groups. Life Satisfaction Among Italian Migrants, Italian Stayers, and Swiss Natives • 465 (H4) Better economic status is positively correlated with life satisfaction among all three groups. However, we also expect certain differences between the groups. A large part of older Italian labor migrants in Switzerland migrated for economic purposes (Bolzman/Vagni 2018). They migrated from regions of Italy that lacked suffi cient economic opportunities, with the hopes of improving their circumstances (Dones/ Ciobanu 2022). They started their lives in Switzerland in lower skilled jobs, and while a few of them were able to move to better socioeconomic positions, most remained in a lower socioeconomic class in comparison to Swiss natives (Bolzman/ Vagni 2018). Their aspirations for better economic conditions may therefore have gone unmet in the long term, and they may thereby assign more value to their fi nancial situation than natives and stayers, who did not embark on a migration journey to improve their economic circumstances. In support of this theory, a study on migrants in the United States revealed that the association between income and life satisfaction is stronger for migrants than for U.S. natives (Bartram 2011). We therefore hypothesize that: (H5) Financial situation has a greater association with the life satisfaction of migrants than natives. 3 Data and methods 3.1 Data This study draws on an original survey stemming from the project “ Transnational ageing among older migrants and natives: A strategy to overcome vulnerability (TransAge)”, which collected data from four different populations in Switzerland and Italy, all aged 65 and older: a) Swiss natives, born and residing in Switzerland, b) Italian international migrants, born in Southern Italy and residing in Switzerland, c) Italian non-migrants (from here on referred to as “stayers”), and d) Italian internal migrants, born in Southern Italy and residing in Northern Italy. This paper focuses specifi cally on the fi rst three groups. Swiss natives had to meet the following criteria: They had to be born in Switzerland and had to have parents who were also born in Switzerland. Similarly, Italian stayers had to be born in Southern Italy and had to have parents who were born in Italy. Italian international migrants had to be born in Southern Italy and had to have migrated to Switzerland, where they now reside. We chose these populations for several reasons. First, Italians are one of the largest foreign national groups aged 65 and older in Switzerland (FSO 2020a/b). Second, a large part of older Italians migrated to Switzerland between the 1950s and 1970s for economic purposes or to reunite with family members who moved as labor migrants (Bolzman et al. 2004; Riaño/Wastl-Walter 2006; Wessendorf 2007), and most came from regions of Southern Italy that lacked economic opportunities • Iuna Dones466 (Wessendorf 2007). We thus group together migrants of a very specifi c migration stream. Third, comparing migrants from the south of Italy to stayers from the south of Italy allows us to compare individuals who were socialized at a young age in the same place, during the same period, and who thus grew up in similar contexts. All the data were collected through two economic and social research institutes. The institute MIS Trend was responsible for the data collection in Switzerland, while the institute Demetra Opinioni oversaw the data collection in Italy. The sample for Swiss natives and Italian migrants residing in Switzerland was obtained from the Swiss Federal Statistical Offi ce and given to MIS Trend. Since almost 70 percent of the total Italian resident population resides in six Swiss cantons (FSO 2018), data were collected in the following regions: Zurich, Bern, Aargau, Vaud, Geneva, and Ticino. The sample for Italian residents was extracted from the Italian national public telephone directory. Demetra Opinioni contacted the study participants through a method of random telephone calling. Participants had to reside in the following areas of Southern Italy: Abruzzo, Basilicata, Molise, Campania, Sicily, Apulia, Calabria, or Sardinia. For the sample residing in Switzerland, data were collected using two methods: online questionnaires and paper questionnaires, and these were fi lled out in either Italian, French, or German. For the sample living in Italy, data were collected through telephone interviews, and these were conducted in Italian. It could be argued that the different data collection modes between Switzerland and Italy may have led to a certain level of social desirability bias: Italian participants in Italy, who were administered the telephone-based questionnaire, may have answered questions in a manner that may be seen as more desirable to the interviewer (Krumpal 2013). Although some research has found that participants tend to respond to subjective well-being questions less positively in web-mode or paper-mode in comparison to face-to-face mode (Piccitto et al. 2022; Zager Kocjan et al. 2023), this difference does not seem to be universally true (Hendriks et al. 2018). Martin and Lynn (2011), for instance, did not fi nd differences in questions on life satisfaction between face-to-face modes and other interview modes, such as web-based and telephone questionnaires. Furthermore, research comparing paper/web and telephone survey modes, which are the ones used in our study, are scarce. To test for a social desirability bias in subjective well-being indicators, we therefore turned to the Swiss Household Panel (SHP), which is conducted largely by telephone, and compared the results of subjective well-being questions in the SHP to results of the exact same variables in our Swiss sample, collected by paper/web. We did not fi nd evidence of a social desirability bias, so we conclude that our two methods of data collection are indeed comparable. The process and results of this analysis are detailed in the Appendix. Each population sample was stratifi ed by age and gender. The data were collected between June and November 2020, between the fi rst and second wave of infections related to the COVID-19 pandemic. In total, 2,354 older adults participated in the study, of which 689 are Italian international migrants, 836 are Swiss natives, and 829 are Italian stayers. After eliminating missing values for all the dependent and Life Satisfaction Among Italian Migrants, Italian Stayers, and Swiss Natives • 467 independent variables outlined in the next section, we arrive at an analytic sample of 1,655 observations, of which 447 are international Italian migrants, 640 are Swiss natives, and 567 are Italian stayers. At this stage, we deem it important to note that the variable largely responsible for the restricted sample was the one indicating whether participants carried out a physically demanding job, detailed below. To ensure the robustness of our model, we carried out two sensitivity analyses without this variable and we conclude that sample size does not impact our results. Sensitivity analyses are shown in tables A4 and A5 of the appendix. 3.2 Measures 3.2.1 Dependent variable The dependent variable for this study is life satisfaction, measured by the Satisfaction with Life Scale (Diener et al. 1985), a 5-item scale assessing the cognitive dimensions of subjective well-being, and one of the most frequently used scales in subjective well-being research (Maddux 2018). The scale is composed of the following items: 1. In most ways my life is close to my ideal. 2. The conditions of my life are excellent. 3. I am satisfi ed with my life. 4. So far I have gotten the important things I want in life. 5. If I could live my life over, I would change almost nothing. Respondents were instructed to indicate their level of agreement with each item on a 7-point scale, ranging from “1=strongly disagree” to “7=strongly agree”. The answers for each item were then added to create an individual score, ranging from 5 to 35, and in the analysis life satisfaction is kept as a numerical variable. 3.2.2 Independent variables The fi rst main predictor variable is migration status, which consists of the three categories of the three populations being studied: Swiss natives, Italian international migrants residing in Switzerland, and Italian stayers. Along with the main independent variable, we also adjust for several other determinants of life satisfaction based on the existing literature (Bartram 2013, 2012; Hendriks/Bartram 2019; Paparusso 2019; Safi 2010). The sociodemographic variables we include in our analyses are age, gender, level of education, fi nancial situation, relationship status, children, network size, self-rated health, and religiosity. We also control for risk attitudes, age-related discrimination, physically demanding job, and fi nally worry with COVID-19 and COVID-19 related deaths in the region of residence, given that our data were collected during the pandemic. Age is kept as a continuous numerical variable, and gender as a dichotomous categorical variable. Level of education is coded into three categories: “Low”, “Medium” and “High”. Financial situation is measured with the question, “Thinking • Iuna Dones468 of your household’s total income, including all the sources of income of all the members who contribute to it, how diffi cult or easy is it currently for your household to make ends meet?” The fi nal variable includes two answer categories: “Easy” and “Neither easy nor diffi cult/Diffi cult”. We measure fi nancial situation in this way because our data contain too many missing values for the questions related to household income and household savings. Relationship status is a dichotomous variable measuring whether the respondent has a partner. Children is also a dichotomous variable, measuring whether the respondent has any children. Network size is measured by asking respondents to list up to fi ve people who played an important role in their lives in the last 12 months, and these could be family members, friends, colleagues, or anyone else they deemed important (adapted from the question on family confi gurations of Widmer et al. (2013), and (Widmer 2016)). The fi nal variable is numerical, ranging from 0 to 5, and represents the total number of people that played an important role in the participant’s life. To measure self-rated health, we asked respondents to rate their general health on a 5-item Likert scale with the following answer categories: “Very good”, “Good”, “Average/So-So”, “Bad” and “Very bad”. We then recoded responses into two categories: “Good”, which includes the fi rst two answer categories, and “Average/ Bad”, which includes the last three. To measure religiosity, we asked participants how often they pray. Answer categories were “Daily”, “At least once per week”, “At least once per month”, “Less than that”, and “Never”. We then created a dichotomous variable with “Regularly” representing the fi rst three answer categories, and “Not regularly” representing the last two. We control for risk attitude, as being relatively willing to take risks is associated with an increased probability of migrating (Jaeger et al. 2010), and higher risk tolerance is associated with higher life satisfaction (Baláž/Valuš 2020). For this, we asked, “How do you see yourself: in general, are you a person who is risk taking or do you try to avoid risks? Please answer on a scale from 0 to 10, where 0 means ‘Risk avoiding’ and 10 means ‘Taking risks’.” The fi nal variable is kept as numerical. Age-related discrimination is measured by asking respondents how often in the previous 12 months they felt discriminated against or badly treated by anyone because of their age. Answer categories were “Never”, “Rarely”, “Sometimes,” and “Often”. We recoded responses into two categories: “No”, which represents those who responded “Never”, and “Yes”, which includes the other answers. Physically demanding job is evaluated with a dichotomous variable by asking respondents whether their current or last job was physically demanding. To measure COVID-19-related worry, respondents were asked to rate their worry with the pandemic on an 11-point Likert scale, and we kept this as a numerical variable. Lastly, COVID-19 related deaths in the region of residence indicates the total COVID-19 deaths in the respondent’s region of residence per 100,000 citizens that occurred from the beginning of the pandemic until the respondent’s interview. To avoid daily variations, we use the weekly average. For the sample residing in Italy, data for this variable come from offi cial data from the Italian Department of Life Satisfaction Among Italian Migrants, Italian Stayers, and Swiss Natives • 469 Civil Protection and is published daily. For the sample residing in Switzerland, the data come from the Swiss Federal Offi ce of Public Health (Ludwig-Dehm et al. 2023). These two COVID-19 variables are not shown in the fi nal regression models due to their non-signifi cance, but we deem it important to specify that we controlled for them, considering the period when the survey was conducted. When analyzing the life satisfaction determinants for each of the three groups, we also add three migrant-specifi c variables: discrimination due to origin, length of stay in Switzerland, and satisfaction with the migration decision. Origin-related discrimination is measured by asking migrants how often they felt discriminated or badly treated because of their origin in the previous twelve months. Answer categories and recoding are the same as the variable indicating age-related discrimination. The resulting variable is dichotomous, with categories “No” (never) and “Yes” (once or more). Length of stay in Switzerland is a numerical variable measuring how many years they have lived in Switzerland. Satisfaction with the migration decision is a numerical variable ranging from 0 (Not at all satisfi ed) to 10 (Completely satisfi ed). 3.3 Statistical analyses To answer our fi rst research question, we rely on t-tests to compare the means of life satisfaction between the different populations. Then, we compute a series of Ordinary Least Squares (OLS) regressions to estimate the relationship between life satisfaction and various independent variables (Tab. 2). In model 1, we include only the main independent variable: migration status. In model 2, we include age, gender, and economic-related variables, such as making ends meet and level of education. In model 3, we include social network variables, such as relationship status, children, and network size. In model 4, we add health. In model 5 we include the remaining variables described above. We had also run a model with the variables related to COVID-19, but this model is not shown, as it does not help further explain the dependent variable’s variance. We choose to iteratively add these variables to better understand which determinants better explain the difference in life satisfaction between the three study groups. We also ran a multicollinearity test to ensure that no two independent variables are strongly correlated. To answer our second research question, we compute an OLS regression for each of the three populations, including all the variables included in the previous step, as well as the three migrant-specifi c variables described above. We report the standardized coeffi cients of all OLS models in order to determine which variables have the largest association with life satisfaction within and between models. Tables with unstandardized coeffi cients can be found in the Appendix (Tab. A2 and A3). • Iuna Dones470 4 Results 4.1 Description of the samples Descriptive statistics of continuous and categorical variables are shown in Table 1. In all three groups, there are slightly more men than women, but gender differences between groups are not statistically signifi cant. All three groups have a mean age of 74 with similar standard deviations. On other characteristics, the three groups are quite distinct. Stayers for instance have a signifi cantly smaller network than both Italian migrants and Swiss natives. Although this seems counter-intuitive, research has shown that individuals in Southern European countries – including Italy – report fewer people in their social networks, while Switzerland is one of the countries that reports the highest average number of people in the network (Tomini et al. 2016: 9). Moreover, migrants have a signifi cantly lower educational level than both Swiss natives and Italian stayers, and Swiss natives have higher educational levels than stayers. Results also show that natives report being in better health than both migrants and stayers. Natives also report praying less regularly than both other groups, while stayers pray the most among the three groups. In terms of family composition, we observe that a signifi cantly higher proportion of stayers does not have a partner in comparison to both migrants and natives, and that nearly all migrants in our sample (95.8 percent) have children, while there is a higher proportion of natives and stayers without children. We also observe that signifi cantly more migrants held physically demanding jobs in comparison to both natives and stayers. In terms of age-related discrimination, a higher proportion of Swiss natives reports having experienced it during the year preceding the questionnaire in comparison to both migrants and stayers. In relation to migrant-specifi c variables, migrants in our sample have lived in Switzerland for an average of 51.7 years (SD=11.0), with a median length of stay of 54 years (IQR=8.5). Most of them do not report experiencing origin-related discrimination in the prior year. 4.2 Differences in life satisfaction Life satisfaction levels are generally high among all three groups, with migrants reporting a mean life satisfaction score of 26.4 (SD=5.8), stayers reporting a mean of 27.8 (SD=5.8) and natives reporting a mean of 28.2 (SD=4.9). However, there are signifi cant differences. An initial t-test shows that international Italian migrants are signifi cantly less satisfi ed than both Swiss natives and Italian stayers (p<0.01), and no statistical difference exists between natives and stayers. These results confi rm hypothesis (H1a) on the lower mean levels of life satisfaction among migrants in comparison to natives, but also reject hypothesis (H2), which proposed that migrants would report higher life satisfaction levels than stayers in Italy. At fi rst glance, this seems to demonstrate that migrants do not reap the benefi ts of migration, as opposed to what is shown in most of the literature Life Satisfaction Among Italian Migrants, Italian Stayers, and Swiss Natives • 471 It a lia n M ig ra n ts S w is s N a ti v e s It a lia n S ta y e rs V a ri a b le M e a n o r N S D o r % M e a n o r N S D o r % M e a n o r N S D o r % L if e s a ti sf a c ti o n a , b 2 6 .4 * 5 .8 2 8 .2 * 4 .9 2 7. 8 * 5 .8 A g e 74 .4 * 6 .3 74 .6 * 6 .5 74 .6 * 6 .9 N e tw o rk s iz e a , c 3 .5 * 1. 6 3 .7 * 1. 6 1. 4 * 1. 6 R is k a tt it u d e a , b , c 3 .2 * 2 .8 5 .1 * 2 .3 3 .8 * 3 .3 C O V ID -1 9 w o rr y b , c 7. 5 * 2 .7 5 .7 * 2 .7 7. 4 * 3 .0 C O V ID -1 9 D e a th s in R e g io n o f R e si d e n ce a , b , c 4 7. 8 * 3 4 .6 2 1. 1 * 2 3 .1 10 .5 * 8 .0 L e n g th o f st a y 51 .7 * 11 .0 S a ti sf a c ti o n w it h m ig ra ti o n 8 .3 * 1. 8 G e n d e r M a le 2 6 2 5 8 .6 3 7 6 5 8 .8 3 0 3 5 3 .4 F e m a le 18 5 41 .4 2 6 4 41 .2 2 6 4 4 6 .6 E d u c a ti o n a , b , c L o w 2 8 0 6 2 .6 4 7 7. 3 2 16 3 8 .1 M e d iu m 11 9 2 6 .6 3 4 4 5 3 .7 2 10 3 7. 0 H ig h 4 8 10 .7 2 4 9 3 8 .9 14 1 2 4 .9 M a ki n g e n d s m e e ta , b , c D if fi cu lt /N e it h e r 3 2 6 7 2 .9 2 3 1 3 6 .1 3 0 4 5 3 .6 E a sy 12 1 2 7. 1 4 0 9 6 3 .9 2 6 3 4 6 .4 H a v in g a p a rt n e ra , c N o 10 2 2 2 .8 13 2 2 0 .6 19 6 3 4 .6 Y e s 3 4 5 7 7. 2 5 0 8 7 9 .4 3 71 6 5 .4 H a v in g a c h ild a , b N o 19 4 .3 9 7 15 .2 7 8 13 .8 Y e s 4 2 8 9 5 .7 5 4 3 8 4 .8 4 8 9 8 6 .2 H e a lt h b , c A v e ra g e /B a d 2 3 1 51 .7 15 9 2 4 .8 3 14 5 5 .4 G o o d 2 16 4 8 .3 4 8 1 7 5 .2 2 5 3 4 4 .6 T a b . 1: S a m p le d e sc ri p ti v e s ta ti st ic s • Iuna Dones472 It a lia n M ig ra n ts S w is s N a ti v e s It a lia n S ta y e rs V a ri a b le M e a n o r N S D o r % M e a n o r N S D o r % M e a n o r N S D o r % P ra y in g a , b , c N o t re g u la rl y 18 1 4 0 .5 3 6 7 5 7. 3 14 4 2 5 .4 R e g u la rl y 2 6 6 5 9 .5 2 7 3 4 2 .7 4 2 3 74 .6 D e m a n d in g j o b a , b N o 19 9 4 4 .5 4 6 7 7 3 .0 3 9 1 6 9 .0 Y e s 2 4 8 5 5 .6 17 3 2 7. 0 17 6 3 1. 0 A g e -r e la te d d is cr im in a ti o n a , b , c N o 3 8 7 8 6 .6 51 0 7 9 .7 5 2 3 9 2 .2 Y e s 6 0 13 .4 13 0 2 0 .3 4 4 7. 8 O ri g in -r e la te d d is cr im in a ti o n N o 3 8 4 8 5 .9 Y e s 6 3 14 .1 N 4 4 7 6 4 0 5 6 7 T a b . 1: C o n ti n u a ti o n a S ig n ifi c an t d if fe re n ce b e tw e e n m ig ra n ts a n d s ta y e rs b S ig n ifi c an t d if fe re n ce b e tw e e n m ig ra n ts a n d n at iv e s c S ig n ifi c an t d if fe re n ce b e tw e e n n at iv e s an d s ta y e rs * A ri th m e ti c m e an ( n u m e ri c v ar ia b le ) S o u rc e : o w n c al cu la ti o n s b as e d o n T ra n sA g e S u rv e y 2 0 2 0 Life Satisfaction Among Italian Migrants, Italian Stayers, and Swiss Natives • 473 (Bartram 2013; Erlinghagen 2011; Hendriks et al. 2018; Nikolova/Graham 2015). On the contrary, they seem worse off than both natives and stayers. However, Table 2 shows that the difference between the life satisfaction of Italian migrants and Swiss natives is fully mediated by sociodemographic variables, thereby rejecting hypothesis (H1b) and suggesting that, when controlling for covariates known to correlate to life satisfaction, migrants are just as satisfi ed with their lives as natives. In contrast to our predictions in our second hypothesis, migrants are less satisfi ed than stayers, and the difference remains signifi cant at the p<0.1 level, even when accounting for all independent variables. However, the coeffi cient is quite small, especially considering that the life satisfaction score ranges from 5 to 35. Results also show that making ends meet and being in good health are the factors that have the largest positive correlation with life satisfaction, while experiencing Model 1: Model 2: Model 3: Model 4: Model 5: Empty Demographic Social Health Additional & Economic network determinants variables of LS Italian migrants (Ref:) Swiss natives 0.166*** 0.061+ 0.061+ 0.015 0.020 Italian stayers 0.127*** 0.073* 0.085* 0.105** 0.062+ Age 0.041+ 0.059* 0.078** 0.079*** Female (Ref: Male) 0.012 0.033 0.047+ 0.041+ Making ends meet (Ref: 0.244*** 0.241*** 0.218*** 0.198*** Diffi cult/Neither) Education: Medium (Ref: Low) 0.025 0.024 -0.001 -0.002 Education: High 0.032 0.027 0.002 0.002 Having a partner (Ref: No) 0.081** 0.077** 0.070** Child: No (Ref: Yes) 0.004 0.005 0.012 Total network 0.004 0.007 -0.002 Good health (Ref: Average/Bad) 0.256*** 0.237*** Praying regularly (Ref: Not 0.065** regularly) Risk attitudes 0.051* Physically demanding job -0.058* (Ref: No) Discrimination: Age (Ref: No) -0.150*** Observations 1,654 1,654 1,654 1,654 1,654 Adjusted R2 0.018 0.075 0.079 0.137 0.165 Tab. 2: OLS regression: Determinants of life satisfaction; standardized coeffi cients + p<0.1; * p<0.05; ** p<0.01; *** p<0.001 Source: own calculations based on TransAge Survey 2020 • Iuna Dones474 age-related discrimination has the largest negative correlation, and these results are in line with the life satisfaction literature (Clark et al. 2018; Deaton 2008; Helliwell/Putnam 2004; Kööts-Ausmees/Realo 2015). Furthermore, we observe that having a partner, praying regularly, and being more likely to take risks are positively associated with life satisfaction, while having had a physically demanding job is negatively correlated with life satisfaction. Gender, education, having children, and network size are not related to life satisfaction. 4.3 Determinants of life satisfaction by group Since the three groups differ in composition from one another, we then looked at determinants of life satisfaction by group using OLS regressions (Tab. 3). The results show both similarities and differences among the three groups. Consistently with the literature on life satisfaction (Clark et al. 2018; Deaton 2008; Helliwell/Putnam 2004; Kahneman/Deaton 2010), making ends meet and being in good health have the largest positive correlation with life satisfaction across groups, confi rming our third and fourth hypotheses. However, our fi fth hypothesis is rejected; fi nancial situation has a greater association with life satisfaction for Swiss natives in comparison to both migrants and stayers. Having experienced age-related discrimination has the largest negative correlation with life satisfaction across the three populations. However, we also Tab. 3: Determinants of life satisfaction by group, standardized coeffi cients Migrants Natives Stayers Age 0.082+ 0.090* 0.085+ Female (Ref: Male) -0.093+ 0.110** 0.089* Making ends meet (Ref: Diffi cult/Neither) 0.161*** 0.251*** 0.146*** Education: Medium (Ref: Low) 0.031 -0.100 0.032 Education: High -0.031 -0.044 0.015 Having a partner (Ref: No) 0.005 0.163*** 0.026 Child: No (Ref: Yes) 0.046 0.027 -0.019 Total network -0.014 0.048 -0.067 Good health (Ref: Average/Bad) 0.147*** 0.267*** 0.232*** Praying regularly (Ref: No) 0.038 0.053 0.096* Risk attitudes 0.039 0.013 0.055 Physically demanding job (Ref: No) -0.049 -0.027 -0.056 Discrimination: Age (Ref: No) -0.132** -0.107** -0.169*** Discrimination: Origin (Ref: No) -0.060 Length of stay in CH 0.007 Satisfaction with migration 0.302*** Observations 447 640 567 Adjusted R2 0.240 0.221 0.121 + p<0.1; * p<0.05; ** p<0.01; *** p<0.001 Source: own calculations based on TransAge Survey 2020 Life Satisfaction Among Italian Migrants, Italian Stayers, and Swiss Natives • 475 observe certain differences in life satisfaction determinants. Italian migrant women have a slightly lower life satisfaction than migrant men, while women have slightly higher life satisfaction than men in the other two groups. Praying regularly is positively correlated with life satisfaction only among stayers, while having a partner is positively correlated with life satisfaction only for Swiss natives. Finally, for migrants, length of stay and having experienced origin-related discrimination are not correlated to life satisfaction. This may be because most of our sample migrated a long time ago, and only a small percentage experienced origin-related discrimination. Satisfaction with the migration decision is positively correlated to life satisfaction. 5 Discussion National governments have started considering and adopting measures of subjective well-being to inform policy deliberations, and life satisfaction scales provide a valid and reliable assessment of subjective well-being (Diener et al. 2013). Studies on migrants’ life satisfaction are still in their early stages, and the life satisfaction of older migrants is a particularly underdeveloped fi eld of research. Europe is experiencing a growing number of older migrants (Ciobanu et al. 2017), and a large part of this population is comprised of individuals who moved at a young age to the industrial economies of Central and North-West Europe between the 1950s and 1970s, and are now ageing in place (Ciobanu et al. 2017; King et al. 2017). Throughout their lifetimes, they often encountered harsh working conditions, lived in deprived neighborhoods, suffered from worse health status than their native counterparts, and experienced discrimination (Bolzman et al. 2004; Ciobanu et al. 2017; King et al. 2017). These accumulated stressors can have negative implications for their well-being in later life, which presents a health care and welfare challenge for governments around Europe (White 2006). Nonetheless, they are a heterogeneous population: They come from different origin countries, have different cultural backgrounds, and vary in their ability to form networks and integrate in the host country (Ciobanu et al. 2017; King et al. 2017). While existing research often groups migrants from different countries of origin (Arpino/de Valk 2018; Calvo et al. 2017; Monteiro/Haan 2022), we focus on a very specifi c migration stream. This article thus aims to contribute to the scarce literature on older migrant well-being by 1) examining the difference in life satisfaction levels between three groups of older adults: Italian migrants living in Switzerland, Swiss natives, and Italian stayers living in Italy, and 2) analyzing the differences in the determinants of life satisfaction across these three groups. Our study produced somewhat unexpected results. Italian older migrants report lower life satisfaction levels than Swiss natives, which we anticipated, but this difference disappears once sociodemographic variables are considered. This outcome is in contrast to the majority of the research on migrants of all ages (Arpino/de Valk 2018; Hadjar/Backes 2013; Hendriks 2015; Hendriks et al. 2018; Safi 2010), as well as certain studies on older migrants specifi cally (Sand/Gruber 2018). • Iuna Dones476 Despite these contradictions, our results fall in line with the analyses by Monteiro and Haan (2022), who did not fi nd a difference in life satisfaction between migrants and natives in Canada. Older Italian migrants also report slightly lower life satisfaction levels than stayers in the country of origin, contrary to our predictions and in opposition to the existing literature (Baykara-Krumme/Platt 2018; Gruber/Sand 2022). However, a key distinction must be made between these cited studies and ours: Italian migrants in Switzerland are in a worse fi nancial situation than stayers, whereas in Baykara- Krumme and Platt (2018) and Gruber and Sand’s (2022) research, migrants were economically better off than stayers. According to Veenhoven’s (1995) livability theory, conditions that make an environment “livable” relate to life satisfaction. In other words, if human needs are met, life satisfaction increases. Our measure of fi nancial situation encapsulates this factor of “livability” by asking respondents how easy or diffi cult it is to make ends meet. Italian migrants in our sample are in fi nancially less “livable” circumstances, and this refl ects on their lower life satisfaction when compared to stayers. In fact, when socioeconomic variables are introduced in the analyses, the difference in life satisfaction decreases. The migrant- stayer life satisfaction gap further diminishes as other sociodemographic variables are added to the analyses, and although it is rather small, it remains statistically signifi cant to the p<0.1 level. This difference could be attributed to Festinger’s (1954) social comparison theory, which argues that life satisfaction can be infl uenced by comparisons to others. The reference groups to which one compares him or herself can change, and migrants can compare themselves to both people in the country of origin, and people in their destination country (Hendriks 2015). We postulate that the labor migrants in our research may, at least in part, compare themselves to their peers in Italy who they may perceive as holding a higher socioeconomic status. Unlike the migrant groups in other studies, who are fi nancially better off than stayers (Baykara-Krumme/Platt 2018; Gruber/Sand 2022), Italian labor migrants in Switzerland may feel they were not able to fulfi ll the economic aspirations for which they migrated (Bolzman/Vagni 2018), leaving them in worse fi nancial conditions than their peers in Italy. This perception may engender negative evaluations of their migration decision, thus having negative implications for their life satisfaction. Our fi rst set of analyses suggest that migration in itself has little to no correlation to the life satisfaction of older migrants, it is rather sociodemographic characteristics, such as fi nancial situation and health, that most strongly relate to it. In comparison to previous studies on older migrants that focused on individuals who migrated at various points in their lives (Calvo et al. 2017; Hadjar/Backes 2013), most of our respondents have lived in Switzerland for many decades and thus have had the chance to adapt and integrate, so while the disruptive effect of migration may have infl uenced life satisfaction earlier in their life course, it no longer has a substantial relation to the way they evaluate their lives. At the same time, migration played a role in the opportunities and resources that Italian migrants could access in Switzerland. Older Italian migrants in Switzerland moved as labor migrants into a country that provided them little possibility for vertical socio-economic mobility, and this lack Life Satisfaction Among Italian Migrants, Italian Stayers, and Swiss Natives • 477 of opportunities has perpetuated itself throughout the life course (Bolzman/Vagni 2018; Wessendorf 2007), leaving most Italian labor migrants in lower socioeconomic conditions than Swiss natives and thereby having important consequences for their life satisfaction. When looking at the determinants of life satisfaction of each of the three groups, for the most part, the three groups resemble each other. Making ends meet and being in good health are the factors that most positively correlate to life satisfaction, while age-related discrimination negatively relates to it, which is in line with the existing literature (Bartram 2015; Clark et al. 2018; Kang/Kim 2022). However, being able to make ends meet has a greater relation to the dependent variable for natives than for migrants and stayers. Contrary to our hypothesis and to Bartram’s (2011) fi ndings, our results lead us to presume that Swiss natives attribute more value to their fi nancial situation than migrants and stayers. Research has shown that personal values act as mitigating factors in the relationship between income and life satisfaction, and that income plays a greater role in life satisfaction for individuals who hold materialistic values rather than for those who hold intrinsic ones (Georgellis et al. 2009). We therefore deduce that the greater importance of fi nancial situation for Swiss natives is related to their personal values. Our results also show that, in the case of migrants, women report lower life satisfaction levels than men, while for natives and stayers, the relationship between being a woman and life satisfaction is positive. The literature on gender and life satisfaction has been largely inconsistent (Batz-Barbarich/Tay 2018), but a study has found that Southern European female migrants report signifi cantly lower well- being levels than males (Gruber/Sand 2022). This is possibly due to “gender-specifi c acculturative stress as a consequence of the migration decision that is usually taken by the male partner” (Gruber/Sand 2022: 980-981). In fact, a qualitative study focused on older Italian migrants in Switzerland revealed that Italian women often described migration as a passive experience rather than something they actively decided to do (Dones/Ciobanu 2022). We therefore propose that Italian women’s inactive choice in their migration decision plays a role in their life satisfaction. Other determinants of life satisfaction differ across groups. Family ties and social networks are not related to life satisfaction for migrants and stayers, while for Swiss natives, having a partner is positively signifi cant. This might be due to the differing personal values of the groups and might refl ect the weight that natives assign to romantic relationships. Praying regularly is positively related to life satisfaction only among stayers, which is consistent with studies showing that the religion-life satisfaction correlation is stronger in Southern European countries than Western Europe (Georgellis et al. 2009). These differences in determinants of life satisfaction, as well as the greater association between income and life satisfaction among Swiss natives, underline the role that cultural background and personal values play in well-being. These fi ndings do not come without limitations. Although life satisfaction is infl uenced by life events, health, and social relations (to name a few), research has found that about 30 percent of life satisfaction is determined by genes and personality traits (Bartels 2015; Røysamb et al. 2018). This means that a signifi cant • Iuna Dones478 degree of unobserved variance remains present. A way to circumvent this problem would be to control for personality traits; unfortunately, these data were not available in our dataset. Furthermore, it would have been better for the Swiss and Italian data collection to have been carried out using the same survey methods. However, as outlined in the data and methods section, we did not fi nd support for the existence of a social vulnerability bias. Moreover, interview mode has been found to have little to no effect in the association between sociodemographic variables and subjective well- being (Piccitto et al. 2022; Sarracino et al. 2017). For these reasons, we maintain the validity of our results. Cross-sectional studies like this are limited in determining whether migrants gain life satisfaction as a result of migration, and longitudinal studies would be more adequate for analyzing the changes in life satisfaction throughout the migration trajectory. However, longitudinal studies following individuals pre- and post- migration are rare, and it has been argued that the inclusion of stayers in the country of origin provides a good benchmark for understanding the role of migration in life satisfaction (Baykara-Krumme/Platt 2018; Gruber/Sand 2022; Hendriks 2015). Other methodological concerns relate to reverse causality and self-selection: Migration may impact life satisfaction, but at the same time, those with lower levels of life satisfaction may be more likely to migrate (Graham/Markowitz 2011). Moreover, migrants differ from stayers in terms of risk tolerance, wealth, and motivation (Jaeger et al. 2010; Nikolova/Graham 2015). We cannot claim causality, as it can only be determined in experimental designs, nor can we fully exclude a self-selection effect. However, we control for risk tolerance to attempt to minimize it. Lastly, our dataset does not include a variable identifying the specifi c reasons for migration of our participants. Nonetheless, we base ourselves on the existing literature showing that Italian adults who migrated to Switzerland in the 1950s and 1970s – as is the case in most of our sample – migrated out of economic necessity or to reunite with their families who migrated as labor migrants (Bolzman/Vagni 2018; Dones/Ciobanu 2022; Riaño/Wastl-Walter 2006; Wessendorf 2007). This literature has documented the lack of socioeconomic opportunities this population encountered in Switzerland, as we detail above, and it allows us to confi dently discuss our results within the context of this labor migration. 6 Conclusion Despite these limitations, our study reaches important conclusions on the life satisfaction of older migrants who have been living in the host country for decades. Although having a migratory background itself has little to no relation to life satisfaction, older Italian migrants in Switzerland have lower average life satisfaction levels than both Swiss natives and Italian stayers. This is partially because they fi nd themselves in lower socioeconomic positions than both natives and stayers, and these socioeconomic disadvantages play an important role in their life satisfaction. Life satisfaction in later life is expected to originate from the Life Satisfaction Among Italian Migrants, Italian Stayers, and Swiss Natives • 479 opportunities to accumulate resources throughout the life course (Calvo et al. 2019), but older Italian migrants in Switzerland have had less opportunities to accumulate such resources than the native population. This is likely due to path dependency, a concept that holds that “a position in the social space is defi ned by its structure of opportunities and constraints that leads or not to a further step in the life course that engenders new opportunities or new constraints” (Bolzman/Vagni 2018: 68). Although some Italian migrants were able to mobilize their resources and improve their socioeconomic standing, many Italian labor migrants entered Switzerland in low social positions that limited their opportunities for vertical socio-economic mobility (Bolzman/Vagni 2018). These disadvantages accumulated themselves throughout the life course, leaving Italian migrants with limited chances to reduce their socioeconomic inequalities vis-à-vis Swiss natives (Bolzman/Vagni 2018), which in turn had meaningful ramifi cations for migrants’ life satisfaction. Our results call for policies to 1) address the socioeconomic inequalities faced by older migrants, and 2) support programs that promote socioeconomic opportunities for migrants of all ages to ensure the well-being of future older adults, regardless of migratory background. In an increasingly mobile world, our fi ndings on the different determinants of life satisfaction also urge for policymakers to 3) consider the diversity of the population in efforts to promote life satisfaction for all constituents. Acknowledgements The author would like to thank Professor Ruxandra Oana Ciobanu for having provided the author with the possibility to carry out this study, and for her invaluable feedback at every stage of the research article. The author would also like to thank Dr. Sarah Ludwig-Dehm for the creation of the variable measuring COVID-19-related deaths in the region of residence. Additionally, the author would like to thank Professor Claudine Burton-Jeangros and Professor N’Dri Paul Konan for their feedback on this article. The Transnational Ageing dataset analyzed in this study is not yet available publicly. For now, it is available from Ruxandra Oana Ciobanu (Oana.Ciobanu@ hetsl.ch) on reasonable request. The work for this paper was funded by the Swiss National Science Foundation through the Professorship Grant “Transnational Ageing among Older Migrants and Natives: A Strategy to Overcome Vulnerability” coordinated by Prof. Ruxandra Oana Ciobanu (grant number PP00P1_179077/1). 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In: International Review of Sociology 23,1: 27-46. https://doi.org/10.1080/03906701.2013.771049 Zager Kocjan, Gaja; Lavtar, Darja; Sočan, Gregor 2023: The Effects of Survey Mode on Self-Reported Psychological Functioning: Measurement Invariance and Latent Mean Comparison across Face-to-Face and Web Modes. In: Behavior Research Methods 55: 1226-1243. https://doi.org/10.3758/s13428-022-01867-8 Zuccotti, Carolina V.; Ganzeboom, Harry B. G.; Guveli, Ayse 2017: Has Migration Been Benefi cial for Migrants and Their Children?: Comparing Social Mobility of Turks in Western Europe, Turks in Turkey, and Western European Natives. In: International Migration Review 51,1: 97-126. https://doi.org/10.1111/imre.12219 Date of submission: 12.12.2022 Date of acceptance: 29.06.2023 Iuna Dones (). University of Applied Sciences and Arts Western Switzerland, Faculty of Social Work (HETSL / HES-SO), Swiss Centre of Expertise in Life Course Research, University of Geneva. Institute of Sociological Research (ISR), University of Geneva. Geneva, Switzerland. E-mail: Iuna.Dones@hetsl.ch URL: https://www.hetsl.ch/cv/iuna-dones/ https://doi.org/10.1017/S0144686X04002296 https://doi.org/10.1080/13691830701541614 https://doi.org/10.1080/13691830600927708 https://doi.org/10.4324/9781315581903 https://doi.org/10.1080/03906701.2013.771049 https://doi.org/10.3758/s13428-022-01867-8 https://doi.org/10.1111/imre.12219 mailto:Iuna.Dones@hetsl.ch https://www.hetsl.ch/cv/iuna-dones/ Life Satisfaction Among Italian Migrants, Italian Stayers, and Swiss Natives • 487 Appendix Testing for social desirability bias To address the issue of differing data collection methods and the possibility of a social desirability bias when measuring subjective well-being indicators, we turned to the Swiss Household Panel (SHP). It is a unique and nationally representative longitudinal study in Switzerland that is mostly carried out through computer- assisted telephone interviewing (Tillmann et al. 2022). The SHP includes fi ve subjective well-being variables that are identical to the ones included in the TransAge project, although these are not included in the main portion of this article. These fi ve variables concern satisfaction with the following life domains: 1) Satisfaction with state of health, 2) Satisfaction with leisure time activities, 3) Satisfaction with personal, social, and family relationships, 4) Satisfaction with accommodation, and 5) Satisfaction with the fi nancial situation of the household. Each of these is measured on a scale from 0 to 10, where 0 means not at all satisfi ed, and 10 means completely satisfi ed. Since these measures of subjective well-being are strongly linked to life satisfaction (Heller et al. 2004), they should respond to the introduction of a social desirability bias in the same way that life satisfaction questions would. If telephone interviewing leads to a social desirability bias, we would expect the mean of each of these variables to be signifi cantly greater among the SHP sample than among the sample of Swiss natives in the TransAge project. To test this, we took wave 22 of SHP data collected between September 2020 and February 2021, which overlaps with the period of data collection done in the TransAge survey. To compare SHP data to Swiss natives in TransAge data, we restricted the SHP sample to include only individuals who completed the survey by telephone, were 65 years old or older at the time of interview, have Swiss nationality, have parents who also have Swiss nationality, and live in the cantons of Zurich, Ticino, Bern, Aargau, Vaud, or Geneva. The resulting SHP sample consists of 1,343 individuals. We then computed the mean of each aforementioned subjective well-being variable for the SHP sample and for the TransAge sample and carried out a Wilcoxon rank-sum test to test whether the difference between the two samples is statistically signifi cant. The results of this analysis are in Table A1. Although the difference between the samples is statistically signifi cant for four out of the fi ve variables, it does not support the social desirability bias hypothesis, as the SHP sample, collected through telephone interviews, presents lower subjective well-being than the paper/web sample. We therefore maintain that our data collected in Italy and Switzerland are comparable due to the lack of evidence supporting the existence of a social desirability bias. • Iuna Dones488 Tab. A1: Social desirability bias testing: SHP and TransAge subjective well-being variables Variable SHP mean TransAge mean P (N=1,343) (N=836) Satisfaction health 7.617 (SD = 1.69) 7.966 (SD = 1.80) p < 0.01*** Satisfaction leisure 8.44 (SD = 1.70) 8.40 (SD = 1.79) p = 0.89 Satisfaction relationships 8.48 (SD = 1.35) 8.73 (SD = 1.43) p < 0.01*** Satisfaction accommodation 8.82 (SD = 1.30) 9.06 (SD = 1.29) p < 0.01*** Satisfaction fi nances 8.27 (SD = 1.70) 8.36 (SD = 1.88) p < 0.05** Source: Swiss Household Panel, 2020; TransAge Survey 2020 Life Satisfaction Among Italian Migrants, Italian Stayers, and Swiss Natives • 489 M o d e l 1 : M o d e l 2 : M o d e l 3 : M o d e l 4 : M o d e l 5 : E m p ty D e m o g ra p h ic & S o ci a l n e tw o rk H e a lt h A d d it io n a l E co n o m ic d e te rm in a n ts v a ri a b le s o f L S It a lia n m ig ra n ts ( R e f. ) S w is s n a ti v e s 1. 8 6 9 * * * 0 .6 8 3 + 0 .6 8 4 + 0 .1 7 2 0 .2 2 0 It a lia n s ta y e rs 1. 4 6 6 ** * 0 .8 4 9 * 0 .9 8 6 * 1. 2 17 ** 0 .7 17 + A g e 0 .0 3 5 + 0 .0 4 9 * 0 .0 6 5 ** 0 .0 6 6 * * * F e m a le ( R e f: M a le ) 0 .1 2 9 0 .3 6 4 0 .5 2 3 + 0 .4 5 9 + M a ki n g e n d s m e e t (R e f: D if fi cu lt /N e it h e r) 2 .6 8 7 * * * 2 .6 4 5 * * * 2 .3 9 2 * * * 2 .1 7 6 * * * E d u c a ti o n : M e d iu m ( R e f: L o w ) 0 .2 8 3 0 .2 7 0 -0 .0 10 -0 .0 2 8 E d u c a ti o n : H ig h 0 .3 9 4 0 .3 3 8 0 .0 2 3 0 .0 2 2 H a v in g a p a rt n e r (R e f: N o ) 1. 0 19 ** 0 .9 6 8 ** 0 .8 7 3 ** C h ild : N o ( R e f: Y e s) 0 .0 61 0 .0 9 4 0 .2 10 T o ta l n e tw o rk 0 .0 10 0 .0 2 1 -0 .0 0 6 G o o d h e a lt h ( R e f: A v e ra g e /B a d ) 2 .8 3 9 ** * 2 .6 3 2 ** * P ra y in g r e g u la rl y ( R e f: N o t re g u la rl y ) 0 .7 2 8 ** R is k a tt it u d e s 0 .0 9 6 * P h y si c a lly d e m a n d in g j o b ( R e f: N o ) -0 .6 6 7 * D is cr im in a ti o n : A g e ( R e f: N o ) -2 .3 5 6 ** * C o n st a n t 2 6 .3 5 8 * * * 2 2 .8 9 2 * * * 2 0 .9 18 * * * 18 .4 6 9 * * * 18 .6 8 5 * * * O b se rv a ti o n s 1, 6 5 4 1, 6 5 4 1, 6 5 4 1, 6 5 4 1, 6 5 4 A d ju st e d R 2 0 .0 18 0 .0 7 5 0 .0 7 9 0 .1 3 7 0 .1 9 5 T a b . A 2 : O L S r e g re ss io n : D e te rm in an ts o f lif e s a ti sf a c ti o n , u n st an d a rd iz e d c o e ffi c ie n ts + p < 0 .1 ; * p < 0 .0 5 ; ** p < 0 .0 1 ; ** * p < 0 .0 0 1 S o u rc e : o w n c al cu la ti o n s b as e d o n T ra n sA g e S u rv e y 2 0 2 0 • Iuna Dones490 Tab. A3: Determinants of life satisfaction by group, unstandardized coeffi cients Migrants Natives Stayers Age 0.075+ 0.067* 0.071+ Female (Ref: Male) -1.088+ 1.094** 1.029* Making ends meet (Ref: Diffi cult/Neither) 2.087*** 2.556*** 1.680*** Education: Medium (Ref: Low) 0.410 -0.983 0.376 Education: High -0.587 -0.440 0.194 Having a partner (Ref: No) 0.069 1.964*** 0.319 Child: No (Ref: Yes) 1.326 0.369 -0.321 Total network -0.051 0.149 -0.245 Good health (Ref: Average/Bad) 1.703*** 3.018*** 2.684*** Praying regularly (Ref: Not regularly) 0.451 0.519 1.262* Risk attitudes 0.082 0.028 0.098 Physically demanding job (Ref: No) -0.574 -0.295 -0.691 Discrimination: Age (Ref: No) -2.229** -1.300** -3.640*** Discrimination: Origin (Ref: No) -0.989 Length of stay in Switzerland 0.004 Satisfaction with migration 0.982*** Constant 11.732** 17.382*** 19.257*** Observations 447 640 567 Adjusted R2 0.240 0.221 0.121 Source: own calculations based on TransAge Survey 2020 Life Satisfaction Among Italian Migrants, Italian Stayers, and Swiss Natives • 491 M o d e l 1 : M o d e l 2 : M o d e l 3 : M o d e l 4 : M o d e l 5 : E m p ty D e m o g ra p h ic S o ci a l n e tw o rk H e a lt h A d d it io n a l & E co n o m ic d e te rm in a n ts v a ri a b le s o f L S It a lia n m ig ra n ts ( R e f. ) S w is s n a ti v e s 1. 7 6 7 * * * 0 .5 5 9 0 .5 51 0 .0 3 6 0 .1 8 6 It a lia n s ta y e rs 1. 3 9 9 ** * 0 .7 4 5 * 0 .9 2 1 * 1. 10 4 ** 0 .7 11 + A g e 0 .0 3 7 + 0 .0 5 2 ** 0 .0 6 7 * * * 0 .0 6 9 * * * F e m a le ( R e f: M a le ) 0 .0 3 8 0 .2 6 2 0 .4 3 1 0 .3 71 M a ki n g e n d s m e e t (R e f: D if fi cu lt /N e it h e r) 2 .7 61 ** * 2 .7 17 ** * 2 .4 71 ** * 2 .3 2 6 ** * E d u c a ti o n : M e d iu m ( R e f: L o w ) 0 .2 5 8 0 .2 4 3 0 .0 19 0 .0 8 3 E d u c a ti o n : H ig h 0 .3 2 9 0 .2 6 9 -0 .0 0 7 0 .1 4 5 H a v in g a p a rt n e r (R e f: N o ) 1. 0 2 2 ** 0 .9 71 ** 0 .8 8 5 ** C h ild : N o ( R e f: Y e s) 0 .1 4 9 0 .1 5 6 0 .2 8 9 T o ta l n e tw o rk 0 .0 2 8 0 .0 3 7 0 .0 0 9 G o o d h e a lt h ( R e f: A v e ra g e /B a d ) 2 .7 2 5 ** * 2 .5 5 6 ** * P ra y in g r e g u la rl y ( R e f: N o t re g u la rl y ) 0 .8 15 ** R is k a tt it u d e s 0 .0 9 6 * D is cr im in a ti o n : A g e ( R e f: N o ) -2 .4 8 0 ** * C o n st a n t 2 6 .3 5 8 ** * 2 2 .8 3 9 ** * 2 0 .7 8 3 ** * 18 .4 5 6 ** * 18 .1 0 4 ** * O b se rv a ti o n s 1, 7 71 1, 7 71 1, 7 71 1, 7 71 1, 7 71 A d ju st e d R 2 0 .0 17 0 .0 7 7 0 .0 8 1 0 .1 3 5 0 .1 6 3 T a b . A 4: S e n si ti v it y a n a ly si s 1 w it h o u t p h y si ca lly d e m an d in g jo b v a ri a b le , u n st an d a rd iz e d c o e ffi c ie n ts + p < 0 .1 ; * p < 0 .0 5 ; ** p < 0 .0 1 ; ** * p < 0 .0 0 1 S o u rc e : o w n c al cu la ti o n s b as e d o n T ra n sA g e S u rv e y 2 0 2 0 • Iuna Dones492 Tab. A5: Sensitivity analysis 2 without physically demanding job variable, unstandardized coeffi cients Migrants Natives Stayers Age 0.069+ 0.069** 0.077* Female (Ref: Male) -1.097* 0.905* 1.014+ Making ends meet (Ref: Diffi cult/Neither) 2.218*** 2.724*** 1.687*** Education: Medium (Ref: Low) 0.528 -0.925 0.413 Education: High -0.460 -0.499 0.320 Having a partner (Ref: No) 0.117 1.978*** 0.302 Child: No (Ref: Yes) 1.057 0.482 -0.276 Total network -0.089 0.163 -0.224 Good health (Ref: Average/Bad) 1.725*** 2.777*** 2.707*** Praying regularly (Ref: Not regularly) 0.582 0.468 1.379* Risk attitudes 0.068 0.026 0.109 Discrimination: Age (Ref: No) -2.445** -1.351** -3.610*** Discrimination: Origin (Ref: No) -1.283+ Length of stay in CH 0.001 Satisfaction with migration 0.928*** Constant 12.664*** 17.234*** 18.358*** Observations 503 697 571 Adjusted R2 0.244 0.217 0.118 Source: own calculations based on TransAge Survey 2020 Published by Federal Institute for Population Research (BiB) 65180 Wiesbaden / Germany Managing Publisher Dr. Nikola Sander 2023 Editor Prof. Frans Willekens Managing Editor Dr. Katrin Schiefer Editorial Assistant Beatriz Feiler-Fuchs Wiebke Hamann Layout Beatriz Feiler-Fuchs E-mail: cpos@bib.bund.de Scientifi c Advisory Board Kieron Barclay (Stockholm) Karsten Hank (Cologne) Ridhi Kashyap (Oxford) Natalie Nitsche (Rostock) Alyson van Raalte (Rostock) Pia S. 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