Differences in migrants’ reason for migration and subjective well-being: not so different after all

Abstract

This article uses 2012–2021 UK survey data to explore differences in subjective well-being (i.e. happiness, anxiety, life satisfaction, and having a worthwhile life) between those born in the UK and foreign-born residents who migrated for different reasons to the country (i.e. employment, study, family reunion, and asylum). Previous literature looking at objective indicators such as employment rates and health suggests that migrants’ reasons for migration relate to major differences across groups in these types of well-being indicators. In contrast, our analysis suggests that differences in subjective well-being with the UK-born are relatively similar across those who migrated for different reasons to the country. Moreover, across reasons for migration, there is a clear pattern of convergence to the subjective well-being levels of the UK-born as length of residence in the UK increases. This differs from studies looking at objective well-being indicators, in which some groups (e.g. those who migrated for family or asylum reasons) take longer to converge to the levels of those born in the country.

Introduction

There is a large literature exploring characteristics of migrants’ life in destination countries, providing insight on how migrants are faring in areas such as employment, housing and health (Brell et al., 2020; Malmusi, 2015; Schneeweis, 2011). Some of these studies consider differences in outcomes which relate to migrants’ reason for migration and highlight that while certain migrants do converge to objective well-being levels of individuals born in the destination country, this is not the case for others (Aydemir, 2011; Connor, 2010; Diaz et al., 2015; Ruiz & Vargas-Silva, 2018).

While the contribution of this literature exploring objective indicators by reason for migration is valuable, it largely ignores the interpretation that individuals make of their own living conditions. This is particularly important in the case of migrants as there could be discrepancies between the dynamics of objective and subjective well-being (SWB). For instance, Stillman et al. (2015) point to a “paradox” whereby migration causes linear improvements in areas such as employment and income, but more complex changes in SWB. A comparison of objective well-being indicators alone, such as employment status, misses these differences in migrants’ subjective appreciation of their well-being in destination countries (Hendriks & Bartram, 2019). There are other illustrations, including in the lead up to the 2022 Qatar FIFA World Cup, which sparked significant controversy concerning migrant workers’ working conditions in the country (Millward, 2017). While the FIFA President claimed immigrant workers should feel a sense of pride and accomplishment for their contribution to a prestigious sporting event, one of these workers stated to a New York Times reporter that “For me, work and money is more important than football” (New York Times, 2022).

As such, the focus of this article is on differences in SWB between individuals born in the country and the foreign-born, focusing on the role of initial reason for migration. We place particular attention on reason for migration as a factor that reflects broader differences across migrants, which range from pre-migration (Bilodeau, 2008; Bürgelt et al., 2008) to post-migration experiences, including expectations about and opportunities for having a fulfilling life in the destination country and social and legal constraints migrants face when making lifestyle choices (Cangiano, 2014; Castelli, 2018; De Jong, 2000).

In this framework, SWB refers to how positively individuals rate the life they lead, and we focus on measures that are widely used in related research. First, on happiness and anxiety as two affective measures, that is, to quantify emotions and feelings of SWB that fluctuate over a short period of time (e.g., yesterday). Second, on life satisfaction and sense that things in life are worthwhile, as, respectively, evaluative and eudemonic measures of SWB. Both capture global assessments individuals make of how their life is going (Diener, 2009).

While there is growing research exploring SWB indicators among migrants (e.g. Bartram, 2011; Hendriks, 2015; Hendriks & Bartram, 2019; Leopold et al., 2017; Safi, 2010), there has been less emphasis on differences in SWB dynamics across reasons for migration. This is the main contribution of this article. In particular, the analysis draws on UK survey data, covering the period from 2012 to 2021 to explore the two following questions. First, what are the differences in subjective well-being between those born in the UK and migrants who migrated for different reasons? Second, how does length of residence in the UK relate to subjective well-being for migrants who migrated for different reasons? The interest for this last question is in determining whether there is a pattern of convergence or divergence to the UK-born SWB.

The UK is an important case study to explore these questions. The country is a major destination for migrants coming for a multitude of reasons (Rienzo & Vargas-Silva, 2022) and is currently redesigning its migration policy priorities as part of the Brexit process (Portes, 2022; Sumption, 2017, 2019). Moreover, the UK is one of few countries collecting nationally representative data on SWB for over a decade, with the stated intention of using SWB evidence for policy purposes (Allin, 2021, Cabinet Office, 2010). Finally, while studies similar to ours highlight that migrants’ SWB is adaptable to conditions in each destination country (Helliwell et al., 2020; Hendriks & Bartram, 2016), there is little evidence on the UK, specifically.

In this context, the remaining sections are organised as follows. "Conceptual considerations and previous findings" section presents key definitions of SWB and a discussion of the current evidence on migrants’ well-being outcomes. "Data and methods" section describes methodological components of this article, while "Results" section discusses the main results. After presenting results from three robustness checks in "Robustness checks" section, "Conclusion" section concludes and suggests implications of these findings.

Conceptual considerations and previous findings

To situate this research, we discuss two strands of the conceptual and empirical literature. The first relates to objective measures of migrants’ well-being, as both differences in objective outcomes across reasons for migration (2.1) and changes related to length of residence in the destination country (2.2). The second focuses on SWB, including a conceptual discussion of SWB measures (2.3) and evidence on migrants’ SWB in destination countries (2.4). We conclude this section by specifying our contribution to the literature (2.5).

Reason for migration and objective well-being outcomes

The conceptual underpinning of the literature exploring the implications of initial reason for migration on well-being outcomes in destination countries has two components. First, that well-being relates strongly to basic human needs (Kanbur et al., 2018; Martela et al., 2023). Therefore, it is important to measure objective indicators in areas such as employment and health to understand how people are doing in their life (Dolan et al., 2008). Second, that each reason for migration reflects a series of factors such as preparedness for migration, experiences during travel to the destination country, legal rights, skills match with the destination labour market, networks, and location in the destination country, among others, that influence how migrants fare in destination countries (Connor, 2010; Demireva & Zwysen, 2020; Kanas & Steinmetz, 2021; Zwysen, 2019). Note that in many countries, migration systems, the majority of which impose strict selection criteria across categories of migrants, amplify differences in objective outcomes across reasons for migration (Aydemir, 2011; Cangiano, 2014).

A recurring finding in high-income countries is that those who migrated for employment and study reasons tend to have better objective outcomes than those who migrated for family and asylum reasons (Brell et al., 2020; Fasani et al., 2022). This is observed on the labour market, for example. In the UK, those who migrated for family reasons have a 15 percentage points employment gap relative to the UK-born. This gap increases to 19 percentage points for asylum migrants, while there is no statistically significant difference between those who migrated for employment reasons and the UK-born (Ruiz & Vargas-Silva, 2018). Evidence that those migrating for asylum have worse labour market outcomes is pointed to in many destination countries. This is likely the result of cumulative processes occurring in home and destination contexts, such as lengthy asylum procedures and uncertain residence statuses (Bevelander & Pendakur, 2014; Brell et al., 2020; Hainmueller et al., 2016).

These differences in objective well-being outcomes by reason for migration are not limited to the labour market (Chiswick et al., 2008; Kaur et al., 2021). In relation to health, Giuntella et al. (2018) estimate that those who migrated to the UK for employment, family and study reasons report better outcomes than the UK-born, while those of asylum migrants are consistently worse. Here, in the same way that different migration routes affect migrants’ objective outcomes in the destination country, coming through different routes impacts migrants’ access to important health care services and subsequent health outcomes (Elstad, 2016; Makarova et al., 2015).

Convergence in migrants’ objective well-being outcomes over time

This literature also considers how differences in migrants’ outcomes across reason for migration change as length of residence in the country increases. For migrants, increasing time spent in the destination country associates with positive outcomes such as familiarity with the labour market (Clark & Lindley, 2009), improved language skills (Dustmann & Fabbri, 2003) and expanded networks (Raghuram et al., 2010), among others factors. These factors help explain the observed convergence in migrants’ outcomes to those of the local-born as length of residence in the destination country increases.

However, this convergence tends to be faster for those who migrated for employment and study reasons, while the gap with asylum migrants takes longer to disappear (Bevelander, 2020; Brell et al., 2020). In the case of labour market outcomes, this convergence typically means higher wages and employment rates for migrants, while in terms of health, convergence materialises as a deterioration in migrants’ health over time (Antecol & Bedard, 2006; McDonald & Kennedy, 2004).

The components of SWB

Our interest is in those subjective reports of well-being of an individual’s conditions that have no direct objective counterparts. The subjective part of well-being considers individuals as “the best judges of their own conditions” (Stiglitz et al., 2009).

It is common to separate SWB into different components, such as evaluative, eudemonic, and experienced components, which capture the different ways in which individuals think about their well-being and which are used in much research in the UK and beyond (Dolan et al., 2011; Waldron, 2010). Evaluative well-being refers to a cognitive assessment a person conducts on their life, all things considered (Diener et al., 1985; Pavot & Diener, 2008). In parallel, eudemonic well-being captures how worthwhile individuals consider their life. Although this is also a life evaluation, a conceptual distinction is that eudaimonia is typically considered independently of any notion of pleasure or satisfaction (Huta & Ryan, 2010; Huta & Waterman, 2014; Ryan & Deci, 2001).

Finally, experienced or affective well-being relates to individuals’ emotions, which fluctuate on the short term, and are qualified in both positive terms, such as joy, happiness, and negative terms, such as sadness, anxiety (Feldman, 2010). Positive (e.g. happiness) and negative (e.g. anxiety) aspects of emotional well-being are generally not considered as opposites of a continuum, but rather as relatively independent (Watson & Clark, 2013). Moreover, while positive emotions are strongly correlated, this is less the case for negative emotions. For example, it is possible to feel sadness, but no anxiety (OECD, 2013). This further indicates that positive and negative affect function as two separate facets of emotions. In "Data and methods" section, we explain how we operationalise indicators from our data to represent each of these SWB components.

Migrants’ subjective well-being

There is a growing literature that considers these SWB outcomes for migrants in destination countries (Bartram, 2011; Hendriks & Burger, 2021; Stillman et al., 2015).¹ An important motivation for this literature is to explore how migrants’ SWB changes as a result of migration and more recently to compare migrants’ SWB to that of the local-born as length of residence in the destination country increases.

From a conceptual perspective, there are several reasons to expect changes in the migrant-local-born SWB gap over time. First, as explained in this "Conceptual considerations and previous findings" section, indicators of migrants’ objective well-being, such as employment likelihood, converge towards that of the local-born. Yet, positive convergence in employment outcomes is often accompanied by a deterioration in other objective outcomes, such a health, and this could lead to a decrease in SWB.

Second, given that many migrants are employed in low-skill jobs in destination countries, this could lead to a deterioration of their SWB. This effect could be aggravated by the cumulative experiences of exclusion and discrimination, which persist across migrant generations and have particularly detrimental implications for how migrants consider their lives overall (Hendriks & Burger, 2020; Melzer & Muffels, 2017; Safi, 2010).

Most studies suggest that migrants report lower levels of SWB than the native-born in early years of residence (Hendriks & Burger, 2020; Obućina, 2013). Reviewing 51 cross-sectional studies comparing SWB of migrants and the native-born, Hendriks (2015) reports a negative SWB gap for migrants in 30 of these. For example, the life satisfaction of immigrants in France is 0.24 points of the 0 to 10 point scale lower than that of the French-born (Safi, 2010). Similarly, immigrants in the Netherlands report 0.21 points lower life satisfaction relative to those individuals born in the Netherlands. This difference decreases to 0.14 for second generation migrants, but remains significant (De Vroome & Hooghe, 2014). Finally, these studies generally indicate that migrants’ SWB converges towards that of the native-born. While this materializes as an upward convergence for migrants with years of residence, migrants’ SWB never fully matches that of native-born (Helliwell et al., 2020; Sachs et al., 2018).

The link between reason for migration and SWB: our contribution to the literature

Having discussed key literature on reasons for migration and SWB, we conclude by explaining our contribution to the literature.

Overall, the evidence highlights significant differences in migrants’ objective well-being outcomes based on reason for migration to the destination country. While this literature is extensive, there has been less emphasis on linking reason for migration with SWB. This omission is important as objective outcomes capture only part of individuals’ well-being.

Next, considering evidence on migrants’ SWB, we find scarce insight on whether patterns of convergence towards the native-born SWB differ for migrants who move for different reasons to the destination country. This perspective would complement well current evidence on migrants’ objective well-being outcomes described above, which points to stark differences across migrant groups that persist over time. Therefore, the current study fills a gap in the literature looking at reason for migration and the literature looking at migrants’ SWB.

Data and methods

Data

The empirical analysis relies on data from the secured version of the Annual Population Survey (APS), provided by the Office for National Statistics’ (ONS) Secure Research Service. The APS is a nationally representative, cross-sectional and continuous household survey, with the largest coverage among all household surveys in the UK. The APS, which combines 2 waves of the main UK Labour Force Survey and national local sample boosts, includes around 320,000 individuals each year. 45% of APS respondents are surveyed for the SWB questions (ONS, 2018).

Since 2010, a question in the APS asks foreign-born respondents about their main reason for coming to the UK. The categories available are employment, study, family reunion, seeking asylum, and other. Note that this question refers to initial reason for migration as opposed to current legal status. For instance, someone who initially migrated for study reasons could be working full-time by the time they are surveyed. As shown in Table 1, most of those in the sample were born in the UK (87%). In this article, those whose country of birth is outside the UK are interchangeably referred to as migrants and foreign-born. The largest migrant group is accounted for by those who migrated for family reasons (35%), followed by employment (33%) and study (16%). Those who migrated for asylum reasons account for just under 7% of all foreign-born.

Table 1 Distribution of the sample

While other surveys in the UK, such as Understanding Society, include some information on SWB and migrant status, the APS has the largest coverage of surveys in the UK. For instance, we have 7,775 observations for those who migrated to seek asylum, the migrant category in our sample with fewer observations. This is particularly important in identifying SWB trends for different groups of migrants, and across different years of residence in the UK.

Since 2011, the APS includes four SWB questions, referring to the different components described in "Conceptual considerations and previous findings" section. The empirical analysis in this article covers an entire decade for which SWB data is available, from 2012 to 2021. SWB questions in the APS all use a 0 to 10 categorical scale where 0 is “not at all” and 10 is “completely”. Specifically, these questions are formulated as follows:

• Overall, how happy did you feel yesterday?

• Overall, how anxious did you feel yesterday?

• Overall, how satisfied are you with your life nowadays?

• Overall, to what extent do you feel that the things you do in your life are worthwhile?

These four questions reflect, respectively, positive affect, negative affect, evaluative and eudaimonic well-being. The scales are harmonised and are used in numerous other surveys worldwide (Diener, 2009; Oishi et al., 2009; Veenhoven et al., 1993). Methodologically, SWB questions are not aggregated into a single measure as each reflects a distinct component.

In all cases, we re-arrange responses such that higher values indicate higher levels of SWB across all variables, hence, facilitating the interpretation of the results. In particular, this means that high values of anxiety reflect a positive well-being outcome, in the same way that high values of happiness suggest a positive well-being outcome.

Table 2 reports the mean values for the SWB indicators. There are important average SWB differences across migrants based on reason for migration. For instance, the life satisfaction of those who migrated for employment reasons (7.71) is higher than that of the UK-born (7.52). In contrast, asylum migrants’ average life satisfaction in our sample is 7.43, which is not only lower than other migrant groups but lower still than the UK-born. In the estimations explained below we explore whether unconditional differences across groups are still present once we control for important covariates.

Table 2 Mean of dependent variables

Methods

The empirical analysis consists of a series of regressions along the following lines:

$$y_{i } = \alpha_{c} + \mathop \sum \limits_{l = 1}^{5} \beta_{l} R_{i} + \beta_{5} O_{i} + \partial X_{i} + L_{j} + T_{t} + \varepsilon_{i}$$

(1)

$$y_{{i{ }}} = \alpha_{c} + \mathop \sum \limits_{k = 1}^{5} \theta_{k} A_{ki} + \partial X_{i} + L_{j} + T_{t} + \varepsilon_{i}$$

(2)

In this case, ${y}_{i}$ is one of the four SWB indicators presented in Table 2 (i.e. happiness, anxiety, life satisfaction and worthwhile life). ${R}_{i}$ indicates one of the reasons for migration (i.e. employment, study, family, asylum) with the base category representing the UK-born (or zero for UK-born respondents). ${\alpha }_{c}$ is the country of birth dummy. Among the variables we control for, country of birth is important since there are cultural and contextual differences in how individuals report SWB (Oishi, 2018; Suh & Koo, 2008). This could affect SWB differences between migrants and the local-born, which we would otherwise conflate with our main focus on reason for migration. ${X}_{i}$ are a series of individual characteristics and ${L}_{j}$ represents the respondent’s local authority of residence in the UK. Historically, there are significant variations across local authorities in numerous aspects such ethnic diversity, unemployment, and access to health services (Lymperopoulou, 2020; Murray et al., 2016). ${T}_{t}$ is time dummy indicating the quarter and year in which a respondent took the survey. Furthermore, we cluster standard errors by survey year throughout the analysis, to reduce the likelihood that our estimates are biased by pooling a decade of survey data. Finally, ${A}_{ki}$ are dummies indicating years of residence in the UK. Table  8 in the Appendix provides a detailed description of the construction of each variable.

In Eq. (1) the focus of the discussion is on the estimated coefficients for ${\beta }_{l}$, which provide information on the differences in self-reported SWB between the UK-born and migrants by reason for migration. In the discussion of the results from estimating Eq. (2), the focus is on ${\theta }_{k}$ which captures information on changes in SWB as length of residence in the UK increases. Equation (2) is estimated for each of the groups in turn (i.e. by reason for migration) relative to the UK-born, in order to facilitate the interpretation. Results of this estimation are presented in graphical form.

Table 3 reports the means for the main independent variables included in the estimation (${X}_{i}$). The controls include gender, age, education, household composition and self-reported health among others.² Importantly, one of the controls is employment status which has been identified as a key factor in explaining individuals’ SWB (Clark & Oswald, 1994; Lucas et al., 2004). Hence, we are exploring differences in SWB by reason for migration as we hold constant a key objective well-being outcome (i.e. employment status). This is particularly important in light of evidence reviewed in "Conceptual considerations and previous findings" section where migrants’ objective outcomes, such as employment, also change over time. Note that the APS does not include data on income, but we include important proxies such as employment status and education in all estimations.

Table 3 Mean of independent variables

Table 3 confirms the differences in objective outcomes discussed in "Conceptual considerations and previous findings" section. For instance, while the employment rate of those who migrated for employment reasons is 87%, this is only 61% for those who migrated for asylum. Furthermore, while 45% of those who migrated for employment rate their health as very good, this is only 35% for those who migrated for family reasons or asylum.

In the remaining sections, we estimate the model using ordinary least squares (OLS), as this is standard in the SWB literature. This literature argues that it is possible to approximate cardinal indicators to continuous indicators in the OLS framework (see for example Hendriks & Burger, 2020; Helliwell et al., 2020).

Results

Differences in SWB are similar across reasons for migration

Table 4 reports the main results from our analysis, which estimates differences in SWB by reason for migration. First, we observe a positive migrant-UK-born gap across reasons for migration for the happiness and worthwhile life indicators. However, none of the coefficients of reason for migration are statistically significant for these indicators. Moreover, while there is some variation, coefficients are for the most part similar in size, around 0.10 points in the 0–10 scale.

Table 4 Association of reason for migration with subjective well-being indicators

On the other hand, the coefficients for anxiety and life satisfaction are negative for all reasons for migration. In the case of the anxiety indicator, the coefficient is statistically significant for those who migrated for employment, study and family reasons, while the point estimate for asylum migrants is just below the 10% cut-off significance level. Since we reverse score the anxiety scale, this indicates that migrants report significantly higher, or worse, anxiety relative to the UK-born.

This anxiety gap is consistent across reasons for migration, but largest in absolute value for those who migrated for study reasons. This group reports worse anxiety outcomes by 0.31 points lower of the 0–10 scale. Even in that case, the differences remain small compared to the unconditional average value of the indicator, which is around 7 for all migrant groups (see Table 2).

There is downward convergence in migrants’ SWB with years of residence

Next, Fig. 1 presents how these dynamics evolve as length of residence in the UK increases for the different groups. In all cases, those born in the UK (zero line) represent the base group.

Fig. 1

Gap between migrants and the UK-born in subjective well-being (Y-axis) for different lengths of residence in the UK (X-axis), by reason for migration. Note: Standard errors clustered by survey year, using unweighted APS data for working age population, 2012–2021. Dotted lines represent 95% confidence intervals. Note that the scale for Anxiety is reversed (i.e. higher values indicate less anxiety)

There are several important dynamics from Fig. 1. First, we observe an initial, positive gap in happiness across all migrant groups, and a similar pattern of convergence towards happiness levels of the UK-born. This same dynamic is present for life satisfaction and also to a large degree for the worthwhile life indicator. The only exception for having a worthwhile life are those who migrated for asylum, for whom there is no convergence towards the UK-born over time, but all coefficients are statistically insignificant.

Second, we observe more variation regarding the anxiety indicators. The point estimates for both family and asylum migrants are initially higher, before converging towards anxiety levels of the native-born. Those who migrated for study reasons also converge to anxiety levels of the UK-born, but start from a lower value in the indicator of anxiety (i.e. worse anxiety), before converging to the UK-born. We do not see convergence in terms of anxiety for those who migrated for employment reasons, but the coefficient is statistically insignificant at all points in time.

That migrants’ SWB converges towards that of natives is a trend which has been found in research elsewhere (Helliwell et al., 2020; Melzer & Muffels, 2017; Sachs et al., 2018). However, these studies generally indicate an upward convergence, while this is not what we observe in Fig. 1 where migrants are disaggregated by reason for migration.

As such, our estimates are surprising given evidence reviewed in "Conceptual considerations and previous findings" section indicating strong gaps in objective well-being outcomes between migrants and native-born residents in the country, based on initial migration reason. We find that this does not translate in SWB outcomes, since there are not only few average SWB differences across migration groups relative to the UK-born, but also similar patterns of downward convergence over time.

Robustness checks

Before concluding, this section presents the results of three robustness checks. In the first check, the analysis is conducted with data up to 2019 only to avoid including the COVID period. There are numerous reports that COVID has substantial implications for individuals’ SWB (Brand et al., 2020; Möhring et al., 2021; Yıldırım & Arslan, 2020). These impacts could be more marked for certain groups of the population such as migrants, who are overrepresented in essential occupations with higher risk of infection (Basso et al., 2022; Bossavie et al., 2022). This is particularly relevant here, given evidence we discussed that reason for migration is strongly related to labour market outcomes in the destination country, including occupation.

In the second check, the sample is restricted to non-EU-nationals, in order to show that the findings hold when excluding those who had freedom of movement prior to Brexit. There is ample evidence that the Brexit process has affected the SWB of EU-nationals in the UK (Benedí Lahuerta & Iusmen, 2021; Martynowska et al., 2020). This could influence the estimated results given the size of the EU migrant population in the UK.

In the third check, we explore whether small, average SWB differences across migration reasons relative to the UK-born are concealing significant differences for those with more extreme SWB outcomes. To do so, we generate a set of dummy variables to indicate that a person provided a response in the top quartile of the sample distribution for each SWB question, thus suggesting having a high level of SWB. Dummy variables for the anxiety question are interpreted in the same direction as dummy variables for happiness, life satisfaction and having a worthwhile life. In Appendix Table 9, we show the distribution of SWB indicators before and after transformation.

Analysis until 2019

As shown in Table 5, limiting the analysis to the pre-COVID period does not have a major impact on the main results. It is still the case that the only significant SWB indicator is that of anxiety, and that the coefficient is negative and similar in size across the different reasons for migration.

Table 5 Association of reason for migration with subjective well-being indicators: excluding COVID period

Analysis excluding EU-nationals

The results are also consistent when excluding EU-nationals from the analysis. In Table 6, the anxiety coefficients are the ones that stand out as statistically significant, thus suggesting a negative SWB gap with the UK-born when using this indicator.

Table 6 Association of reason for migration with subjective well-being indicators: excluding EU-nationals

Analysis using a high well-being threshold

Our main findings are also consistent with estimates in Table 7 that consider high SWB outcomes. First, there are few differences between migrants and the UK-born in reported SWB, even at this more extreme point of the SWB distribution. Second, differences are most marked in relation to anxiety, but these differences are relatively homogenous across migration reasons. In particular, estimates in Table 7 suggest that migrants have a lower likelihood of reporting low levels of anxiety. This gap ranges from 5.4% points (those who migrated for study reasons) to 4.5% points (those who migrated for employment reasons) relative to the UK-born.

Table 7 Association of reason for migration with indicators of high subjective well-being

Conclusion

This article explores differences in SWB between those born in the destination country and migrants who migrated for different reasons. The analysis thus departs from the substantial evidence on differences in objective well-being indicators by reason for migration (Aydemir, 2011) and increasing research on SWB in destination countries (Hendriks & Bartram, 2019), but which does not consider the role of reason for migration.

There are many reasons to expect SWB differences across groups of migrants. In particular, the literature on objective well-being, including evidence for the UK, suggests that reason for migration is a key differentiating factor across migrants which persists along years of residence (Giuntella et al., 2018; Ruiz & Vargas-Silva, 2018).

In contrast, our results suggest that the gap in SWB between the UK-born and migrants is fairly similar across different reasons for migration. Notably, there is no statistically significant gap regarding indicators of happiness, life satisfaction and having a worthwhile life, while there is a negative anxiety gap, regardless of reason for migration. That is, migrants across all reasons for migration are less likely than the UK-born to report low anxiety levels. Excluding COVID years and EU-nationals in the context of Brexit does not affect this main finding. Exploring these patterns as length of residence in the UK increases, we see mainly a convergence of migrants to the SWB indicators of the UK-born, regardless of reason for migration.

Our results are particularly puzzling in that they reveal more commonality across migrant groups in terms of SWB than objective well-being. The results also suggest that there is faster convergence in SWB for migrants compared to objective well-being measures. In all, our analysis highlights the importance of considering SWB indicators in assessing migrants’ living outcomes in destination countries as they clearly provide distinct information. This is particularly important in light of the increasing tendency of governments to change policy objectives from measures of economic production (e.g. GDP), to new measures developed for the purpose of measuring individual well-being (O'Donnell & Oswald, 2015, Costanza et al., 2009).

Finally, our findings open avenues for further research on the higher levels of anxiety reported by migrants across reasons for migration compared to the UK-born. While there is a substantial literature exploring anxiety for refugees given the traumatic experiences lived by many individuals in this group (Henkelmann et al., 2020; Lindert et al., 2009), our analysis suggests higher levels of anxiety across all reasons for migration.

Appendix

See Tables 8 and 9.

Table 8 Definition of all variables included in the estimations

Table 9 Distribution of subjective well-being responses before and after transformation of the variables