## Abstract

International migration that is motivated by the striving for a better life is growing explosively. Migrants and policymakers would benefit from knowing whether migrants’ outcomes reflect their aims and expectations. Quantitative research that examines the happiness of migrants has been performed in different academic disciplines (e.g. psychology, sociology, and economics). The spread of research over various disciplines has restricted researchers from reaching overall conclusions on the following issues: (1) do migrants become happier? and (2) do migrants become as happy as ‘natives’ in the host country? This paper integrates the interdisciplinary findings on these questions in a systematic review of the research findings (44 studies; migrant sample > 70,000). In answer to the first question, the review reveals that migrants can become happier by migrating but it strongly depends on the specific migration stream. In answer to the second question, migrants typically did not reach similar levels of happiness to those of natives. Recommendations for future research are provided.

## 1. Introduction

Human migration has been a ubiquitous phenomenon since the beginning of humanity. A wide variety of people perceive the opportunity to choose one’s place to live as a valuable tool for improving one’s life. Migration to another country is one of the most impactful decisions in life as migration breaks the systematic patterns in which people live their lives. Changes can occur in the work sphere, in social life, and in the external environment, among others. Reflecting its importance, the decision to emigrate is typically a thoroughly evaluated choice that is driven by principal motivators in life. Recent research has shown that migrants have little worry over guaranteeing basic survival needs; they move because they feel relatively unhappy compared to people with similar socio-economic characteristics and feel restricted in offsetting this gap when staying in their country of origin ( Graham and Markowitz 2011 ; Otrachshenko and Popova 2014 ; Chindarkar 2014 ). This finding concurs with well-being studies that argue that a satisfactory and joyful life becomes a powerful behavioural driver when the survival motive is satisfied (e.g. Diener 2000 ). Correspondingly, the IOM (2013 : 75) concluded in the 2013 World Migration Report that ‘The most fundamental questions they (i.e. migrants) must ask themselves, therefore, are whether they will be happier if they migrate and whether their life will be better than it is now’ . An interesting query is whether it is realistic for migrants to expect greater happiness due to emigrating.

This query has become more prominent in recent decades as geographical mobility has increased. The number of people living outside of their home countries rose from 75 million in 1975 (representing 2.2 per cent of the world population) to 150 million in 2000, reaching 214 million in 2010 (representing 3.1 per cent of the world population), and an estimated 405 million people will have migrated by 2050 ( IOM 2010 ). This upward trend promotes the expectancy that migration is a viable strategy to improve one’s life. Millions of people would not have opted for emigration if they had not expected it to boost their happiness, right?

This is an ostensibly sound question that challenges the value of studying individuals’ migration outcomes. However, people face difficulties in predicting the outcomes of choices and therefore frequently make suboptimal decisions ( Kahneman 2011 ). Even the most important and thoughtful choices in people’s lives are not immune to these forecasting biases ( Frederick and Loewenstein 1999 ), to which the migration decision is no exception ( Schkade and Kahneman 1998 ). The most prominent cause of the forecasting bias among migrants is the failure to anticipate that the improved circumstances lose their effect over time after the initial ‘migration honeymoon period’. In particular, comparison groups and aspiration levels gradually adapt to the new circumstances. An interesting paradox conveyed by Bălţătescu (2007) is that immigrants who experience improved objective well-being do not by definition experience improved subjective well-being, and vice versa. This paradox concurs with the findings in broader well-being literature that satisfying strong external drivers often does not result in the increase in happiness aspired to. Due to forecasting biases, people are overly driven to improve external (often pecuniary) circumstances ( Frey and Stutzer 2014 ). Ironically, non-pecuniary factors are the ones that lastingly affect happiness ( Headey 2010 ). This implies that migrants undervalue the negative effects of relinquishing intrinsic factors such as social capital and cultural identity ( Portes 2000 ). A final issue is that following migration, a sizeable proportion of migrants conclude that they had been overly optimistic about their chances of obtaining their desired living conditions in their place of settlement ( Benson and O’Reilly 2012 ; Mähönen, Leinonen and Jasinskaja-Lahti 2013 ). They mistakenly believed that the grass is greener on the other side ‘of the border’, frequently combined with overconfidence in their abilities to exploit potential advantages. Taken together, the forecasting biases can result in fruitless, or even backfiring, attempts at migration.

### 1.1 The present study

This paper evaluates whether migrants’ biases in decision-making processes lead to suboptimal decisions, or whether the increasing migration streams reflect the positive outcomes experienced by migrants. Concurrently, a related issue that has been debated in previous literature is tested: the debate is whether migrants completely progress towards the happiness levels of natives in the destination country over time, as assimilation theories suggest ( Esser 2010 ), or whether differences remain as suggested by recent studies, for instance because of the ongoing influence of one’s heritage ( Senik 2011 ; Voicu and Vasile 2014 ).

Briefly stated, the current paper addresses the following two questions: A number of empirical studies have addressed these questions. However, the field has remained exceptionally data-driven and multidisciplinary, which has resulted in a dispersed field in which few scholars build on each other’s work. The current paper conducts a systematic review of research findings that unites findings on this topic in, among others, two specific fields (subjective well-being and migration) and three broader disciplines (psychology, sociology, and economics). A systematic review is preferred over a meta-analysis because the number of studies is insufficient to conduct a meta-analysis that accounts for the factors that cause contingent outcomes across migration streams. The two focal questions addressed in this article have been raised in a valuable book chapter of Simpson (2013) . The current paper extends Simpson’s work in two ways. First, whereas Simpson discusses only a subset of papers, I use a systematic and interdisciplinary approach in which, to my knowledge, all relevant scientific publications are included that remain within the boundaries of the review (see section 3.2). The comprehensive overview of the literature allows for evidence-based inferences. The second contribution is the provision of a schematic and detailed overview of the included studies and their features. For each study, features of the researched migration stream and the utilized methodology are presented.

1. Do migrants become happier?

2. Do migrants become as happy as natives in the host country?

The next section defines the constructs of interest and discusses methodological issues in studying the outcomes of migrants. The third section presents the review strategy. The fourth section presents and discusses the findings of the review. The final section concludes the paper and discusses avenues for future research.

## 2. Conceptual and methodological issues

### 2.1 The concept of happiness

The following two sources of information are used to assess one’s happiness: (1) how well one feels most of the time, and (2) to what extent one perceives oneself as obtaining what one wishes from life. The first component is affective in nature and is commonly referred to as the ‘hedonic level of affect’. The second component is cognitive in nature and is known by academics as ‘contentment’. Happiness is measured by various self-report questions that are diverse in their main focus. The three main categories of self-reports comprise one or multiple questions about (1) satisfaction with life as a whole (in which contentment with life plays a primary role), (2) experienced emotions (the balance of experienced positive and negative affect), and (3) general happiness (which combines the cognitive and affective components). The way happiness is measured impacts the outcome, for instance because contentment is stronger related to one’s personal circumstances than affect ( Lucas, Diener and Suh 1996 ). To promote accurate inferences, the exact measure used by each study is listed when presenting the results.

### 2.2 Methodological issues in assessing the effect of migration on happiness

The measurement of changes in happiness implies that it would be optimal to utilize longitudinal data. However, longitudinal data on international migration are sparse. Therefore, the literature has largely resorted to cross-sectional methods that compare the post-migration happiness of migrants to the happiness of external comparison groups at the same point in time. To answer whether migrants have become happier upon migration, migrants have been compared to people who have a similar country of origin but who did not emigrate; these people are hereafter referred to as ‘stayers’. Hence, the happiness of stayers serves as a proxy for pre-migration happiness. To assess whether migrants obtain similar happiness levels to those of natives some time after migration, migrants have been compared to individuals in the host country, hereafter referred to as ‘natives’. Cross-sectional studies and longitudinal studies face methodological issues that deserve a discussion to enable accurate inferences on the happiness of migrants.

#### 2.2.1 Self-selection

Cross-sectional studies have limited explanatory power regarding causality because migration is a selective phenomenon (e.g. McKenzie, Stillman and Gibson 2010 ; Polgreen and Simpson 2011 ). The selection problem can be diminished by the inclusion of covariates that reduce omitted variable bias. However, at least 30 per cent of happiness is genetically determined, which implies that a substantial degree of unobserved variance remains present ( Lykken and Tellegen 1996 ). The practical implication of this issue in migration research is that, even after controlling for personal characteristics, migrants have lower happiness ( Graham and Markowitz 2011 ; Otrachshenko and Popova 2014 ; Chindarkar 2014 ) or higher happiness ( Bartram 2013a ) than natives. To downgrade self-selection, matching samples ( Hunter et al. 2008 ; IOM 2013 ; Bartram, forthcoming ), instrumental variables ( Safi 2010 ), two-stage ‘treatment-effects’ models ( Melzer 2011 ; Bartram 2013a ; Bartram, forthcoming ) and multilevel models ( Voicu and Vasile 2014 ) have been used. However, these methods cannot completely rule out self-selection problems; therefore, it must be acknowledged that cross-sectional studies have limited leverage in answering whether and how much migrants gain happiness.

#### 2.2.2 Inclusion of covariates

Most studies have controlled for a range of (semi-) time-invariant factors such as age, gender, education level, marital status, religion, and household size to lower omitted variable bias. It is advisable to additionally control for a broad range of personality traits and life values, because migrants are typically more extrinsically oriented (e.g. more oriented towards work, achievement, and power) and less intrinsically oriented (e.g. valuing family and friends) compared to stayers ( Boneva and Frieze 2001 ). A second group of incorporated covariates are categorized as time-variant covariates . These factors include, inter alia, income, employment status, health, social network, and socio-economic status. The inclusion of time-variant covariates can be useful to diminish unobserved heterogeneity, but these covariates are tricky. They are often affected by the act of emigration and one can therefore throw the baby out with the bathwater when incorporating these covariates because vital paths that cause changes in happiness are blocked. The inclusion of time-variant factors also offers the possibility to assess whether migrants become (un)happier regardless of a set of time-variant covariates. Therefore, the inclusion of multiple models can be valuable, beginning with a model that only includes time-invariant covariates and gradually adding time-variant factors in subsequent models (see e.g. Bartram 2013b ).

#### 2.2.3 Longitudinal studies

The comparison of changes within individuals offsets many causality issues. Nonetheless, caution is required when making inferences based on longitudinal models; a bias towards happy migrants is present in longitudinal studies because unhappy migrants are more likely to enter the attrition group as they have a higher tendency to re-migrate ( Erlinghagen 2011 ; Krause 2013 ). Note that this issue may also apply to cross-sectional studies; the probability of interviewing a ‘successful’ migrant can be greater than that of interviewing ‘unsuccessful’ migrants because re-migration rates can be assumed to be higher among unsuccessful migrants. A second issue that longitudinal studies must take into account is that the significant life changes caused by migration cause high volatility in happiness in the few years before and after migration. Migrants experience a decrease in life satisfaction that begins approximately three years before migrating (e.g. Melzer and Muffels 2012 ), followed by a peak shortly after migration (e.g. Obućina 2013 ). 1 Therefore, longitudinal studies should compare migrants several years before and after migration to get around the dip and peak.

#### 2.2.4 Inferences

The issues discussed clarify that cross-sectional studies in particular skate on thin ice when answering a question that is longitudinal in nature. Therefore, the current review gives relatively greater attention to methodologically stronger studies. Hazardous inferences have been made in some prior studies, given the quality of the data. For instance, some cross-sectional studies have claimed to compare the actual migration outcome to how migrants’ lives hypothetically would have been if they had not emigrated (e.g. IOM 2013 ). Even when including the methods discussed in order to diminish selection issues, this counterfactual question cannot be answered by cross-sectional studies. Specifically, merely considering migration positively affects individuals who in the end did not move because of cognitive dissonance ( Festinger 1957 ), or alternatively, it can have a negative effect on these people because the greater awareness of the relatively unfavourable conditions in their country of origin can lead to feelings of deprivation.

## 3. Method

The present review of research findings aims to provide insights into the two study questions. A systematic literature search, based on set boundaries, was conducted to avoid the cherry-picking of studies. All eligible papers were included based on the reported analyses, unless otherwise indicated.

### 3.1 Literature search strategy

Papers that relate migration to happiness are published in the journals of multiple disciplines, including journals that focus on migration, subjective well-being, economics, psychology, and sociology. Therefore, the first step was to conduct a broad literature search in databases of various disciplines, as follows: EconLit, ERIC, PsycInfo, SocINDEX, and the World Database of Happiness. English-language articles were searched using migration-related keywords (i.e. international migration, emigration, immigration, and immigrants) in various combinations with three well-being-related keywords (i.e. happiness, subjective well-being, and life satisfaction). This search yielded 28 studies. The following step was to examine (1) cited articles in the papers already included and (2) other articles that cited the papers already included. This snowballing technique yielded an additional 16 studies.

### 3.2 Eligibility of studies

The following boundaries were formulated to identify relevant studies:

1. Academic literature. Only strictly scientific articles (with the exception of the World Migration Report 2013 ) 2 are included to guarantee minimal levels of reliability and validity regarding the analysis.

2. Data structure. Merely quantitative studies are included. 3

3. Groups of interest. First and second generation emigrants are the experimental groups of interest because the common goal of migration is to provide a better life for oneself, one’s relatives, and one’s descendants.

4. Meaningful benchmark. Studies are only included when the sample of migrants is meaningfully compared to a valid benchmark. Migrants’ pre-migration happiness (in longitudinal data) and the happiness of stayers (in cross-sectional data) are valid benchmarks to assess whether migrants become happier upon migration. Natives are a valid benchmark to assess whether migrants become as happy as natives over time. Studies are excluded that compare groups of migrants mutually or that make comparisons based on different surveys/measures.

5. Appropriate measure of happiness. Only studies that utilized a valid measure according to the World Database of Happiness are included ( Veenhoven 2014 ). There are two exceptions: the Satisfaction with Life Scale (SWLS) and the Student’s Life Satisfaction Scale (SLSS) are not accepted in the World Database of Happiness but are incorporated in this review because they are well accepted by others in the field.

### 3.3 Incorporated studies

Ultimately, 38 publications, two forthcoming papers, and four valuable working papers are included. 4 The booming recent interest in the happiness outcomes of migration becomes clear in the temporal disproportional spread of the published papers, as depicted in Fig. 1 . The upward trend occurs mainly due to the rising attention in sociology and the advent of journals that focus on explaining subjective well-being. Contributions to the literature can, to a lesser extent, also be found in economic and psychological journals. Exploring migrants’ happiness has been a less considered theme in migration journals than one would expect given the specific interest of migration journals in improving migrants’ lives.

Figure 1.

Number of published papers over 5-year periods per scientific field.

Figure 1.

Number of published papers over 5-year periods per scientific field.

## 4. Results

Table 1 summarizes the 64 comparisons that were made in the 44 included studies. The table confirms the limited number of longitudinal studies. The longitudinal comparison and the comparison of migrants to stayers reveal scattered findings on the first question of whether migrants become happier after migration. Finally, most of the studies that compare migrants to natives indicate that migrants do not reach similar happiness levels to those of natives. The next two sections discuss the incorporated studies in greater detail.

Table 1.

Overview of research findings on the happiness of migrants

Post-migration subjective well-being of international migrants (versus comparison group)

Study design Benchmark Positive Neutral Negative
Longitudinal Pre-migration happiness  1 *
Cross-sectional Happiness of stayers
Happiness of natives 17 30
Post-migration subjective well-being of international migrants (versus comparison group)

Study design Benchmark Positive Neutral Negative
Longitudinal Pre-migration happiness  1 *
Cross-sectional Happiness of stayers
Happiness of natives 17 30

Note: ‘Positive’ implies a higher level of post-migration happiness relative to the benchmark, ‘neutral’ indicates a similar level, and ‘negative’ indicates a lower level.

*Both the study of Mähönen et al. (2013) and the study of Lönnqvist et al. (2014) have analysed the same longitudinal migration stream and arrived at similar conclusions.

### 4.1 Do migrants become happier?

A detailed overview of studies that address migrants’ increase in happiness levels is depicted in Table 2 . Experimental and longitudinal studies have a qualitatively superior design relative to cross-sectional studies and are therefore discussed separately. Studies that use datasets and studies that use their own data are in addition distinguished because the data collection procedures and sample designs are inherently different.

Table 2.

Overview of studies on differences in happiness due to migration

Migration stream  Who? (migration generation)  When migrated? * N of sample Measure Methodology Covariates Effect on migrants Survey Study
Length of stay n migrants
Longitudinal and experimental studies
Russia → Finland Diaspora migrants (1) 2008–2010 143  General happiness 1-item Paired samples T-test  Positive INPRES  Mähönen et al. (2013) **
$x¯$ = 0.5 years
Russia → Finland  2008–2014 85  Life satisfaction 4-item SWLS Latent growth model  Positive INPRES/LADA Lönnqvist et al. (2014)
$x¯$ = 3 years
Tonga → New Zealand Winners in migration lottery (1) 2002–2005 185 General happiness Local average treatment effect-estimates (LATE) age – education – pre migration employment and income – gender – marital status – region – religion Negative PINZMS Stillman et al. (2015)
<3 years 110 1-item
Studies using datasets for comparing migrants to stayers
Germany → Europe Adults (1) 1944–2009 11,096 Life satisfaction OLS regression age – education – employment – gender – health – social capital Positive ESS Erlinghagen (2011)
85% >5 years 1,010 1-item wave 1–4
Developing countries → Developed countries Adults (1) 1946–2011 +− 10,000 Life satisfaction Matched stayers age – education – gender Positive  Gallup World Poll 2009–2011 IOM (2013)
1-item
Developed countries → Developed countries Adults (1) 1946–2011 +− 5,500 Life satisfaction Matched stayers age – education – gender Positive  Gallup World Poll 2009–2011 IOM (2013)
1-item
East Europe → West Europe Adults (1) 1945–2010 42,380  General happiness 1-item OLS regression & 2-stage model age – education – employment – gender – health – income – marital status – religion – social capital No difference ESS Bartram (2013a)
1,071 wave 4–5
Romania → mainly West Europe Adults (1) 1943–2009 1,595  General happiness 1-item OLS regression age – employment – gender – health – marital status – religion – social capital No difference ESS Bartam (2013b)
<10 years 153 wave 4
West Europe → South Europe Adults (1) 1944–2009 56,733  General happiness 1-item Matched stayers and 2-stage model age – (parental) education – friends – gender – health – income – partner – region – religion Negative ESS Bartram (forthcoming)
338 wave 1–5
Developing countries → Developing countries Adults (1) 1946–2011 +− 8,250 Life satisfaction Matched stayers age – education – gender Negative  Gallup World Poll 2009–2011 IOM (2013)
1-item
Developed countries → Developing countries Adults (1) 1946–2011 +− 1,250 Life satisfaction Matched stayers age – education – gender Negative  Gallup World Poll 2009–2011 IOM (2013)
1-item
Studies creating own surveys for comparing migrants to stayers
North India → UK women aged 45–55 (1) 1951–2006 103  General happiness 1-item ANCOVA education – employment – marital status Positive Own survey Hunter et al. (2008)
50
Worldwide → Portugal Adolescent returnees (1) 1990–2010 832 Life satisfaction Bivariate  No difference Own survey Neto and Neto (2011)
$x¯$ = 8.5 years 217 5-item SWLS
Migration stream  Who? (migration generation)  When migrated? * N of sample Measure Methodology Covariates Effect on migrants Survey Study
Length of stay n migrants
Longitudinal and experimental studies
Russia → Finland Diaspora migrants (1) 2008–2010 143  General happiness 1-item Paired samples T-test  Positive INPRES  Mähönen et al. (2013) **
$x¯$ = 0.5 years
Russia → Finland  2008–2014 85  Life satisfaction 4-item SWLS Latent growth model  Positive INPRES/LADA Lönnqvist et al. (2014)
$x¯$ = 3 years
Tonga → New Zealand Winners in migration lottery (1) 2002–2005 185 General happiness Local average treatment effect-estimates (LATE) age – education – pre migration employment and income – gender – marital status – region – religion Negative PINZMS Stillman et al. (2015)
<3 years 110 1-item
Studies using datasets for comparing migrants to stayers
Germany → Europe Adults (1) 1944–2009 11,096 Life satisfaction OLS regression age – education – employment – gender – health – social capital Positive ESS Erlinghagen (2011)
85% >5 years 1,010 1-item wave 1–4
Developing countries → Developed countries Adults (1) 1946–2011 +− 10,000 Life satisfaction Matched stayers age – education – gender Positive  Gallup World Poll 2009–2011 IOM (2013)
1-item
Developed countries → Developed countries Adults (1) 1946–2011 +− 5,500 Life satisfaction Matched stayers age – education – gender Positive  Gallup World Poll 2009–2011 IOM (2013)
1-item
East Europe → West Europe Adults (1) 1945–2010 42,380  General happiness 1-item OLS regression & 2-stage model age – education – employment – gender – health – income – marital status – religion – social capital No difference ESS Bartram (2013a)
1,071 wave 4–5
Romania → mainly West Europe Adults (1) 1943–2009 1,595  General happiness 1-item OLS regression age – employment – gender – health – marital status – religion – social capital No difference ESS Bartam (2013b)
<10 years 153 wave 4
West Europe → South Europe Adults (1) 1944–2009 56,733  General happiness 1-item Matched stayers and 2-stage model age – (parental) education – friends – gender – health – income – partner – region – religion Negative ESS Bartram (forthcoming)
338 wave 1–5
Developing countries → Developing countries Adults (1) 1946–2011 +− 8,250 Life satisfaction Matched stayers age – education – gender Negative  Gallup World Poll 2009–2011 IOM (2013)
1-item
Developed countries → Developing countries Adults (1) 1946–2011 +− 1,250 Life satisfaction Matched stayers age – education – gender Negative  Gallup World Poll 2009–2011 IOM (2013)
1-item
Studies creating own surveys for comparing migrants to stayers
North India → UK women aged 45–55 (1) 1951–2006 103  General happiness 1-item ANCOVA education – employment – marital status Positive Own survey Hunter et al. (2008)
50
Worldwide → Portugal Adolescent returnees (1) 1990–2010 832 Life satisfaction Bivariate  No difference Own survey Neto and Neto (2011)
$x¯$ = 8.5 years 217 5-item SWLS

Note: By clicking on the author name of a study (the column on the right), a digital hyperlink links to the World Database of Happiness in which more detailed information about the empirical results of the paper are collected based on this review. Studies using the SWLS or the SLSS have no digital hyperlink because those studies are not accepted by the World Database of Happiness (see section 3.2 for more details).

*When migration history is derived from country of birth, it is assumed that the surveyed individuals have migrated while in the range of zero and 65 years, as surveys mainly consist of people below 65 years.

**The reported analysis in the paper uses the 6-item GWBI-scale. This measure is no well-accepted measure for well-being. Yet, one item in this scale is a valid happiness-item, as follows: ‘How happy, pleased or satisfied have you been with your personal life?’. Upon request, the authors have re-run their analysis. The paired samples T-test revealed a positive migration effect on this happiness-item: t(142) = −5.33, p < .001.

#### 4.1.1 Cross-sectional

The IOM (2013) and Bartram’s study ( forthcoming ) match migrants to stayers based on age, gender, and (parents’) education. The IOM reveals that migrants who moved towards or between developing countries become, in general, less satisfied with life. In contrast, those who moved to or between developed countries become more satisfied with life. 5 Bartram’s finding is in line with this pattern. He observes that Western Europeans who moved to the less developed Southern Europe were less happy than their non-migrating counterparts. This difference remains when controlling for a range of time-invariant and time-variant personal characteristics. By applying a two-stage treatment-effects model, Bartram (2013a) found that Eastern Europeans positively selected into migration to Western Europe but that there was no positive effect of the move itself. Similarly, Bartram (2013b) found no difference in happiness between Romanian immigrants in Western Europe and Romanian stayers. The other cross-sectional studies in Table 2 are methodologically less innovative. However, they show interesting results, such as gains in life satisfaction for German emigrants.

#### 4.1.2 Experimental

Stillman et al. (2015) derived high-quality data from a survey among Tongan participants in a random ballot lottery; the desired ‘prize’ was being permitted to migrate to New Zealand. From a scientific view, this ‘natural experiment’ randomly assigned the participants to one of the two compared groups: migrants or compulsory stayers. The ‘lucky’ movers from Tonga to New Zealand were similarly happy during the post-migration peak (one year after arrival) to their counterparts who had to stay in Tonga. However, the emigrants became less happy over time and were significantly less happy 33 months after their move compared to the stayers (eight-tenths lower on a five-point scale). Interestingly, emigrants’ objective well-being greatly increased; for instance, emigrants’ wages nearly tripled relative to stayers’ wages. A second interesting discrepancy is between mental health and happiness. Tongan emigrants experienced decreases in happiness even though their mental health increased by approximately three points on a twenty-point scale.

#### 4.1.3 Longitudinal

The related studies of Mähönen, Leinonen and Jasinskaja-Lahti (2013) and Lönnqvist et al. (2014) illustrate that Russian diaspora migrants who moved to Finland reported higher life satisfaction in the years after migration than a year before migration. Pre-migration life satisfaction was only measured one year before migration, which is problematic because migrants may experience a pre-migration dip (see section 2.2.3). Hence, caution is required in making strong inferences based on these results because the positive effect may be driven by the pre-migration dip.

#### 4.1.4 Concluding remarks

Whereas there seems to be some evidence that the state of development of migrants’ country of origin relative to their host country plays a role, several high-quality studies present findings that do not correspond to this trend ( Bartram 2013a ; Bartram 2013b ; Stillman et al., 2015 ). Hence, there is more to migration than just moving to a well-developed country; substantial roles may be attributed to specific characteristics of the host country, the country of origin, and/or the migrants themselves. There are no clear patterns of other potential moderators such as time since migration and the methodology of the study.

### 4.2 Do migrants become as happy as natives in the host country?

Table 3 illustrates that lower happiness among migrants compared to natives is present in diverse migration streams and migrant generations. The findings of Ullman and Tatar (2001) are particularly interesting; they found that Russian migrants had lower life satisfaction than Israeli natives despite higher socio-economic status and better education. However, several studies do not find lower happiness among migrants and thus deviate from the general pattern. Four explanations can be given for these deviations. First, it is likely that migrants already had higher or similar pre-migration happiness relative to natives (may apply to Shields, Price and Wooden 2009 ; Easterlin and Plagnol 2008 ; Bartram 2011 ; Rasmi, Chuang and Safdar 2012 ; IOM 2013 ). However, pre-migration levels cannot explain the deviation in every instance (e.g. Turks to Scandinavia in Virta, Sam and Westin 2004 ). Second, some studies include time-variant controls (e.g. income, employment, and health) that are also determinants of happiness (see Obućina 2013 ; Sander 2011 ; Dittmann and Goebel 2010 ). Hence, it remains unclear whether these migrants truly have similar happiness or the time-variant controls block vital pathways to happiness. Third, some sample sizes are too limited to reasonably expect that the happiness levels reach significance ( Sam 1998 ; Hirschi 2009 ; Bartram 2011 ). Fourth, migrants have truly reached similar happiness. Palisi and Canning (1983) , Virta, Sam and Westin (2004) and Neto and Barros (2007) convincingly show that the immigrants under study reached the happiness levels of migrants. Some other studies found that only specific subgroups within a sample exhibited similar happiness to that of natives. These contrasting findings were observed for first- versus second-generation migrants ( Van Praag, Romanov and Ferrer-i-Carbonell 2010 ; Krause 2013 ) and for males versus females ( Frijters, Haisken-DeNew and Shields 2004 ). These results highlight the importance of examining factors that cause contingent outcomes. Finally, the IOM (2013) observed disparate findings on the life satisfaction measure and the affect balance scale, which illustrates the value of identifying the exact happiness measure.

Table 3.

Overview of studies comparing the happiness of migrants and natives

Migration stream  Who? (migration generation) When migrated?* N of sample  Measure Methodology Covariates Effect on migrants Survey Study
Length of stay n migrants
Studies using datasets for comparing migrants to natives
East-Europe → Germany Adults (1) 1944–2009 +− 15,000 Life satisfaction OLS random effects age – education – employment – gender – housing – income – marital status – relative deprivation Positive GSOEP Obućina (2013)
1-item  wave 11–26
English speaking countries → Australia Adults (1) 1936–2001 13,903 Life satisfaction Ordered probit with fixed effects age – education – employment – health – children – housing – income – marital status – religion Positive HILDA Shields et al. (2009)
1-item wave 1
Developed countries → Developing countries  Adults (1) 1946–2011 +10,000 Life satisfaction Adjusted means age – education – gender
• Life satisfaction:

• Positive

• Affect balance:

• Negative

Gallup World Poll 2009–2011 IOM (2013)
1-item
Affect balance
6-item
Europe → West Germany Adult (1) 1939–2004 230,340 Life satisfaction Bivariate  No difference GSOEP Easterlin and Plagnol (2008)
24,930 1-item wave 1–18
South and West Europe → Germany Adult (1) 1944–2009 +− 15,000 Life satisfaction OLS random effects age – education – employment – gender – housing – income – marital status – relative deprivation No difference GSOEP Obućina (2013)
1-item wave 11–26
Portugal → Switzerland Adolescents (1/2) 1988–2006 280 Life satisfaction Bivariate  No difference ICSEY Neto and Barros (2007)
$x¯$ = 7 years 93 5-item SWLS
Europe & Canada → US Adults (1) 1930–1995 1,339 Life satisfaction Ordered logit regression age – employment – health – income – income*migration – children – marital status No difference WVS Bartram (2011)
120 1-item wave 3
Worldwide → US Adults (1) 1941–2006 6563 General happiness Ordered probit model age – education – employment – gender – health – children – income – marital status – religion – region No difference GSS Sander (2011)
1-item 2000–2006
Worldwide → West and East Germany Adults (1) 1941–2006 27,249 Life satisfaction OLS regression age – education – gender – health – life conditions – personality – social capital – relative deprivation No difference GSOEP Dittmann and Goebel (2010)
1-item wave 17–23
Worldwide → Developed countries Adults (1) 1949–2011 51,004 Life satisfaction OLS regression age – religion – gender – health – children – income – income*migration – marital status – employment No difference  Gallup World Poll 2006–2011 Olgiati et al. (2013)
4,772 1-item
Worldwide → Germany Adults (1) 1990–2000 4,100 Life satisfaction Ordered probit model with random effects age – employment – health – children – income – life changes – marital status – political vote – region – year controls  (♂) Negative GSOEP Frijters et al. (2004)
<10 years 1-item (♀) No difference wave 8–17
Worldwide → Israel Jews (1/2) 1941–2006 5,114 Life satisfaction OLS regression including POLS-operationalization age – education – employment – gender – health – children – income – marital status – religion
• 1st generation:

• Negative

• 2nd generation:

• No difference

Israeli Social Survey Van Praag et al. (2010)
4,173 1-item 2006
Worldwide → Germany Unemployed adults (1/2) 1944–2009 2,542 Life satisfaction OLS regression age – education – employment – gender – health – children – income – marital status
• 1st generation:

• No difference

• 2nd generation:

• Negative

IZA evaluationdataset S Krause (2013)
432 1-item 2007–2009
Developed countries → Developed countries Adults (1) 1946–2011 +5,500
• Life satisfaction

• 1-item

• Affect balance

• 6-item

Adjusted means age – education – gender
• Life satisfaction: No difference

• Affect balance:

• Negative

Gallup World Poll 2009–2011 IOM (2013)
Developing countries → Developing countries Adults (1) 1946–2011 +8,250
• Life satisfaction

• 1-item

• Affect balance 6-item

Adjusted means age – education – gender
• Life satisfaction: No difference

• Affect balance:

• Negative

Gallup World Poll 2009–2011 IOM (2013)
Developing countries → Developed countries Adults (1) 1946–2011 +1,250
• Life satisfaction

• 1-item

• Affect balance 6-item

Adjusted means age – education – gender
• Life satisfaction: No difference

• Affect balance:

• Negative

Gallup World Poll 2009–2011 IOM (2013)
Developing countries → US Adults (1) 1930–1995 <1,339 Life satisfaction Ordered logit regression age – employment – health – income – interaction migration & income – children – marital status Negative WVS Bartram (2011)
1-item wave 3
East Europe → West Europe Adults (1) 1939–2004 88,029  Life satisfaction & general happiness 1-item Bivariate  Negative ESS Bălţătescu (2007)
$x¯$ = 18.5 years 7,482 wave 1–2
Morocco/Turkey→ The Netherlands aged 14-45 (1/2) 1963–2008 3,925 Life satisfaction Multilevel model age – children – education – gender – partner Negative NELLS survey De Vroome and Hooghe (forthcoming)
1,697 4-item SWLS
Turkey → West Germany Adults (1) 1939–2004 230,340 Life satisfaction Bivariate  Negative GSOEP Easterlin and Plagnol (2008)
1-item wave 1–18
Turkey → The Netherlands Young adults (2) Born between 1968–1990 273 Life satisfaction Hierarchical regression age – gender – socio-economic status (SES) Negative Own survey Verkuyten (2008)
141 5-item SWLS
Turkey → Germany Adults (1) 1944–2009 +− 15,000 Life satisfaction OLS random age – education – employment – gender – housing – income – marital status – relative deprivation Negative GSOEP Obućina (2013)
1-item effects wave 11–26
Non-English speaking countries → Australia Adults (1) 1936–2001 13,903 Life satisfaction Ordered probit with fixed effects age – education – employment – health – children – housing – income – marital status – religion Negative HILDA Shields et al. (2009)
1-item wave 1
Worldwide → UK Adults (1) 1944–2009 32,025 Life satisfaction OLS regression age – gender – education – marital status – children – employment – household income – housing – urban/rural – health – religion – length of stay – neighbourhood Negative UKHLS Platt, Knies, and Nandi (2014)
50% <10 years 4,175 1-item 2009/2010
East Europe → West Europe Adults (1) 1945–2010 42,380 General happiness Own calculation  Negative ESS Bartram (2013a)
1,071 1-item wave 4–5
Worldwide → Canada Disabled adults (1) 1926–1991 24,036 General happiness Ordered logit model age – gender – marital status – region – religion – SES Negative HALS Uppal (2006)
4,375 1-item 1991
Worldwide → Germany Adults (1) 1939–2004 12,006 Life satisfaction Bivariate  Negative GSOEP Haisken-De New and Sinning (2010)
1,890 1-item wave 22
Worldwide → Germany Adults (1/2) 1940–2005 21,079 Life satisfaction ANCOVA age – gender Negative GSOEP Nesterko et al. (2013)
$x¯$ = 25 years 2,971 1-item wave 23
South Europe → Germany Adults (1) 1940–2010 71,779 Life satisfaction OLS regression age – education – employment – gender – marital status Negative GSOEP Kozcan (2013)
$x¯$= 34 years 2,837 1-item wave 1–27
Worldwide → North Italy Adolescents (1) 1991–2006 6,276 Contentment OLS regression age – bullied – gender – SES – social capital Negative HBSC Vieno et al. (2009)
481 1-item Cantril
Within Europe Adults (1/2) 1941–2006 56,338  Life satisfaction & general happiness 1-item OLS regression age – education – employment – gender – health – income – marital status – religion Negative ESS Safi (2010)
6,077 wave 1–3
Within Europe Adults (1/2) 1943–2008 66,697 Total happiness Bivariate but robustness checks included age – gender – marital status Negative ESS Senik (2011)
11,771 1-item wave 1–4
Within Europe Adults (1/2) 1947–2012 32,275 Life satisfaction Ordered probit model age – bullied – education – employment – ethnic minority – gender – health – housing – income – marital status – political vote – religion Negative ESS Kirmanoğlu and Başlevent (2014)
1-item wave 6
Studies creating own surveys for comparing migrants to natives
European Canadians → Egypt/Libanon Students(1) 1982–2010 260 Life satisfaction ANOVA  Positive Own Survey Rasmi et al. (2012)
129 5-item SWLS
Arab Canadians → Egypt/Libanon Students(1) 1982–2010 260 Life satisfaction ANOVA  No difference Own Survey Rasmi et al. (2012)
129 5-item SWLS
South East Europe → Switzerland Adolescents (1) 1943–2007 330 Life satisfaction Hierarchical regression age – gender No difference Own survey Hirschi (2009)
57 5-item SWLS
Developing countries → Norway Adolescents (1/2) 1979–1997 715 Life satisfaction ANOVA  No difference Own survey Sam (1998)
$x¯$= 9.5 years 506 5-item SWLS
Turkey → Scandinavia Adolescents (1/2) 1985–2003 822 Life satisfaction ANCOVA age – SES No difference Own survey Virta et al. (2004)
$x¯$= 9.5 years 391 5-item SWLS
Worldwide → Londen/Los Angeles/Sydney Adult men (1) 1915–1980 752 Affect Balance Structural age – education – housing – marital status No difference Own Survey Palisi and Canning (1983)
140 10-item Equation Model
Developing countries → The Netherlands Adolescents (1) 1969–1985 261 Contentment ANOVA  Negative Own survey Verkuyten (1986)
157 1-item Cantril
Developing countries → The Netherlands Adolescents (1) 1972–1988 3,228 Contentment ANOVA  Negative Own survey Verkuyten (1989)
518 1-item Cantril
Developing countries → Portugal Adolescents (1) 1990–2009 676 Life satisfaction ANOVA  Negative Own survey Neto (2001)
$x¯$ = 8 years 313 5-item SWLS
Bulgaria → Turkey Forced migrants (1) 1989 183 Life satisfaction Bivariate  Negative Own survey Yenilmez et al. (2007)
$x¯$ = 15 years 85 5-item SWLS
Former Soviet Union → Israel Adolescents (1) 1982–2000 254 Life satisfaction Bivariate  Negative Own survey Ullman & Tatar (2001)
$x¯$ = 5.5 years 119 7-item SLSS
Worldwide → Spain Adults (1) 1967–2012 1,646 Life satisfaction ANOVA sense of community Negative Own survey Hombrados-Mendieta et al. (2013)
700 5-item SWLS
Migration stream  Who? (migration generation) When migrated?* N of sample  Measure Methodology Covariates Effect on migrants Survey Study
Length of stay n migrants
Studies using datasets for comparing migrants to natives
East-Europe → Germany Adults (1) 1944–2009 +− 15,000 Life satisfaction OLS random effects age – education – employment – gender – housing – income – marital status – relative deprivation Positive GSOEP Obućina (2013)
1-item  wave 11–26
English speaking countries → Australia Adults (1) 1936–2001 13,903 Life satisfaction Ordered probit with fixed effects age – education – employment – health – children – housing – income – marital status – religion Positive HILDA Shields et al. (2009)
1-item wave 1
Developed countries → Developing countries  Adults (1) 1946–2011 +10,000 Life satisfaction Adjusted means age – education – gender
• Life satisfaction:

• Positive

• Affect balance:

• Negative

Gallup World Poll 2009–2011 IOM (2013)
1-item
Affect balance
6-item
Europe → West Germany Adult (1) 1939–2004 230,340 Life satisfaction Bivariate  No difference GSOEP Easterlin and Plagnol (2008)
24,930 1-item wave 1–18
South and West Europe → Germany Adult (1) 1944–2009 +− 15,000 Life satisfaction OLS random effects age – education – employment – gender – housing – income – marital status – relative deprivation No difference GSOEP Obućina (2013)
1-item wave 11–26
Portugal → Switzerland Adolescents (1/2) 1988–2006 280 Life satisfaction Bivariate  No difference ICSEY Neto and Barros (2007)
$x¯$ = 7 years 93 5-item SWLS
Europe & Canada → US Adults (1) 1930–1995 1,339 Life satisfaction Ordered logit regression age – employment – health – income – income*migration – children – marital status No difference WVS Bartram (2011)
120 1-item wave 3
Worldwide → US Adults (1) 1941–2006 6563 General happiness Ordered probit model age – education – employment – gender – health – children – income – marital status – religion – region No difference GSS Sander (2011)
1-item 2000–2006
Worldwide → West and East Germany Adults (1) 1941–2006 27,249 Life satisfaction OLS regression age – education – gender – health – life conditions – personality – social capital – relative deprivation No difference GSOEP Dittmann and Goebel (2010)
1-item wave 17–23
Worldwide → Developed countries Adults (1) 1949–2011 51,004 Life satisfaction OLS regression age – religion – gender – health – children – income – income*migration – marital status – employment No difference  Gallup World Poll 2006–2011 Olgiati et al. (2013)
4,772 1-item
Worldwide → Germany Adults (1) 1990–2000 4,100 Life satisfaction Ordered probit model with random effects age – employment – health – children – income – life changes – marital status – political vote – region – year controls  (♂) Negative GSOEP Frijters et al. (2004)
<10 years 1-item (♀) No difference wave 8–17
Worldwide → Israel Jews (1/2) 1941–2006 5,114 Life satisfaction OLS regression including POLS-operationalization age – education – employment – gender – health – children – income – marital status – religion
• 1st generation:

• Negative

• 2nd generation:

• No difference

Israeli Social Survey Van Praag et al. (2010)
4,173 1-item 2006
Worldwide → Germany Unemployed adults (1/2) 1944–2009 2,542 Life satisfaction OLS regression age – education – employment – gender – health – children – income – marital status
• 1st generation:

• No difference

• 2nd generation:

• Negative

IZA evaluationdataset S Krause (2013)
432 1-item 2007–2009
Developed countries → Developed countries Adults (1) 1946–2011 +5,500
• Life satisfaction

• 1-item

• Affect balance

• 6-item

Adjusted means age – education – gender
• Life satisfaction: No difference

• Affect balance:

• Negative

Gallup World Poll 2009–2011 IOM (2013)
Developing countries → Developing countries Adults (1) 1946–2011 +8,250
• Life satisfaction

• 1-item

• Affect balance 6-item

Adjusted means age – education – gender
• Life satisfaction: No difference

• Affect balance:

• Negative

Gallup World Poll 2009–2011 IOM (2013)
Developing countries → Developed countries Adults (1) 1946–2011 +1,250
• Life satisfaction

• 1-item

• Affect balance 6-item

Adjusted means age – education – gender
• Life satisfaction: No difference

• Affect balance:

• Negative

Gallup World Poll 2009–2011 IOM (2013)
Developing countries → US Adults (1) 1930–1995 <1,339 Life satisfaction Ordered logit regression age – employment – health – income – interaction migration & income – children – marital status Negative WVS Bartram (2011)
1-item wave 3
East Europe → West Europe Adults (1) 1939–2004 88,029  Life satisfaction & general happiness 1-item Bivariate  Negative ESS Bălţătescu (2007)
$x¯$ = 18.5 years 7,482 wave 1–2
Morocco/Turkey→ The Netherlands aged 14-45 (1/2) 1963–2008 3,925 Life satisfaction Multilevel model age – children – education – gender – partner Negative NELLS survey De Vroome and Hooghe (forthcoming)
1,697 4-item SWLS
Turkey → West Germany Adults (1) 1939–2004 230,340 Life satisfaction Bivariate  Negative GSOEP Easterlin and Plagnol (2008)
1-item wave 1–18
Turkey → The Netherlands Young adults (2) Born between 1968–1990 273 Life satisfaction Hierarchical regression age – gender – socio-economic status (SES) Negative Own survey Verkuyten (2008)
141 5-item SWLS
Turkey → Germany Adults (1) 1944–2009 +− 15,000 Life satisfaction OLS random age – education – employment – gender – housing – income – marital status – relative deprivation Negative GSOEP Obućina (2013)
1-item effects wave 11–26
Non-English speaking countries → Australia Adults (1) 1936–2001 13,903 Life satisfaction Ordered probit with fixed effects age – education – employment – health – children – housing – income – marital status – religion Negative HILDA Shields et al. (2009)
1-item wave 1
Worldwide → UK Adults (1) 1944–2009 32,025 Life satisfaction OLS regression age – gender – education – marital status – children – employment – household income – housing – urban/rural – health – religion – length of stay – neighbourhood Negative UKHLS Platt, Knies, and Nandi (2014)
50% <10 years 4,175 1-item 2009/2010
East Europe → West Europe Adults (1) 1945–2010 42,380 General happiness Own calculation  Negative ESS Bartram (2013a)
1,071 1-item wave 4–5
Worldwide → Canada Disabled adults (1) 1926–1991 24,036 General happiness Ordered logit model age – gender – marital status – region – religion – SES Negative HALS Uppal (2006)
4,375 1-item 1991
Worldwide → Germany Adults (1) 1939–2004 12,006 Life satisfaction Bivariate  Negative GSOEP Haisken-De New and Sinning (2010)
1,890 1-item wave 22
Worldwide → Germany Adults (1/2) 1940–2005 21,079 Life satisfaction ANCOVA age – gender Negative GSOEP Nesterko et al. (2013)
$x¯$ = 25 years 2,971 1-item wave 23
South Europe → Germany Adults (1) 1940–2010 71,779 Life satisfaction OLS regression age – education – employment – gender – marital status Negative GSOEP Kozcan (2013)
$x¯$= 34 years 2,837 1-item wave 1–27
Worldwide → North Italy Adolescents (1) 1991–2006 6,276 Contentment OLS regression age – bullied – gender – SES – social capital Negative HBSC Vieno et al. (2009)
481 1-item Cantril
Within Europe Adults (1/2) 1941–2006 56,338  Life satisfaction & general happiness 1-item OLS regression age – education – employment – gender – health – income – marital status – religion Negative ESS Safi (2010)
6,077 wave 1–3
Within Europe Adults (1/2) 1943–2008 66,697 Total happiness Bivariate but robustness checks included age – gender – marital status Negative ESS Senik (2011)
11,771 1-item wave 1–4
Within Europe Adults (1/2) 1947–2012 32,275 Life satisfaction Ordered probit model age – bullied – education – employment – ethnic minority – gender – health – housing – income – marital status – political vote – religion Negative ESS Kirmanoğlu and Başlevent (2014)
1-item wave 6
Studies creating own surveys for comparing migrants to natives
European Canadians → Egypt/Libanon Students(1) 1982–2010 260 Life satisfaction ANOVA  Positive Own Survey Rasmi et al. (2012)
129 5-item SWLS
Arab Canadians → Egypt/Libanon Students(1) 1982–2010 260 Life satisfaction ANOVA  No difference Own Survey Rasmi et al. (2012)
129 5-item SWLS
South East Europe → Switzerland Adolescents (1) 1943–2007 330 Life satisfaction Hierarchical regression age – gender No difference Own survey Hirschi (2009)
57 5-item SWLS
Developing countries → Norway Adolescents (1/2) 1979–1997 715 Life satisfaction ANOVA  No difference Own survey Sam (1998)
$x¯$= 9.5 years 506 5-item SWLS
Turkey → Scandinavia Adolescents (1/2) 1985–2003 822 Life satisfaction ANCOVA age – SES No difference Own survey Virta et al. (2004)
$x¯$= 9.5 years 391 5-item SWLS
Worldwide → Londen/Los Angeles/Sydney Adult men (1) 1915–1980 752 Affect Balance Structural age – education – housing – marital status No difference Own Survey Palisi and Canning (1983)
140 10-item Equation Model
Developing countries → The Netherlands Adolescents (1) 1969–1985 261 Contentment ANOVA  Negative Own survey Verkuyten (1986)
157 1-item Cantril
Developing countries → The Netherlands Adolescents (1) 1972–1988 3,228 Contentment ANOVA  Negative Own survey Verkuyten (1989)
518 1-item Cantril
Developing countries → Portugal Adolescents (1) 1990–2009 676 Life satisfaction ANOVA  Negative Own survey Neto (2001)
$x¯$ = 8 years 313 5-item SWLS
Bulgaria → Turkey Forced migrants (1) 1989 183 Life satisfaction Bivariate  Negative Own survey Yenilmez et al. (2007)
$x¯$ = 15 years 85 5-item SWLS
Former Soviet Union → Israel Adolescents (1) 1982–2000 254 Life satisfaction Bivariate  Negative Own survey Ullman & Tatar (2001)
$x¯$ = 5.5 years 119 7-item SLSS
Worldwide → Spain Adults (1) 1967–2012 1,646 Life satisfaction ANOVA sense of community Negative Own survey Hombrados-Mendieta et al. (2013)
700 5-item SWLS

Note:*When migration history is derived from country of birth, it is assumed that the surveyed individuals have migrated while in the range of zero and 65 years, as surveys mainly consist of people below 65 years.

#### 4.2.1 Concluding remarks

It can be concluded that only a small set of migrants bridged the complete gap when taking into account that some studies found no gaps because (1) there was already no pre-migration gap, (2) the included covariates offset the potential gap, or (3) the sample sizes were too limited to detect significant differences. The gap remained present in various populations and for various happiness indicators.

### 4.3 Theoretical explanations for findings

#### 4.3.1 The change in happiness

A majority of migrants move to countries that provide better economic conditions, a more effective government, and/or a more constructive society. They often pay a high psychosocial price for these gains, including, among others, the absence of significant others, cultural disparities, linguistic limitations, and social degradation. Hence, a trade-off often must be made. A substantial subset of the migrant population makes suboptimal decisions because of the hardships migrants face in forecasting the outcomes of migration. The four most prominent biases are that migrants often have excessive expectations that are not met by reality ( Benson and O’Reilly 2012 ), give too much weight to the effect of extrinsic (often economic) factors at a cost of intrinsic (psychosocial) factors ( Frey and Stutzer 2014 ), adapt sooner than expected to better extrinsic circumstances ( Frederick and Loewenstein 1999 ), and do not foresee the experience of deprived feelings that are caused by the change of a single frame of reference (natives in the country of origin) into a dual frame of reference that additionally includes the often objectively better off natives in the home country ( Gokdemir and Dumludag 2012;,Gelatt 2013 ; Obućina 2013 ). However, there is also a substantial subset of migrants that have accurately forecast that the advantages of migration would outweigh the costs and thus became happier by migrating.

#### 4.3.2 The happiness-gap to natives

The gap is grounded in several factors. First, the objective circumstances of immigrants are typically worse than those of natives. Obvious examples are income and unemployment rates. However, less obvious factors also play a role, such as lower job security rates and higher rates of people who work in jobs that do not match their skills ( Kozcan 2013 ). Second, as discussed, the dual frame of reference results in feelings of deprivation. Third, cultural factors of the heritage country continue to have an effect on migrants ( Senik 2011 ; Voicu and Vasile 2014 ). Fourth, hardships such as discrimination and linguistic limitations are specific to the immigrant population. Two additional suggested explanations deserve more research. Bobowik et al. (2011) suggest that the gap is partly caused by migrants’ life values. Their reasoning draws on the observation that psychological threats increase the priority that people give to extrinsic goals ( Sheldon and Kasser 2008 ). Immigrants commonly experience suboptimal conditions and threats such as the need to integrate into an unfamiliar culture and prejudices. Consequently, immigrants tend to become more extrinsically oriented, whereas intrinsically oriented people are typically happier ( Boneva and Frieze 2001 ). This reasoning is in line with the robust observation that integrated migrants, who generally feel less threat, are happier than less integrated migrants (e.g. Virta, Sam and Westin 2004 ). The second suggestion is based on the argument of Veenhoven (2000) that people’s life ability plays a vital role in happiness. The lower education of migrants may result in lower knowledge and skills to make optimal decisions and to make the best of life. However, both suggestions are currently not much more than speculations and therefore need to be researched further.

## 5. Discussion

The aim of the review is to advance the understanding of the happiness outcomes of migration. The review illustrates that migrants reach greater happiness in only a subset of migration streams. Immigrants do not simply become happier when moving to a more developed country, because migrants commonly face several psychosocial hardships in the host country, such as the absence of significant others, cultural disparities, linguistic limitations, and social degradation. The differences in happiness outcomes between migration streams signify that characteristics of the receiving and sending country, as well as personal capabilities and characteristics, play a substantial role. The review additionally reveals that immigrants only occasionally reach similar happiness to that of natives in the host country. Several factors that contribute to the gap are worse objective circumstances, feelings of deprivation, cultural features, and migration-specific hardships such as discrimination and linguistic limitations. Notably, these conclusions are based on aggregated outcomes for migration streams; a subset of migrants within a migration-stream may deviate from the general trend.

Additional data and research are needed to give a more detailed and reliable answer to the question of whether migration fosters happiness. The range of migration flows that have been researched is limited and selective. Consequently, some major migration flows are not yet studied (e.g. Latinos to the USA). Additionally, the mixed findings suggest that it is valuable to further examine the determinants of happiness at both the individual level and the country level. The greater knowledge would improve the accuracy of migrants’ decision making processes and allow policymakers to promote migrants’ happiness through the implementation of more effective policies.

I will now provide a research agenda to stimulate further research on this topic. Qualitatively superior data (preferably longitudinal) are of great importance to overcome most of the methodological limitations this field currently faces. These data do not always have to come from datasets. Studies using self-collected samples can have a sizeable role in advancing the field because they can reveal specific contingent mechanisms that are addressed by contemporarily available datasets. These studies can incorporate factors associated with (1) specific migration streams (e.g. cultural distance between the countries), (2) the country of origin (e.g. internalized culture), (3) the host country (e.g. immigration policies), and (4) the individual migrant (e.g. expectations and aspirations, personality, and migration motives). Considering the measurement of happiness, all studies are based on self-reported happiness, which is typically based on the memorized self. The memorized self generates aggregated and selective data, which distorts information ( Kahneman 2011 ). Trending methods that question the more accurate experience of the self are now available, such as the Experience Sampling Method and the Day Reconstruction Method. Finally, future studies should investigate the destinations for which specific migrant groups can potentially experience the greatest gain in happiness. Only Olgiati, Calvo and Berkman (2013 : 402) touched upon this topic by showing that ‘It is Australia, Belgium, The Netherlands, Portugal and Sweden where economic migrants seem to get it right: they migrate to a place where income translates easily into well-being’.

A limitation of the current study is that it only focuses on migrants themselves. A subset of migrants moves to provide better futures to significant others who remain in the host country. A body of literature has suggested that significant others suffer in happiness from the absence of a loved one and that this suffering is not completely offset by higher economic well-being due to received remittances ( Guo, Aranda and Silverstein 2009 ; Borraz, Pozo and Rossi 2010 ; Jones 2014 ). In contrast, a positive effect has been found in the Gallup data ( Cárdenas, Di Maro and Sorkin 2009 ). Gartaula, Visser and Niehof (2012) observed that households that faced economic hardship experienced somewhat increased happiness, whereas those that met their basic needs prior to the husband’s departure did not experience increased happiness. Another group of stakeholders who are not addressed in the current paper are the natives in the host country. Akay, Constant and Giulietti (2014) and Betz and Simpson (2013) observed a weak positive influence of the immigrant population on natives’ happiness. Notably, the more the migrants were integrated into the country, the more positive was their influence. A topic that has received disproportionally little attention is the effect of outgoing migration streams on the happiness of stayers.

A final question is why only a small number of migrants who did not become happier after the move return to their country of origin. Several reasons apply. First, people are typically optimistic about their future; migrants perceive the first few years after migration as investments in their future ( Knight and Gunatilaka 2010 ). Second, cognitive dissonance causes migrants who do not experience an increase in happiness to believe that they are in a better position than they would have been if they had stayed in the place of origin (Stillman et al. 2015). Third, some migrants are embarrassed that they have not obtained what they were looking for, and they are reluctant to reveal this to people in their home country ( Mahler 1995 ).

The occurrence of suboptimal migration decisions and the reluctance of unsuccessful migrants to re-migrate highlight that policymakers and scholars need to help migrants make optimal decisions to develop a society that incorporates thriving immigrants.

## Acknowledgements

I am grateful to Ruut Veenhoven for helpful comments and for suggesting to link the incorporated studies in the review to the World Database of Happiness.

Conflict of interest statement . None declared.

## Notes

1. It has not been examined to date whether the potential pre-migration dip in migration is caused by the future act of migration or by the fact that people who experience decreases in happiness tend to opt for migration to restore their happiness.
2. The World Migration Report 2013 is included because it uses the qualitatively strong Gallup World Poll data, which is combined with high-quality analysis.
3. Qualitative studies are not incorporated because of the absence of statistical tests. However, qualitative studies can contribute greatly to quantitative studies in getting a more detailed grasp of the experiences of migrants.
4. An interesting body of research has studied the happiness of movers from former East Germany to former West Germany, and vice versa. This is perceived to be a semi-international migration stream. Findings on this migration stream are excluded from our analysis but are worth briefly mentioning. Longitudinal and cross-sectional data show that East Germans who moved to West Germany gained life satisfaction. In contrast, West Germans who moved to East Germany experienced losses in life satisfaction ( Frijters, Haisken-DeNew and Shields 2004 ; Fuchs-Schündeln and Schündeln 2009 ; Melzer 2011 ; Melzer and Muffels 2012 ). Concerning the comparison to natives, East German migrants did not reach the life satisfaction levels of West Germans, and West German migrants remained more satisfied with life than East Germans ( Melzer and Muffels 2012 ).
5. Caution is required in interpreting these results because Eastern and Southern European countries were incorporated into the group of developed countries. The positive outcome of migration within developed countries may be driven by the sizeable migration streams in recent years from Eastern and Southern Europe to more developed European countries.

## References

Akay
A
Constant
A
Giulietti
C
‘The Impact of Immigration on the Well-Being of Natives’
Journal of Economic Behavior & Organization
,
2014
, vol.
103
(pg.
72
-
92
)
Bălţătescu
S
‘Central and Eastern Europeans Migrants’ Subjective Quality of Life: A Comparative Study’
Journal of Identity and Migration Studies
,
2007
, vol.
1

2
(pg.
67
-
81
)
Bartram
D
‘Economic Migration and Happiness: Comparing Immigrants’ and Natives’ Happiness Gains from Income’
Social Indicators Research
,
2011
, vol.
103

1
(pg.
57
-
76
)
Bartram
D
‘Happiness and “Economic Migration”: A Comparison of Eastern European Migrants and Stayers’
Migration Studies
,
2013a
, vol.
1

2
(pg.
156
-
75
)
Bartram
D
‘Migration, Return and Happiness in Romania’
European Societies
,
2013b
, vol.
15

3
(pg.
408
-
22
)
Bartram
D
‘Inverting the Logic of Economic Migration: Happiness among Migrants Moving from Wealthier to Poorer Countries in Europe’
Journal of Happiness Studies
,
forthcoming
Benson
M
O’Reilly
M K
Lifestyle Migration: Expectations, Aspirations and Experiences
,
2012

Farnham, UK: Ashgate
Betz
W
Simpson
N B
‘The Effects of International Migration on the Well-Being of Native Populations in Europe’
IZA Journal of Migration
,
2013
, vol.
2

12
(pg.
1
-
12
)
Bobowik
M
, et al.  .
‘Personal Values and Well-Being among Europeans, Spanish Natives and Immigrants to Spain: Does the Culture Matter?’
Journal of Happiness Studies
,
2011
, vol.
12

3
(pg.
401
-
19
)
Boneva
B S
Frieze
I H
‘Toward a Concept of a Migrant Personality’
Journal of Social Issues
,
2001
, vol.
57

3
(pg.
477
-
91
)
Borraz
F
Pozo
S
Rossi
M
‘And What About the Family Back Home? International Migration and Happiness in Cuenca, Ecuador’
,
2010
, vol.
27

1
(pg.
7
-
27
)
Cárdenas
M
Di Maro
V
Sorkin
I
‘Migration and Life Satisfaction: Evidence from Latin America’
,
2009
, vol.
26

1
(pg.
9
-
33
)
Chindarkar
N
‘Is Subjective Well-Being of Concern to Potential Migrants from Latin America?’
Social Indicators Research
,
2014
, vol.
115

1
(pg.
159
-
82
)
De Vroome
T
Hooghe
M
‘Life Satisfaction among Ethnic Minorities in the Netherlands: Immigration Experience or Adverse Living Conditions?’
Journal of Happiness Studies
,
forthcoming
Diener
E
‘Subjective Well-Being: The Science of Happiness and a Proposal for a National Index’
American Psychologist
,
2000
, vol.
55

1
(pg.
34
-
43
)
Dittmann
J
Goebel
J
‘Your House, Your Car, Your Education: The Socioeconomic Situation of the Neighborhood and Its Impact on Life Satisfaction in Germany’
Social Indicators Research
,
2010
, vol.
96

3
(pg.
497
-
513
)
Easterlin
R A
Plagnol
A C
‘Life Satisfaction and Economic Conditions in East and West Germany Pre- and Post-Unification’
Journal of Economic Behavior & Organization
,
2008
, vol.
68

3–4
(pg.
433
-
44
)
Erlinghagen
M
‘Nowhere Better than Here? The Subjective Well-Being of German Emigrants and Remigrants’
Comparative Population Studies
,
2011
, vol.
36

4
(pg.
899
-
926
)
Esser
H
‘Assimilation, Ethnic Stratification, or Selective Acculturation? Recent Theories of the Integration of Immigrants and the Model of Intergenerational Integration’
Sociologica
,
2010
, vol.
4

1
(pg.
1
-
29
)
Festinger
L
A Theory of Cognitive Dissonance
,
1957
Stanford, CA
Stanford University Press
Frederick
S
Loewenstein
G
Kahneman
D
Diener
E
Schwart
N
Well-Being: The Foundations of Hedonic Psychology
,
1999
New York
Russell Sage Foundation
(pg.
302
-
29
)
Frey
B S
Stutzer
A
‘Economic Consequences of Mispredicting Utility’
Journal of Happiness Studies
,
2014
, vol.
15

4
(pg.
937
-
56
)
Frijters
P
Haisken-DeNew
J P
Shields
M A
‘Investigating the Patterns and Determinants of Life Satisfaction in Germany following Reunification’
The Journal of Human Resources
,
2004
, vol.
39

3
(pg.
649
-
74
)
Fuchs-Schündeln
N
Schündeln
M
‘Who Stays, Who Goes, Who Returns? East−West Migration within Germany Since Reunification’
Economics of Transition
,
2009
, vol.
17

4
(pg.
703
-
38
)
Gartaula
H N
Visser
L
Niehof
A
‘Socio-Cultural Dispositions and Wellbeing of the Women Left Behind: A Case of Migrant Households in Nepal’
Social Indicators Research
,
2012
, vol.
108

3
(pg.
401
-
20
)
Gelatt
J
‘Looking Down or Looking Up: Status and Subjective Well-Being among Asian and Latino Immigrants in the United States’
International Migration Review
,
2013
, vol.
47

1
(pg.
39
-
75
)
Gokdemir
O
Dumludag
D
‘Life satisfaction among Turkish and Moroccan immigrants in the Netherlands: The Role of Absolute and Relative Income’
Social Indicators Research
,
2012
, vol.
106

3
(pg.
407
-
17
)
Graham
C
Markowitz
J
‘Aspirations and Happiness of Potential Latin American Immigrants’
Journal of Social Research & Policy
,
2011
, vol.
2

2
(pg.
9
-
25
)
Guo
M
Aranda
M P
Silverstein
M
‘The Impact of Out-Migration on the Inter-Generational Support and Psychological Wellbeing of Older Adults in Rural China’
Ageing and Society
,
2009
, vol.
29

7
(pg.
1085
-
104
)
Haisken-DeNew
J
Sinning
M
‘Social Deprivation of Immigrants in Germany’
Review of Income and Wealth
,
2010
, vol.
56

4
(pg.
715
-
33
)
B
‘The Set Point Theory of Well-Being Has Serious Flaws: On the Eve of a Scientific Revolution?’
Social Indicators Research
,
2010
, vol.
9

7
(pg.
7
-
21
)
Hirschi
A
‘Career Adaptability Development in Adolescence: Multiple Predictors and Effect on Sense of Power and Life Satisfaction’
Journal of Vocational Behavior
,
2009
, vol.
74

2
(pg.
145
-
55
)
M I
, et al.  .
‘Sense of Community and Satisfaction with Life among Immigrants and the Native Population’
Journal of Community Psychology
,
2013
, vol.
41

5
(pg.
601
-
14
)
Hunter
M S
, et al.  .
‘Culture, Country of Residence and Subjective Well-Being: A Comparison of South Asian Mid-Aged Women Living in the UK, UK Caucasian Women and Women Living in Delhi, India’
International Journal of Culture and Mental Health
,
2008
, vol.
1

1
(pg.
44
-
57
)
International Organization for Migration (IOM)
World Migration Report 2010: The Future of Migration—Building Capacities for Change
,
2010
Geneva
IOM
International Organization for Migration (IOM)
World Migration Report 2013: Migrant Well-Being and Development
,
2013
Geneva
IOM
Jones
R C
‘Migration and Family Happiness in Bolivia: Does Social Disintegration Negate Economic Well-Being?’
International Migration
,
2014
, vol.
52

3
(pg.
177
-
93
)
Kahneman
D
Thinking, Fast and Slow
,
2011
New York
Farrar, Strauss, and Giroux
Kirmanoğlu
H
Başlevent
C
‘Life Satisfaction of Ethnic Minority Members: An Examination of Interactions with Immigration, Discrimination, and Citizenship’
Social Indicators Research
,
2014
, vol.
116

1
(pg.
173
-
84
)
Knight
J
Gunatilaka
R
‘Great expectations? The Subjective Well-being of Rural-Urban Migrants in China’
World Development
,
2010
, vol.
38

1
(pg.
113
-
24
)
Lucas
R E
Diener
E
Suh
E
‘Discriminant Validity of Well-Being Measures’
Journal of Personality and Social Psychology
,
1996
, vol.
71

3
(pg.
616
-
28
)
Koczan
Z
‘Does Integration Increase Life Satisfaction?’
2013

Discussion Paper, Faculty of Economics, University of Cambridge, No. 1314
Krause
A
‘Don’t Worry, Be Happy? Happiness and Reemployment’
Journal of Economic Behavior & Organization
,
2013
, vol.
96
(pg.
1
-
20
)
Lönnqvist
J-E
, et al.  .
‘The Mixed Blessings of Migration: Psychological and Social Well-Being over the Course of Migration’
2014
University of Helsinki Working Paper
Lykken
D
Tellegen
A
‘Happiness is a Stochastic Phenomenon’
Psychological Science
,
1996
, vol.
7

3
(pg.
186
-
9
)
Mahler
S J
American Dreaming: Immigrant Life on the Margins
,
1995
Princeton, NJ
Princeton University Press
Mähönen
T A
Leinonen
E
Jasinskaja-Lahti
I
‘Met Expectations and the Wellbeing of Diaspora Immigrants: A Longitudinal Study’
International Journal of Psychology
,
2013
, vol.
48

3
(pg.
324
-
33
)
McKenzie
D
Stillman
S
Gibson
J
‘How Important is Selection? Experimental vs. Non-Experimental Measures of the Income Gains from Migration’
Journal of the European Economic Association
,
2010
, vol.
8

4
(pg.
913
-
45
)
Melzer
S M
‘Does Migration Make You Happy? The Influence of Migration on Subjective Well-Being’
Journal of Social Research & Policy
,
2011
, vol.
2

2
(pg.
73
-
92
)
Melzer
S M
Muffels
R
‘Migrant’s Pursuit of Happiness. The Impact of Adaptation, Social Comparison and Relative Deprivation: Evidence from a “Natural” Experiment’
2012

SOEP Discussion Paper No. 448
Nesterko
Y
, et al.  .
‘Life Satisfaction and Health-Related Quality of Life in Immigrants and Native-Born Germans: The Role of Immigration-Related Factors’
Quality of Life Research
,
2013
, vol.
22

5
(pg.
1005
-
13
)
Neto
F
‘Satisfaction with Life among Adolescents from Immigrant Families in Portugal’
,
2001
, vol.
30

1
(pg.
53
-
67
)
Neto
F
Barros
J
‘Satisfaction with Life among Adolescents from Portuguese Immigrant Families in Switzerland’
Swiss Journal of Psychology
,
2007
, vol.
66

4
(pg.
215
-
23
)
Neto
F
Neto
J
‘Satisfaction with Life among Adolescents from Returned Portuguese Immigrant Families’
Journal of Social Research & Policy
,
2011
, vol.
2

2
(pg.
27
-
46
)
Obućina
O
‘The Patterns of Satisfaction among Immigrants in Germany’
Social Indicators Research
,
2013
, vol.
113

3
(pg.
1105
-
27
)
Olgiati
A
Calvo
R
Berkman
L
‘Are Migrants Going Up a Blind Alley? Economic Migration and Life Satisfaction Around the World: Cross-National Evidence from Europe, North America and Australia’
Social Indicators Research
,
2013
, vol.
114

2
(pg.
383
-
404
)
Otrachshenko
V
Popova
O
‘Life (Dis)Satisfaction and the Decision to Migrate: Evidence from Central and Eastern Europe’
The Journal of Socio-Economics
,
2014
, vol.
48
(pg.
40
-
9
)
Palisi
B J
Canning
F C
‘Urbanism and Social Psychological Well-Being: A Cross-Cultural Test of Three Theories’
The Sociological Quarterly
,
1983
, vol.
24

4
(pg.
527
-
43
)
Platt
L
Knies
G
Nandi
A
‘Life Satisfaction, Ethnicity and Neighbourhoods: Is There an Effect of Neighbourhood Ethnic Composition on Life Satisfaction?’
2014

Working Paper (No. 1407). Centre for Research and Analysis of Migration (CReAM), Department of Economics, University College London
Polgreen
L A
Simpson
N B
‘Happiness and International Migration’
Journal of Happiness Studies
,
2011
, vol.
12

5
(pg.
819
-
40
)
Portes
A
Lesser
E L
‘Social Capital: Its Origins and Applications in Modern Sociology’
Knowledge and Social Capital
,
2000
Boston, MA
Butterworth-Heinemann
(pg.
43
-
67
)
Rasmi
S
Chuang
S S
Safdar
S
Journal of Cross-Cultural Psychology
,
2012
, vol.
43

1
(pg.
84
-
90
)
Safi
M
‘Immigrants’ Life Satisfaction in Europe: Between Assimilation and Discrimination’
European Sociological Review
,
2010
, vol.
26

2
(pg.
159
-
76
)
Sam
D L
‘Predicting Life Satisfaction among Adolescents from Immigrant Families in Norway’
Ethnicity & Health
,
1998
, vol.
3

1–2
(pg.
5
-
18
)
Sander
W
‘Location and Happiness in the United States’
Economics Letters
,
2011
, vol.
112

3
(pg.
277
-
9
)
D A
Kahneman
D
‘Does Living in California Make People Happy? A Focusing Illusion in Judgments of Life Satisfaction’
Psychological Science
,
1998
, vol.
9

5
(pg.
340
-
6
)
Senik
C
‘The French Unhappiness Puzzle: The Cultural Dimension of Happiness’
2011

Discussion Paper Series, Forschungsinstitut zur Zukunft der Arbeit, No. 6175
Sheldon
K M
Kasser
T
‘Psychological Threat and Extrinsic Goal Striving’
Motivation and Emotion
,
2008
, vol.
32

1
(pg.
37
-
45
)
Shields
M A
Price
S W
Wooden
M
‘Life Satisfaction and the Economic and Social Characteristics of Neighbourhoods’
Journal of Population Economics
,
2009
, vol.
22

2
(pg.
421
-
43
)
Simpson
N
Zimmermann
K
Constant
A
‘Happiness and Migration’
International Handbook on the Economics of Migration
,
2013
Chapter 21
Edward Elgar Cheltenham, UK, and Northampton, USA
(pg.
393
-
407
)
Stillman
S
, et al.  .
‘Miserable Migrants? Natural Experiment Evidence on International Migration and Objective and Subjective Well-Being’
World Development
,
2015
65
(pg.
79
-
93
)
Ullman
C
Tatar
M
‘Psychological Adjustment among Israeli Adolescent Immigrants: A Report on Life Satisfaction, Self-Concept, and Self-Esteem’
,
2001
, vol.
30

4
(pg.
449
-
63
)
Uppal
S
‘Impact of the Timing, Type and Severity of Disability on the Subjective Well-Being of Individuals with Disabilities’
Social Science & Medicine
,
2006
, vol.
63

2
(pg.
525
-
39
)
Van Praag
B
Romanov
D
Ferrer-i-Carbonell
A
‘Happiness and Financial Satisfaction in Israel: Effects of Religiosity, Ethnicity, and War’
Journal of Economic Psychology
,
2010
, vol.
31

6
(pg.
1008
-
20
)
Veenhoven
R
‘The Four Qualities of Life’
Journal of Happiness Studies
,
2000
, vol.
1

1
pg.
1−39

Veenhoven
R
Measures of Happiness
,
2014

World Database of Happiness, Erasmus University Rotterdam. < http://worlddatabaseofhappiness.eur.nl/hap_quer/hqi_fp.htm > accessed 29 January 2014
Verkuyten
M
‘The Impact of Ethnic and Sex Differences on Happiness among Adolescents in the Netherlands’
Journal of Social Psychology
,
1986
, vol.
126

2
(pg.
259
-
60
)
Verkuyten
M
‘Happiness among Adolescents in the Netherlands: Ethnic and Sex Differences’
Psychological Reports
,
1989
, vol.
65

2
(pg.
577
-
8
)
Verkuyten
M
‘Life Satisfaction among Ethnic Minorities: The Role of Discrimination and Group Identification’
Social Indicators Research
,
2008
, vol.
89

3
(pg.
391
-
404
)
Vieno
A
, et al.  .
‘Health Status in Immigrants and Native Early Adolescents in Italy’
Journal of Community Health
,
2009
, vol.
34

3
(pg.
181
-
7
)
Virta
E
Sam
D L
Westin
C
‘Adolescents with Turkish Background in Norway and Sweden: A Comparative Study of their Psychological Adaptation’
Scandinavian Journal of Psychology
,
2004
, vol.
45

1
(pg.
15
-
25
)
Voicu
B
Vasile
M
‘Do “Cultures of Life Satisfaction” Travel?’
Current Sociology
,
2014
, vol.
62

1
(pg.
81
-
99
)
Yenilmez
C
, et al.  .
‘A Gender-Oriented Comparison between the Mental Health Profiles of Bulgarian Immigrants Forcibly Migrated to Turkey and the Native Population 15 Years after Migration’
International Journal of Psychiatry in Clinical Practice
,
2007
, vol.
11

1
(pg.
21
-
8
)