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Why are Locals Happier than Internal Migrants? The Role of Daily Life

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Several survey studies have found that internal migrants report lower levels of happiness than locals, even after accounting for socio-economic factors. Traditional global self-ratings reveal that the migrant–local happiness-gap is also present in the data we present. The reasons for the migrant–local happiness-gap are as yet unclear. This paper aims to open this ‘black box’ by exploring the role of daily activities among a population that has generally been overlooked despite their high migration frequency: young adults. An innovative smartphone application is used that combines two techniques for multiple moment assessment: the experience sampling method and the day reconstruction method. Based on the application data, we examine whether internal migrants spend their time differently than locals and in which situations they feel noticeably less happy than locals. The data reveal that internal migrants distribute less time to happiness-producing activities such as active leisure, social drinking/parties, and activities outside home/work/transit. Internal migrants feel less happy than locals when spending time with friends and while eating. Possible explanations focusing on the role of social capital are discussed. Further analyses reveal that daily life experiences greatly enhance the explanation of the migrant–local happiness-gap. This paper demonstrates the potential value of real-time data and phone applications in solving happiness puzzles.
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The role of daily life
Martijn Hendriks, Kai Ludwigs, Ruut Veenhoven
Social Indicaters Research, online since Januari 2015, DOI 10.1007/s11205-014-0856-7
Several survey studies have found that internal migrants report lower levels of happiness than
locals, even after accounting for socio-economic factors. Traditional global self-ratings reveal
that the migrant-local happiness-gap is also present in the data we present. The reasons for
the migrant-local happiness-gap are as yet unclear. This paper aims to open this ‘black box’
by exploring the role of daily activities among a population that has generally been
overlooked despite their high migration frequency: young adults. An innovative smartphone
application is used that combines two techniques for multiple moment assessment: the
Experience Sampling Method and the Day Reconstruction Method. Based on the application
data, we examine whether internal migrants spend their time differently than locals and in
which situations they feel noticeably less happy than locals. The data reveal that internal
migrants distribute less time to happiness-producing activities such as active leisure, social
drinking/parties, and activities outside home/work/transit. Internal migrants feel less happy
than locals when spending time with friends and while eating. Possible explanations focusing
on the role of social capital are discussed. Further analyses reveal that daily life experiences
greatly enhance the explanation of the migrant-local happiness-gap. This paper demonstrates
the potential value of real-time data and phone applications in solving happiness puzzles.
Keywords: internal migration, residential mobility, happiness, subjective well-being,
Experience Sampling Method, Day Reconstruction Method
Prof. Dr. Ruut Veenhoven Erasmus University Rotterdam, Faculty of Social Sciences,
P.O.B. 1738 3000 DR Rotterdam, Netherlands and North-West University in South Africa
Research from multiple countries has found that internal migrants are unable to reach similar
levels of happiness as locals (Aksel et al. 2007; Cheng, Wang, and Smyth 2014). Some
studies even find migrants to be less happy than people in the place of settlement (locals) and
people in the place of origin (stayers), which holds even after controlling for a range of socio-
economic factors (Appleton and Song 2008; Knight and Gunatilaka 2010). A specific, well-
researched case of internal migration is that of German internal migrants after reunification.
This paper makes a two-fold contribution. The first contribution is theoretical: the current
paper progresses current knowledge on i nternal migrants by opening the ‘black box’ on
factors causing the migrant-local happiness-gap. This is achieved by evaluating the migrant-
local happiness-gap from a new perspective: the role of daily life, which allows us to address
the three questions that were raised in the first paragraph. The second contribution is
methodological: a pioneering smartphone application is introduced that cost-effectively
incorporates two leading research methods to zoom in on daily life: the Experience Sampling
Method (ESM) and the Day Reconstruction Method (DRM). Although the application as
developed is focused on happiness, the concept of the application is applicable and valuable
across many research fields.
Those who moved post-reunification from the former East Germany to the former West
Germany have become happier after migration but have not reached similar happiness as
former West-Germans over time, whereas West-to-East migrants have become unhappier but
remain having higher happiness than East-Germans over time when accounting for socio-
demographic factors (Frijters, Haisken-DeNew, and Shields 2004; FuchsSchündeln and
Schündeln 2009; Melzer 2011). These findings raise three questions: why does the migrant-
local happiness-gap occur? Does the lower general happiness reported by migrants in surveys
also translate in less happiness in daily life? What can be done to reduce the gap?
This paper specifically focuses on internal migrants to intensify inquiry among scholars
and policy makers into this population. Internal migration has remained an underdeveloped
theme, especially when compared to international migration. Yet, migrating within a country
greatly exceeds the number of international migrants and is a crucial life event, as it largely
disrupts and destabilises the pattern of daily life (Molloy, Smith, and Wozniak 2011).
Additionally, this paper focuses on a population that has been overlooked in the literature on
the happiness of internal migrants: young adults. Ironically, young adults are those who
migrate most frequently as they face major life changes such as starting a job, study, family,
or moving in with a partner. They are also especially sensitive to life-disruptions because
compared to their older peers, they have less self-esteem and life experience, and they are
more dependent, less emotionally stable, and more vulnerable to peer pressure (Rosenberg
1965). Hence, this population in particular needs support in making the most of migrating.
What can multiple moment assessments add to general surveys? Global self-reports,
based on a ggregated data retrieved from memory, are not always exhaustive in explaining
sociological, economic, or psychological puzzles (Csikszentmihalyi and Hunter 2003;
Kahneman et al. 2004). Hektner, Schmidt, and Csikszentmihalyi suggest that zooming in on
people’s daily lives can open black boxes that remain closed when using general surveys.
Zooming in on daily life provides insight into what one does and how one feels throughout
the day. Examples of studies benefiting from such data are Knabe et al. (2010), who use it to
Martijn Hendriks, Kai Ludwigs, Ruut Veenhoven
Why are locals happier than internal migrants?
understand the happiness gap between the employed and the unemployed, and Kahneman et
al. (2006), who use it to clarify the weak relationship between income and happiness. Current
migration literature has merely used ratings of overall happiness derived from general
questionnaires. There is reason to believe that examining daily life in greater detail
contributes to explaining the migrant-local happiness-gap. Upon moving, migrants need to
build a new social network, create new life patterns, and engage in new activities,
organisations, and teams. This substantially impacts daily life in two fashions. First, it c an
result in a different distribution of time as one’s daily routine is disrupted and certain
activities are voluntarily or involuntarily initiated or discontinued (e.g., one’s job,
volunteering, sports). Second, it can lead to less enjoyment of particular daily life activities;
for instance, going out with a person one has recently met may be less enjoyable than going
out with a long-time friend.
Why incorporate both the ESM and the DRM? Both methods capture a representative
sample of individuals’ actions, thoughts and feelings throughout the day, across contexts,
close to their actual occurrence. In the ESM, respondents are asked to report their present
feelings and actions at short notice after receiving each of several signals distributed
throughout the day. The DRM asks respondents to complete diaries of the previous day in
which the feelings experienced during each performed activity are reported. The unique
methodologies imply unique strengths and weaknesses, making co-existence desirable (an
extensive discussion is presented in section three). Despite the value of combining these
methods, researchers typically choose between these two methods to reduce costs and to
increase people’s willingness to participate (Diener and Tay 2013). Therefore, a pioneering
smartphone application is introduced that cost-effectively combines these methods.
Young adults in the Düsseldorf area (Germany) used the application for two weeks. The
multiple moment assessments obtained four sources of information for every period of the
1. How the person is feeling
2. What the person is doing
3. Where the person is
4. Who is with the person
The multiple moment assessments began after completing a baseline questionnaire. The
baseline questionnaire includes six global measures of subjective well-being, of which four
specifically measure global happiness. For all six measures, migrants report lower
happiness/subjective well-being than locals. Moving to the data obtained from DRM and
ESM, two steps are taken to detect whether migrants and locals also have dissimilar daily life
experiences. First, we examine whether migrants distribute less time to happiness-promoting
activities, places, and people. Second, we examine whether migrants feel unhappier in certain
places, during certain activities, and with certain people. In a subsequent analysis, daily life
experiences are moved to the position of explanatory factors to discover the degree to which
daily life experiences explain the migrant-local happiness gap present in global self-ratings.
Data on da ily life experiences obtained by the smartphone application are shown to have
substantial explanatory power, indicating that the two sought-for research contributions are
The remainder of the paper is organised as follows. Section 2 reviews the literature that
relates internal migration to happiness. Section 3 discusses the value and co-existence of the
DRM and the ESM. Section 4 introduces the smartphone application used in this paper.
Section 5 describes the experimental set-up, and Section 6 presents the results. The final
section concludes, discusses, and provides policy implications.
Martijn Hendriks, Kai Ludwigs, Ruut Veenhoven
Why are locals happier than internal migrants?
Internal migration is usually defined as the geographical relocation of people over a
substantial distance within national borders. The impact of migration on people’s lives goes
beyond mere ‘geographically relocation’. One must adapt to another physical, social, and
cultural environment, develop new life patterns, and build new social contacts. It leads to
challenges such as finding new friends, communities, hobbies, and sports (teams), implying
that stress typically accompanies migration. It offers migrants great opportunities but also
substantial risks. The migration literature shows that migrants may not get the best out of
migration. Studies in Australia and Turkey have found that 30-50 percent of migrants regret
their decision to migrate, implying that it is difficult to overcome the hardships that come
with migration (Stimson and Minnery 1998; Aksel et al. 2007; Fozdar and Torezani 2008).
Although our study does not focus on pr e-migration versus post-migration happiness
development, it is relevant to review studies testing whether migrants gained in happiness by
migrating. Recent studies in Finland (Ek et al. 2008), Australia (Kettlewell 2010), and the UK
(Nowok et al. 2013) conclude that most people fail to obtain greater happiness by internal
migration. These findings imply that migrants do not commonly reach similar levels of
happiness as locals, as they do not gain in happiness at all. The gap is shown to be especially
relevant for recent migrants, although it is still present among long-term migrants (Knight
and Gunatilaka 2010; Cheng et al. 2014).
The key question is why migrants cannot get the best out of migration and how this
failure translates into lower levels of happiness in daily life. The social capital literature
shows that most migrants face difficulty connecting to others, which makes building new
networks an underestimated challenge (Portes 2000; Putnam 2000). Hardships arise because:
(1) migrants have little initial social capital via which potential friends can be met; (2) an
internal migrant often becomes a member of the out-group because they are seen as
‘different’, for instance, due to a different accent; and (3) migrants face impaired self-esteem
as they are still adapting to the new environment and feel ‘pressured’ to build new social
capital. In daily life, these hardships can translate into feelings of inferiority when being
around others, mostly because of being less in one’s ‘comfort zone’, having friendships of
lower quality, and lacking social support), and/or spending less time with good friends (e.g.,
one is less invited to social events). The broaden-and-build theory (Fredrickson 2001)
suggests that migrants will spend less time on physically and mentally effortful activities.
Namely, internal migrants typically give in on mental health due to the stress that comes with
migration (Chen 2011); experiencing negative feelings impairs openness to experiences and
reduces activeness because one has less mental energy to distribute. Lower mental health
results in less time allocated to effortful events as active leisure, meeting people, and out-of-
home activities. Moreover, migrants may not have access to their preferred activities in the
place of settlement, forcing them to discontinue certain activities. Relatedly, migrants may
lack the motivation to rebuild in the new place what they had built up in the old place over
the years (e.g., one’s reputation on a sports team).
Taken together, it s uggests that migrants are less engaged in effortful leisure activities.
This can reduce happiness, as activity theory suggests that active, social, and challenging
activities typically result in higher happiness (Rodríguez, Látková, and Sun 2008). As a by-
product of less social capital, migrants may enjoy social or effortful leisure activities less as
they cannot always perform these activities with their long-time friends but have to settle
with less close friends. Relatedly, they occasionally need to resort to less desired activities as
they have no friends, team, or community with whom they can perform the desired activity
(Putnam 2000). The time composition of everyday activities as eating, sleeping, and
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Why are locals happier than internal migrants?
housekeeping is less of a choice, which implies that time distributed to these activities is not
so much affected by migrating. Activities where no social and energy-restrictions are
involved are also hypothesised to be less affected; examples include in-home activities and
individual activities such as reading. In conclusion, it is hypothesised that lower happiness of
migrants is particularly caused by less enjoyment of and time composition for social and
effortful activities, but to a lesser degree by individual and daily activities.
Global self-reports used in prior literature have only allowed the examination of the
happiness-gap from a helicopter-view’, whereas tracking daily experiences provides the
opportunity for a more detailed look at the migrant-local happiness-gap. The advantages are
more diverse. Primarily, global self-reports (e.g., satisfaction with life-as-a-whole) rely on
distorted information derived from memory. People face hardships in retrieving all the
relevant data from their memory and to subsequently aggregate these data because one’s
answer depends strongly on recent and vivid experiences (Diener, Inglehart, and Tay 2013).
The use of memory and the need for aggregation are minimised for assessments on a
momentary (ESM) or daily (DRM) basis; it makes these methods less vulnerable to recall-
and aggregation bias, implying a better representation of actual experience.
The key advantages of the DRM over the ESM are: (1) the obtained data cover the
complete day, and (2) completing the diaries does not interrupt the flow of daily life, making
the DRM less burdensome than the ESM (Diener and Tay 2013). The key advantages of the
ESM over the DRM are: (1) superior ecological validity, as participants provide self-reports
in the environment and at the moment of truly experiencing the feelings, and (2) it does not
face the issue of the DRM that some participants divide the day into more episodes than
others, resulting in potential divergent responses between two groups. Their co-existence also
gives the opportunity to test for convergent validity of daily life assessments. This is valuable
because the psychometric support for the ESM and especially the DRM is limited at this
point in time. In conclusion, clear grounds for a multi-method design are present.
Second, episodic
assessments complement global self-reports because the latter typically encloses a strong
cognitive component of happiness, whereas the former encloses more ‘pure’ affective
evaluations. An advantage of the ESM is that it promotes ecological validity, as participants
provide self-reports in the environment where they truly experience the feelings. A final
contribution over traditional cross-sectional studies is that the panel element allows for more
robust individual assessments of happiness as biases such as the mood bias are cancelled out
on the individual level. The principal limitation of the ESM and DRM are their high costs. A
second limitation is that assessments of momentary happiness (i.e., mood) are aggregated to
an assessment of long-term happiness, whereas in actuality, the predictors are not exactly the
same. A third limitation is that overall scores are biased as participants selectively present
information, e.g., participants are reluctant to report that they have been making love (Diener
and Tay 2013). Accordingly, global self-reports and episodic assessments are supplementary
in assessing happiness.
Martijn Hendriks, Kai Ludwigs, Ruut Veenhoven
Why are locals happier than internal migrants?
In studies applying the DRM and ESM, experimenters typically handed participants a PDA
that had to be used during the experimental period. The use of smartphones has several
benefits. First, smartphones promote further ecological validity as participants complete the
assessments on a mobile phone to which they are accustomed and which they do not only use
for experimental purposes, resulting in lower awareness of ‘being followed’. Second, the
burden on participants is lower because they do not have to carry around an extra device.
This can raise the rates of response and participation. Third, it reduces costs, as no di gital
devices need to be provided to participants, which implies that there are no costs for
purchasing, repairing, and retrieving the equipment. Finally, applications allow for the
establishment of ‘fuzzy’ samples consisting of people who voluntarily and regularly indicate
their feelings. With this information, the impact of shocks can be revealed (e.g., the impact of
a natural disaster or one’s national team winning a s occer match) and data on momentary
assessments can be easily collected cross-nationally
. The use of smartphone applications has
become a more attractive option as many people now own smartphones. We created a cost-
and time-effective happiness application that allows participants to complete both daily
happiness diaries and momentary assessments on their personal mobile phones. This is not
the first smartphone application developed to examine episodic happiness. Killingworth and
Gilbert (2010) successfully used a happiness application for experience sampling, and
MacKerron (2011) developed a happiness app to study the influence of the local environment
(e.g., the weather) on episodic happiness. The application we introduce has two main
advantages over these applications. First, the Day Reconstruction Method is included on top
of the Experience Sampling Method. Second, this application is downloadable for Android
users, whereas earlier apps focused on i Phone users. Using Android decreases the self-
selection problem because approximately 65 percent of smartphone users have Android,
whereas iPhone users represent only 25 percent of smartphone users (Kantar World Panel
5.1 Sample and procedure
In the recruitment procedure, individuals were informed that the study involves a tracking of
happiness and time-use and that the study incorporates questions about demographics.
Individuals were additionally informed of the confidentiality of answers, the possibility to
skip a question in any case, and the possibility to opt out of the study at any moment.
Interested individuals were asked to list their e-mail address. In exchange for course credit,
123 young adults (17-30 years old) studying psychology in the Düsseldorf area were
recruited for participation. Concurrently, 75 young adults living in the Düsseldorf area were
recruited via word-of-mouth communication to increase the heterogeneity of the sample (e.g.,
to include non-students).
To prevent dropout, a lottery was announced in which those who
Martijn Hendriks, Kai Ludwigs, Ruut Veenhoven
Why are locals happier than internal migrants?
completed at least two-third of the diaries and experience samples could win a 250 euro voucher.
The multi-method study consists of three parts: (1) an online questionnaire (2) momentary
assessments, and (3) day reconstructions. A brief questionnaire, including a range of
measures of happiness and demographic questions, was purposively designed to obtain a
baseline-estimate of a person’s happiness. All participants completed the baseline-
questionnaire on the same evening and were afterwards informed how to download the
application onto their mobile phones. After downloading the application, a tutorial with
instructions on how to use the application was provided to raise conscientiousness and boost
response accuracy. The episodic assessments began for all participants on November, 7, 2013
(Thursday) and lasted for two weeks until November, 21, 2013 ( Thursday). Each day, six
signals were distributed throughout daytime covering the entire waking day; two consecutive
signals were always more than an hour apart. When signalled, participants were asked to
indicate (1) how they were feeling, (2) what they were doing, (3) where they were, and (4)
who was with them. The activities they could choose from were equal to those of the
HappinessIndicator (Oerlemans, Bakker, and Veenhoven 2014) and in line with
categorisations made by Kahneman et al. (2004). Every morning, participants were asked to
complete a diary of the previous day in which they answer the same four questions.
Participants are included in the analysis when the signal response rate was over 66 percent
in both the Experience Sampling Data (56 out of 84) and the daily diaries (10 out of 15).
These minima have been successfully surpassed by 109 locals and 41 migrants, indicating an
attrition rate of 24 percent. These 150 participants yielded a total of 11,455 momentary
assessments and 1,918 day reconstructions. The participants’ response rates in the ESM and
DRM are, respectively, 91 percent and 85 percent and there were no noteworthy differences
in compliance between migrants and locals. One to two minutes for completing an experience
sample is supported in literature as being desirable to make the interruptions brief and less
intrusive (Hektner et al. 2007). In our study, this was considerable less with an average of
about 30 s econds. The time to complete a diary was typically in the range of five to ten
5.2 Variables
Dependent variables.
To facilitate robust assessments about happiness and subjective well-being, the OECD
published guidelines on measuring subjective well-being (OECD 2013) in which they
propose including measures for (1) overall happiness (2) sub-elements of happiness (life
satisfaction and hedonic affect) and (3) elements of broader subjective well-being
(eudaimonic well-being and domain evaluations). The baseline questionnaire follows the
proposed structure by including one overall happiness measure, three measures focusing on
sub-elements of happiness, and two measures focusing on br oader subjective well-being,
although it should be noted that we are mainly interested in the four measures focusing on
happiness. Overall happiness is our primary interest and assessed by the question: ‘Taking all
things together, how happy would you say you are?’. It is answered on a numerical 10-point
scale ranging from extremely unhappy to extremely happy. Life satisfaction embodies the
cognitive side of happiness. The life satisfaction measure is ‘All things considered, how
satisfied are you with your life as a whole nowadays?’ ranging from 0 ( extremely
dissatisfied) to 10 (extremely satisfied). Additionally, a frequently used multiple-item scale to
measure life satisfaction is included: Diener’s Satisfaction With Life Scale (SWLS; Diener et
al 1985). The original 10-item Affect Balance Scale is included to assess the affective side of
happiness (Bradburn 1969). The first measure of broader subjective well-being is
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Why are locals happier than internal migrants?
psychological functioning (also referred to as eudaimonia or flourishing) and is measured by
the Flourishing Scale (Diener et al. 2010). This scale incorporates eight items (e.g., I lead a
purposeful and meaningful life) and is rated on a seven-point scale (1=strongly disagree;
7=strongly agree). Next, participants evaluated satisfaction with ten life domains (e.g.,
satisfaction with financial status or satisfaction with health status; for the other items, see
OECD 2013) on a 10-point scale (0=not at all satisfied; 10=completely satisfied). As
recommended by the OECD, every participant started the baseline questionnaire by rating
one’s overall happiness and finished with rating domain satisfactions to minimise spill-over
effects in the measures we are most interested in.
Prior studies applying the DRM or ESM have either used an affect balance scale (multi-
item) or a single question on current happiness to assess affective feelings in daily life. We
opted for the latter option, operationalized by the questions ‘How do you feel?’ in the ESM
and ‘How did you feel’ in the DRM and answered on a n 11-item numerical scale ranging
from ‘unhappy’ to ‘happy’, for three reasons. First, it is less of a burden on pa rticipants.
Second, the single-item measure is strongly correlated with the multi-item measure, implying
that the results are largely robust to the measure used (Knabe et al. 2010). Third, there is an
ongoing debate about the validity of aggregating specific emotions. When aggregating, there
is no agreement on how specific feelings should be weighed against each other (White and
Dolan 2009). For instance, joy may have a stronger effect than relaxation. By rating the 1-
item question, the respondent himself weights which emotions and thoughts are most
important for his overall feelings during an activity. Additionally, positive and negative affect
do not lie on a single dimension in the affective system, which makes it hazardous to
aggregate them (Cacioppo and Bernston 1994).
Independent variables.
An important reason behind the scant research on internal migrants is that there is no clear
boundary between an internal migrant and a local. Two recent studies have utilised a question
asking about the spatial distance (measured in kilometres) one has moved (Kettlewell 2010;
Nowok et al. 2013). This measure may not be optimal as the ‘perceived’ distance of
migration may depend on f actors such as one’s transportation resources and cultural
differences. Measures of cultural distance and travel-time from the place of origin encompass
elements that are related to happiness (cultural differences) and other confounding elements
(transportation opportunities often serves as a proxy for income), leading to an inherent bias.
Therefore, we preferred to use an objective measure: spatial distance. The exact question we
used is: ‘What is the approximate distance, from the city or town where you lived in before
you moved, to the city or town in which you are currently living?’. The five answer-options
were ‘More than a 1000 kilometres’, ‘100-1000 kilometres’, ’25-100 kilometres’, <25
kilometres’ and ‘I always lived here’. Due to the limited sample size and to maintain a
parsimonious model, we chose to merge these categories into a single ‘migrant’-category and
a single ‘locals’-category. Nowok and colleagues find that those who moved over more than
100 kilometres (long-distance movers) have lower happiness than those who move smaller
distances (25-100 kilometres). Kettlewell defined migrants who moved more than 20
kilometres as migrants. We wished to distinguish between those who truly experience the
need to build new social lives from those whose daily lives are less affected. Therefore, we
categorised those who migrated over 100 ki lometres as migrants and other participants as
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Control variables.
To minimise self-selection bias, the following factors that are typically associated with
happiness are included as covariates in the empirical analysis: age, gender, having a partner,
immigrant status (including 1
and 2
generation immigrants are classified as immigrants),
household income, employment status, and whether one has a chronic condition as a proxy
for health.
Additionally, personality is incorporated as measured by the ‘TIPI-scale’
(Gosling, Rentfrow, and Swann 2003). More specific controls for the purposes of our study
are also included. These are household situation (as it is strongly correlated to migration),
being a student (as a substantial portion of the participants are students), and being born in
East Germany (those born in East Germany are typically unhappier).
5.3 Analytical strategy
The ESM-data do not only account for momentary happiness but also yield an assessment of
a participant’s general happiness level by taking the mean of the separate momentary
responses (Kahneman 1999). T he same applies to the DRM, although one cannot simply
aggregate all happiness-assessments as activities have dissimilar durations. We follow
previous studies in applying the duration-weighted method of aggregation (e.g., White and
Dolan 2009), having the following formula:
EpisodeDuringFeelingDurationEpisodeDRMByHappinessDailyTotal )*(
in which i represents an individual and j an episode. This formula is not optimal as it is
unlikely that people assign a similar weight to each episode; however, because there is little
knowledge concerning the importance of particular episodes in daily life, this method is
acknowledged to be best practice. Happiness is commonly treated as being cardinal in
subjective well-being literature; we follow this approach as the results of cardinal models are
more intuitive and easier to interpret than estimates from ordinal probit models. In addition,
cardinal and ordinal analyses of life satisfaction yield, in general, similar results (Ferrer-i-
Carbonell and Frijters 2004).
The presence of the migrant-local happiness-gap is examined in two steps. First, the
presence of differences in happiness between migrants and locals is checked for each of the
six global self-reports and for the aggregated scores of the ESM and the DRM. Next, a
MANCOVA is applied, which takes the positive correlation between the dependent variables
into account. To avoid multicollinearity in the MANCOVA, the rule-of-thumb of Maxwell
(2001) is followed, which indicates that dependent variables should be low to moderately
correlated with a lower boundary of 0.30 and an upper-boundary of 0.70. In table 1, the
correlations in bold are very close to or exceed the upper-boundary, which implies that the
MANCOVA is likely to suffer from multicollinearity when including all variables. Possible
solutions to avoid multicollinearity are (1) the formation of a composite variable, or (2)
dropping variables that cause the multicollinearity problem. We opted for the latter option
because there is no c lear basis for aggregating the measures into an overall measure of
subjective well-being, making it hazardous to form a composite variable (OECD 2013).
Additionally, the central focus of this paper is the happiness-gap. Therefore, the multivariate
effect is based on four elements of happiness that are typically distinguished: overall
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Why are locals happier than internal migrants?
happiness (as measured by the overall happiness measure), daily happiness (by the
aggregated score of the day reconstructions), the cognitive element of happiness (by the
SWLS), and the affective element of happiness (by the affect balance scale).
To explore the role of daily life, we will proceed by applying two perspectives to zoom in
on the data obtained by experience sampling and happiness-diaries. A trait-like perspective is
applied to detect possible time-composition effects. The following question is answered from
this perspective: do migrants and locals allocate a different amount of time to certain
activities, people, and places? Next, a state-like perspective is applied to answer the question:
do particular activities, interaction partners, and locations lead to different happiness for
migrants and locals? Knabe et al. (2010) refer to differences in happiness for the same type of
activity as the ‘saddening’ effect. To enable more robust, meaningful, and interpretable
results, the twenty-one specific activities from which respondents could select when
completing their diaries and experience samples (e.g., exercising and eating) are aggregated
into five overarching categories derived from the time-and-leisure composition literature
(Dardis, Soberon-Ferrer, and Patro 1994). These categories are social leisure/entertainment,
active leisure, passive leisure, daily activities, and work-related activities.
Next, we aim to show the incremental value of daily life experiences in explaining the
migrant-local happiness-gap. Three OLS-regression models are developed for each of the six
global self-ratings, which are the explained variables. Model 1 includes migration as an
independent variable and also controls for individual and household characteristics to
minimise selection-bias. Model 2 adds the time-composition differences as independent
variables to examine the effect of different time-composition on the migrant-local happiness-
gap. Model 3 presents a full model by including activities in which a clear saddening effect is
present as independent variables.
6.1 Descriptive statistics
Migration-specific questions in the baseline-questionnaire reveal that 63 percent of the
migrants in the sample moved less than three years ago, half of the migrants moved without
knowing any friends or family in the host place, 58 percent plan to live less than three more
years in the study area, and 67 percent moved for study purposes. More general sample
descriptors are listed in table 2. We will examine two models to analyse the happiness-gap,
one including and one excluding the household situation. The reason for this division is that
the household situation may have a potential mediating effect on the happiness outcome of
migration because a different household situation is a logical consequence of migrating. The
correlation matrix (table 2) shows the convergent validity among the data derived from the
DRM and the ESM, as the correlation between these methods is significant, sizeable, and
larger in magnitude than their correlations with global happiness measures.
6.2 The migrant-local happiness-gap
Model A.
The degree to which the gap is present for each dependent variable when not controlling for
household situation, but after controlling for all other covariates included in table 2, is shown
in model A of table 3. Univariate results show that locals consistently reported significantly
higher scores (at the 10 percent-level) over the six measures. The gaps are somewhat larger
for the four global self-ratings of happiness than for eudaimonic well-being and domain
satisfactions. The practical importance of the findings is at least as important as the p-values
in our study because we combine a limited sample size with a wide range of covariates to
minimize selection-bias
.The partial eta squares indicate that the effect sizes are modest, which
can be considered as
Martijn Hendriks, Kai Ludwigs, Ruut Veenhoven
Why are locals happier than internal migrants?
substantial in the context of happiness. Episodic assessments are typically found to be more
rigid (e.g., Knabe et al. 2010), which is also the case in our data. A marginally significant
gap is observed for the DRM-data, whereas the ESM-data do not display a statistically
significant difference. Using the Bonferroni procedure, the MANCOVA reveals a significant
difference between migrants and locals, and a mediocre effect of migration, on the four
combined happiness variables (F (4, 130) = 2.49; p = .046; Wilks’ Lambda = .929; ηρ²= .071).
Model B.
The household situation is additionally controlled for in model B of table 3. The results of
model B are highly similar to those of model A. Non-reported results reveal that the low
impact of the household situation can be explained by the weak and non-significant
relationship between household situation and happiness. The practical and statistical
significance of the combined variables is also largely similar to model A (F (4, 127) = 2.31 p
= .061; Wilks’ Lambda = .932; ηρ²= .068). The results suggest that the happiness-gap is not
completely driven by differences in demographics and income and that over 6 percent of the
multivariate variance of the dependent variables is associated with the migrant-dummy. The
episodic assessments in model B do not reveal significant differences between migrants and
non-migrants. Nonetheless, substantial happiness-gaps in the aggregated DRM-data and
ESM-data remain present, which make it interesting to analyse the DRM-data and ESM-data
in more detail to reveal which specific daily experiences cause these gaps.
6.3 Time-composition of daily activities.
In this section, a trait-like perspective is applied to zoom in on the time-allocation of migrants
and locals. All covariates are included, which provides a substantial degree of certainty that
the time-composition differences caused by migrating are filtered. Using the DRM-method,
table 4 shows that locals spend significantly more time on active leisure activities.
Interestingly, being engaged in active leisure is typically recognised as promoting happiness.
When looking at specific activities, it emerges that locals spend significantly more time on
social drinking/parties, exercising, and in places other than home/work/transport. In contrast,
migrants spend more time on the computer, possibly to communicate with those not living
nearby. OLS regressions, controlling for the full set of covariates and the migration-dummy,
show that greater time-allocation (in hours) to exercising, social drinking/parties, and places
other than home/work/transport, are associated with higher scores on t he overall happiness
measure in our sample (B’s are, respectively, +.28, +.35, and +.02). In contrast, spending
time on the computer is associated with lower scores on happiness (B= -.05). In sum, we can
conclude that time composition seems to play a role in the happiness-gap.
6.4 Enjoyment of daily activities
Table 5 applies a state-like perspective to detect whether migrants and locals feel dissimilar
happiness during certain episodes. It appears that migrants feel as good as locals during
activities such as working and being with colleagues. In contrast, locals report significantly
higher happiness scores in both the ESM and the DRM compared to migrants while eating
and being with friends. Sizeable gaps are also present in other activities such as intimacy/sex,
but no s trong inferences can be drawn as the gaps are not significant due to the limited
sample size. The happiness-gap of ‘eating’ is analysed in greater detail in table 6.
‘deeper’ analysis of the eating category reveals that the happiness-gap especially occurs due
to locals’ greater enjoyment of eating with significant others, which is in line with the fact
that migrants generally enjoy being with friends less. Interestingly, we observed in table 4
that locals do not spend more time on eating and with friends. These results suggest that the
saddening effect adds unique value in explaining the happiness-gap. On the contrary, time
distribution to some other activities is in line with the happiness derived from those activities;
that is, locals report both substantially higher happiness and time spent on activities outside
home/work/transit and on e xercising. Additionally, migrants spend more time on the
computer and appear to enjoy that time more.
Martijn Hendriks, Kai Ludwigs, Ruut Veenhoven
Why are locals happier than internal migrants?
6.5 The incremental value of daily life experiences
The final model shows the incremental value of including time composition effects, and
saddening effects that consistently and significantly differed between migrants and locals.
Table 7 proceeds in stages. In the baseline model (model 1), the full set of covariates is added
to minimise the chance that the more extensive models (model 2 a nd 3) pick up s election
effects instead of adding unique explanatory power. In model 2, t he time allocation of the
five distinguished categories is incorporated and supplemented by the category ‘other
leisure’, as it does not belong in a specific category. Finally, a full” model is created (model
3) in which the consistently-found saddening effects of eating and being with friends are
included. The value of model 2 and 3 is threefold.
First, it allows us to examine the degree to which the inclusion of daily life experiences
can reduce the coefficient of the migration dummy. Logically, the migration dummy in model
1 is largely similar to the migration gap reported in model B of table 3 as the same covariates
are included but a different statistical procedure is applied. When also including time
allocation (model 2), the gap decreases for all dependent variables relative to the first model
and becomes insignificant for four of the six variables. The gap decreases further when
saddening effects are included (model 3), resulting in insignificant migration variables for all
dependent variables. Although part of the gap remains present in model 3, the gap decreases
substantially in comparison to the less comprehensive models. Hence, daily assessments are
valuable contributions in explaining the happiness-gap.
Second, the decreased gap can be explained by examining the effect of the time spending
categories and saddening effects on t he dependent variables. Active leisure is positively
related to happiness and partially explains the gap because locals spend more time on t his
happiness-producing activity. Feeling good while eating and being with friends is also
associated with higher scores for the dependent variables. One’s feelings with friends can be
expected to have a stronger association with long-term happiness than one’s feelings during
eating as social networks are crucial for people. Interestingly, the reverse was consistently
found over the dependent variables. Note, however, that the gap in eating is largely caused by
enjoying eating with friends less.
Finally, we examine whether each progressive model has incremental value in explaining
general happiness and subjective well-being. For this purpose, adjusted R squared statistics
are reported because they impose a penalty on a dditional parameters to a model. Models 2
and 3 have incremental value in explaining each dependent variable as the R-square rises in
any case from model 1 t o model 2 a nd from model 2 t o model 3. T his implies that time
composition and differences in momentary feelings are valuable explanatory factors, on top
of individual and household characteristics, for explaining subjective well-being and
6.6 Robustness check
The cross-sectional data cannot rule out the possibility that the migration effect is driven by
migrants who are genetically unhappier than locals and therefore never obtain a similar
happiness level. For multiple reasons, it is unlikely that the entire migration gap would be
caused by genetics; German internal migrants after reunification appeared to be somewhat
happier than non-migrants (FuchsSchündeln and Schündeln 2009), migrants are typically
self-confident and optimistic individuals, which correlates with higher happiness (Knight and
Gunatilaka 2010), and the gap we observe remains sizeable after controlling for personality.
Still, a more formal test of possible selectivity would increase the leverage of the results.
Therefore, we follow Bartram (2013) in applying a 2-stage treatment effects model.
Martijn Hendriks, Kai Ludwigs, Ruut Veenhoven
Why are locals happier than internal migrants?
The goal of the first stage is to obtain an estimation of the probability that one migrates.For this
purpose, an instrumental variable is needed to predict the probability that someone would
migrate, in addition to factors that affect the decision to migrate but cannot be affected by the
act of migration (age and gender in our study). The instrumental variable must be strongly
related to the independent variable (i.e., the migration-decision) but unrelated to the
dependent variable (i.e., happiness). Spatial distance in kilometers to the nearest university
offering a psychology-programme was chosen as an instrument. That is, most migrants
indicated moving for the purpose of studying psychology (67 percent), which implies that
only those who lived far away from a university felt the need to migrate (see column 1 i n
table 8). The distance to a psychology programme is unrelated to happiness. The adoption of
this instrument implies that only the student population of our sample was utilised in this
analysis (N=101). The second stage examines the effects of the independent variables on
A residual for each observation is obtained in both stages. Estimates are biased
in a standard OLS if the unobservables in stage 1 are correlated with the unobservables in the
stage 2 m odel. The negative 𝜌 in table 8 indicates a negative correlation between the
unobservables in the first stage and in the second stage. Thus, unobservables are negatively
(positively) related to migration and positively (negatively) related to happiness. This
suggests that, if at all, migrants are positively selected from the population in terms of
happiness, implying an increased gap when further removing selection effects. This is
confirmed when looking at the coefficient sizes of a standard OLS (B= .42) and the two-stage
model (B= .51). The insignificant λ indicates that there is no ground for preferring this more
advanced model over a basic OLS-model.
The key goals of this paper have been to present a widely applicable methodology that can
accurately zoom in on daily life and to advance the migration literature by addressing why
internal migrants are typically unhappier than locals from a new point of view: the role of
daily life. Global self-reports reveal that a gap remains present among young adults after
controlling for socio-demographic differences. These gaps are shown to be particularly
caused by a different experience of daily life. One part of the explanation comes from a
different distribution of time. The young adult migrants allocated less time to active leisure
and activities outside of home/work/transit. Specifically, they spent significantly less time on
exercising and social drinking/parties. This is unfortunate as these activities are all associated
with high momentary happiness and high global self-ratings of happiness. A possible
explanation for the time composition differences can be drawn from the broaden-and-build
theory (Fredrickson 2001). The stressful lives of migrants lead them to have less mental and
physical energy to engage in happiness-promoting activities as they are typically effortful. A
snowball develops in which less openness to, and energy for, happiness-promoting activities
leads to less positive feelings, which subsequently leads again to less mental energy, and so
on. Locals also spend more time on the computer, which is generally associated with lower
happiness. However, migrants were somewhat happier than locals when spending time on the
computer. A profound reason for higher enjoyment and more time allocated to the computer
may be the use of social media on the computer as a tool to communicate with their friends
and family who do not live close by. Another part of the explanation for the migrant-local
happiness-gap comes from lower happiness of migrants while being with friends and while
eating. The lower enjoyment of eating is not caused by eating with friends less often, but by
experiencing less enjoyment while eating with friends. The social capital literature provides
two potential explanations for migrants’ lower enjoyment when being or eating with friends.
Locals have lived in a certain place for a long time and have therefore had the opportunity to
be selective in choosing friends and maintaining relationships over time. Migrants have had
limited opportunities to build new social networks and must therefore choose from a
considerably smaller pool of people (Putnam 2000). Relatedly, migrants’ ties with others are
typically not as strong as the ties that locals have with their long-time friends, leading to
Martijn Hendriks, Kai Ludwigs, Ruut Veenhoven
Why are locals happier than internal migrants?
The knowledge regarding the impact of internal migration on ha ppiness is limited,
especially compared to international migration. This paper reveals that migrants can benefit
from aid in daily life decisions. From a policy perspective, migrants appear to benefit from
help in building new social lives and engaging in positive experiences such as active leisure.
This can be achieved by local governments offering help, information, or discounts to
migrants for becoming engaged in new communities and social- and active leisure activities
in the host region. National governments can reduce migration stress by simplifying moving
processes, such as the process of registering in a new city.
feelings of low social support and lower levels of comfort while spending time with the ‘new
friends’ (Portes 2000). Temporal comparison processes may augment the dissatisfaction with
the current friends because the less intimate new friends are negatively compared to long-
time friends in the place of origin. Both the time composition differences and the differences
in momentary happiness while being with friends explain a substantial part of the migrant-
local happiness-gap.
Methodologically, we show that the use of technologies that zoom in on daily life add to
the explanation of global subjective well-being. Future research can solve other economic,
sociological, and psychological puzzles by using cost-effective smartphone applications that
zoom in on the phenomenon under interest to obtain detailed information that is difficult to
derive from general surveys. The black boxes opened by this methodology can greatly benefit
public policy making as it helps to clarify what causes particular phenomena, thereby offering
a step forward in acting upon these problems and thereby improving happiness in society.
Despite its contributions, this study also has limitations. The independent variable may not
have been optimal as spatial distance may be different to perceived distance. The future
robustness of findings on internal migration can be improved by the development of an index
of perceived distance including factors as travelling time and culture distance and
complementing the measure of spatial distance. Another limitation was our sample; it w as
quantitatively limited, directed to a specific region, and included mostly females. We
encourage future studies to check whether our results are generalisable to other regions,
countries, and populations. A limitation in the measurement of happiness was that
participants completed all six global subjective well-being scales consecutively, which lowers
the advantages of measuring multiple constructs as biases as the impact of mood and
question-order may consistently occur in the baseline-questionnaire. A limitation of applying
both the ESM and the DRM is that there are likely to be carry-over effects from one activity
to the next. A final limitation was the cross-sectional research design. Although we managed
to minimise the chance of selection biases by using a two-stage model, a longitudinal design
incorporating pre-migration data would have been preferable. Yet, longitudinal datasets
incorporating migration-data are largely unavailable and therefore this study is not an
exception in having to resort to cross-sectional data.
In conclusion, by relating the introduced smartphone application to a b aseline
questionnaire, we show the incremental value that multiple moment assessments can bring to
general surveys in advancing knowledge. In this paper, this technology has been valuable in
explaining the migrant-local happiness-gap by revealing the role of daily life experiences. We
hope human knowledge will be advanced by applying similar technology on a wider scale.
The authors thank Stephan Erdtmann for technological help with constructing the application
and Martijn Burger and Thomas de Vroome for comments on earlier versions.
Martijn Hendriks, Kai Ludwigs, Ruut Veenhoven
Why are locals happier than internal migrants?
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Martijn Hendriks, Kai Ludwigs, Ruut Veenhoven
Why are locals happier than internal migrants?
This is also recognised as semi-internal migration, as former West Germany (BRD) and former East
Germany (DDR) were reunited into one Germany in 1990, but faced significant social, economic, and
cultural differences.
Some degree of memory bias is likely to be present when applying DRM, for instance, due to the “peak-end-rule”
(Redelmeier, Katz, and Kahneman 2003). The bias remains acceptable, however, because people are shown to
have adequate access to relevant information for indicating their feelings on the previous day (Kahneman et al. 2004).
This advantage is not yet applicable to our application as we lacked the resources to publicly introduce and promote
the application.
Additionally, 11 young adults not living in the Dusseldorf area and 21 adults over the age of 30 were recruited but
not considered for analysis as they introduced potential endogenous biases (e.g., living in a happier or unhappier
region or migrated decades ago).
Analyses distinguishing the 109 locals in 55 non-movers and 54 short-distance movers (<100 kilometers) reveal no
significant differences on all six subjective-well being measures; analyses are available on request.
An education variable, asking about the highest level of education completed is excluded because it was highly
correlated with age (r=0.82). The high correlation is plausible given our sample of young adults.
Robustness checks are performed by replacing the 1-item life satisfaction measure with the SWLS and
replacing the overall day reconstruction score with the overall experience sampling score. The outcomes are in
line with the reported results; results are available on request.
According to Cohen (1992), effect sizes should be interpreted as follows: ηρ² = 0.01 as small, ηρ² = 0.06 as medium,
and ηρ² = 0.14 as large.
Further robustness analyses suggest that the happiness-gap between migrants and locals was largely unaffected
by (1) excluding a minimum boundary for signal response rate, (2) including people over 30 years old, or (3)
including those not living in the Düsseldorf region; results are available on request.
A more detailed analysis of ‘friends’ did not appear to be useful due to the limited sample size per activity.
This type of ‘Heckman’ model applies a probit model in the first stage to reflect on the binary nature of the migration
Similar results are found when using other dependent variables; results are available on request.
Martijn Hendriks, Kai Ludwigs, Ruut Veenhoven
Why are locals happier than internal migrants?
Table 1. Correlation-matrix of subjective well-being measures.
Note: all correlations are significant at the 1% level.
Pearson Correlation coefficient (r)
1-item life
Overall happiness
1-item life satisfaction
Affect Balance
Eudaimonia 0.42 0.36 0.44 0.49 0.43
Martijn Hendriks, Kai Ludwigs, Ruut Veenhoven
Why are locals happier than internal migrants?
Table 2. Descriptive characteristics of the sample
Full sample
Mean (SD) / %
Mean (SD) / %
Mean (SD) / %
F statistic
Age in years 21.7 (3.10) 22.7 (3.19) 21.4 (2.99)
Gender (% male) 18% 10% 21%
Has a partner 50% 54% 49%
(Psychology) Students 73% 71% 73%
4.08 (0.66)
4.13 (0.52)
4.06 (0.71)
3.99 (0.63)
4.00 (0.58)
3.98 (0.65)
4.18 (0.78)
4.18 (0.73)
4.18 (0.80)
4.52 (0.80)
4.62 (0.80)
4.48 (0.80)
Emotional stability 3.83 (0.73) 3.82 (0.78) 3.83 (0.72)
Chronic condition 21% 27% 19%
Immigrant 14% 17% 13%
Born in East-Germany 4% 10% 2%
Monthly Income
Below modal
Modal (€2.500 net)
Above modal
Having a job (% yes) 44% 44% 44%
Household situation
At parents’ home
With partner
Flat-sharing with others
Note: Significance levels at the 10%, 5%, and 1% level are denoted by
, *, and ** respectively
Martijn Hendriks, Kai Ludwigs, Ruut Veenhoven
Why are locals happier than internal migrants?
Table 3. Univariate differences in happiness and subjective well-being.
Note: Bonferroni adjustment for multiple dependent variables.
Significance levels at the 10%, 5%, and 1% level are denoted by
, *, and ** respectively
Model A all covariates, except for
household situation
Mean difference
(df = 134)
Effect size
Adj.Mean SE Adj. Mean SE Locals-Migrants F -statistic
Overall happiness
0. 60
1-item life satisfaction (0-10) 6.60 0.19 5.97 0.32 0.63
Affect Balance
(-5; 5)
5-item SWLS
4.74 *
Eudaimonic well-
(1-7) 5.43 0.08 5.12 0.13 0.31
Domain satisfactions (0-10) 6.77 0.13 6.31 0.21
Day reconstruction
Experience sampling (0-10) 6.53 0.08 6.32 0.14
Model B - All covariates included
Mean difference
(df = 131)
Effect size
Adj.Mean SE Adj. Mean SE Locals-Migrants F -statistic
Overall happiness
1-item life satisfaction
Affect Balance
(-5; 5)
5-item SWLS (1-7) 5.06 0.09 4.63 0.16
Eudaimonic well-being
Domain satisfactions
Day reconstruction
Experience sampling
Martijn Hendriks, Kai Ludwigs, Ruut Veenhoven
Why are locals happier than internal migrants?
Table 4. Happiness from a trait-like perspective (DRM-data)
Note: Mean time a day corrected for differences in all covariates listed in table 1.
Significance levels at the 10%, 5%, and 1% level are denoted by
, *, and ** respectively
Mean time a day (Hours:minutes) F-statistic
Social leisure/entertainment 1:22 1:19
Social drinks and partying 0:19 0:05 7.66**
Visiting cinema, theatre, or sports 0:08 0:11
Talking 0:34 0:40
Shopping 0:07 0:09
Institutional event (e.g. church-event) 0:14 0:14
Active Leisure 0:55 0:32
Intimacy/sex 0:08 0:07
Exercising 0:24 0:12
Hobbies 0:23 0:13
Passive Leisure 2:50 2:48
Reading 0:08 0:07
Watching TV 1:28 1:27
Listening to music 0:05 0:08
On the Computer 0:18 0:39 4.18*
Resting 0:51 0:27
Other leisure
Daily activities 4:09 4:30
Eating 1:09 1.22
Taking care of others 0:12 0:20
Cooking 0:13 0:09
In transit 1:40 1:42
Getting up and ready 0:55 1:06
Work-related activities 5:57 6:14
Housekeeping 0:37 0:40
Working 1:09 1:07
Studying 4:11 4:27
Total 16:16 16:09
Interaction partners
Partner 2:09 1:51
Friends 3:43 4:00
Direct family 1:40 1:56
Alone 7:16 7:10
Colleagues 1:21 1:21
Total 16:09 16:18
Elsewhere out of house 6:20 5:20 3.35
At home 7:51 8:26
At work 1:05 1:30
In public transport/vehicle 0:55 1:03
Total 16:11 16:19
Martijn Hendriks, Kai Ludwigs, Ruut Veenhoven
Why are locals happier than internal migrants?
Table 5. Happiness from a state-like perspective in the ESM and the DRM
Note: Results are mean-adjusted for differences in all covariates listed in table 1.
The five overarching categories are weighted for frequency of performing the underlying specific activities.
Significance levels at the 10%, 5%, and 1% level are denoted by
, *, and ** respectively
Social leisure/entertainment 7.87 7.71 7.42 7.17
Social drinks and partying 8.32 7.96 7.65 7.80
Going to cinema/theatre/sports 8.09 8.26 7.71 7.47
Talking 7.79 7.60 7.03 7.15
Shopping 7.59 7.42 7.72 7.05
Institutional events (e.g. church event) 7.07 7.36 7.12 7.05
Active Leisure 7.74 7.48 7.20 7.26
Intimacy/sex 8.37 6.84 7.74 7.35
Exercising 7.72 7.15 2.72
7.32 7.08
Hobbies 7.24 7.57 6.97 6.90
Passive leisure 6.72 6.92 6.52 6.34
Reading 7.58 5.48 7.71* 6.81 6.52
Watching TV 7.31 7.18 6.82 6.79
Listening to music 7.00 7.31 6.99 6.50
On the Computer 6.40 6.97 2.93
6.52 6.59
Resting 5.97 6.41 5.95 5.84
Other leisure 7.63 7.27 7.15 7.22
Daily activit
ies 6.47 6.27 6.53 6.34
Eating 7.44 6.95 5.89* 7.04 6.72 3.15
Taking care of others 6.96 5.68 7.76 7.39
6.68 5.97 6.87 6.52
In transit 6.29 5
.94 6.40 6.33
Getting up and ready 5.65 5.47 6.08 6.00
Work-related activities 6.18 6.01 6.10 5.94
Housekeeping 6.31 5.97 6.47 6.00 2.96
Working 6.25 6.26 6.14 6.29
Studying 6.10 5.99 6.02 5.79
Interaction partners
Partner 7.45 7.16 6.90 7.10
Friends 7.28 6.82 5.76* 7.08 6.70 4.43*
Direct family 7.19 6.77 6.86 6.47 3.22
Alone 6.16 6.06 6.11 6.00
Colleagues 6.14 6.17 6.02 6.20
Elsewhere out of house 6.90 6.63 6.76 6.45 3.30
At home 6.54 6.32 6.39 6.28
At work 6.21 6.11 6.07 6.00
In public transport/vehicle 5.96 5.83 6.04 6.35
Martijn Hendriks, Kai Ludwigs, Ruut Veenhoven
Why are locals happier than internal migrants?
Table 6.Unraveling the happiness-difference of eating (DRM).
Note: Percentages and means are adjusted for differences in all covariates listed in table 1.
Significance levels at the 10%, 5%, and 1% level are denoted by +, *, and ** respectively
Interaction partners
Momentary happiness
Locals Migrants F-statistic
Direct family
Colleagues 1% 2% - -
Martijn Hendriks, Kai Ludwigs, Ruut Veenhoven
Why are locals happier than internal migrants?
Note: OLS estimation. Standard errors in parentheses.
Significance levels at the 10%, 5%, and 1% level are denoted by
, *, and ** respectively
Model 1 – Controlling for personal characteristics (df=130)
Internal migration
0.91** (0.34)
0.40* (0.19)
0.201 0.218 0.248 0.268 0.101 0.205
Adjusted R-squared
Model 2 – Additionally controlling for time-allocation (df=124)
Internal migration
0.50 (0.32)
0.38 (0.40)
0.80* (0.35)
0.26 (0.19)
0.24* (0.17)
0.31 (0.27)
Social leisure
0.10 (0.13)
0.14 (0.17)
0.11 (0.15)
0.07 (0.08)
Active leisure
0.37* (0.15)
0.53** (0.19)
0.23 (0.17)
0.25** (0.09)
0.08 (0.08)
Passive leisure
0.05 (0.07) -
0.08 (0.09)
0.19 (0.08)
(0.05) -
0.11** (0.04) -
0.02 (0.06)
Other leisure
0.01 (0.14) -
0.01 (0.17)
0.24 (0.15)
0.07 (0.08) -
0.02 (0.07)
0.04 (0.12)
Daily activities
0.06 (0.06)
0.11 (0.07)
0.03 (0.07)
0.01 (0.04)
0.02 (0.03)
0.01 (0.05)
0.02 (0. 05) -
0.05 (0.05)
0.04 (0.03) -
0.02 (0.03) -
0.09* (0.04)
0.250 0.295 0.289 0.336 0.183 0.268
Adjusted R-squared
0.099 0.153 0.146 0.203 0.019 0.129
Model 3 – Additionally controlling for ‘saddening’ effects (df=122)
Internal migration
0.31 (0.32) -
0.18 (0.40)
0.59 (0.36)
0.19 (0.20)
0.11 (0.27)
Feeling during eating
0.39* (0.16)
0.48* (0.20) 0.29
0.21* (0.10)
0.21** (0.08)
Feeling with friends
0.10 (0.16)
0.02 (0.20) 0.25 (0.18)
0.00 (0.10)
0.07 (0.08)
0.31* (0.14)
0.297 0.333 0.327 0.363 0.246 0.332
Adjusted R-squared
0.141 0.186 0.178 0.222 0.079 0.185
Overall happiness
1-item life satisfaction
Affect Balance
(-5; 5)
Table 7. The incremental value of including daily life experiences.
Martijn Hendriks, Kai Ludwigs, Ruut Veenhoven
Why are locals happier than internal migrants?
Table 8: Two stage treatment model
Probability to migrate
B (SE)
Overall happiness
B (SE)
Distance to psychology-
program (instrument)
(0.00) Internal migration -
Gender 0.02
Constant -4.55
Note: B’s of full set of covariates not reported.
Significance levels at the 10%, 5%, and 1% level are denoted by
, *, and ** respectively
Martijn Hendriks, Kai Ludwigs, Ruut Veenhoven
Why are locals happier than internal migrants?
... For example, Oishi et al. (2007) showed that residential mobility was associated with the relative centrality of one's personal self over the collective self. Moreover, it plays a significant role in shaping one's social relationships (Lun et al., 2012(Lun et al., , 2013Oishi et al., 2013) and influencing well-being (Hendriks et al., 2016;Oishi & Schimmack, 2010;Oishi et al., 2012b;Oishi, 2010;Price et al., 2018). ...
... Second, the current work contributes to research on residential mobility. Abundant work has used psychological science as its backdrop to explore how residential mobility influences people's self-concept (Oishi et al., 2007), social relationships (Lun et al., 2012(Lun et al., , 2013Oishi et al., 2013), and well-being (Hendriks et al., 2016;Oishi & Schimmack, 2010;Oishi et al., 2012b;Oishi, 2010;Price et al., 2018). Consumer research on this topic, however, is limited (Koo, 2022;Oishi et al., 2012a;Wang et al., 2021). ...
... Third, scholars of residential mobility have largely shown that residential mobility leads to adverse outcomes-such as poorer educational outcomes (Friedman-Krauss & Raver, 2015;Metzger et al., 2015;Schmitt et al., 2015), lower levels of well-being (Hendriks et al., 2016;Oishi & Schimmack, 2010;Oishi et al., 2012b;Oishi, 2010;Price et al., 2018), and a lower sense of community belonging (Oishi et al., 2007(Oishi et al., , 2009(Oishi et al., , 2015. (See some exceptions: residential mobility can reduce ethnocentrism (De et al., 2015) and contribute to improving intergroup relationships by reducing intergroup bias , as well as lead to higher donations to distant beneficiaries (Wang et al., 2021 ...
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A major challenge in new product development is how to increase consumers' adoption of new offerings. Using the socio‐ecological perspective, we reveal a largely ignored but important social factor that alters consumers' new product adoption. Specifically, we propose that residential mobility—the frequency with which individuals change their residence—acts as an antecedent of new product adoption. Six studies—using different operationalizations of residential mobility—provide convergent evidence that residential mobility (vs. stability) augments new product adoption in both laboratory settings and real business settings. This effect is driven by openness to new experiences and moderated by the voluntariness of moving. Our findings add to the literature on new product adoption and residential mobility. Moreover, marketers should take residential mobility into full consideration when designing marketing strategies for new products and presenting contextual cues to activate consumers' residential mobility mindset to enhance their acceptance of new products.
... Bárcena-Martín & Pérez-Moreno, 2017;Hadjar & Backes, 2013;Sand & Gruber, 2018). The few studies examining internal migration have found similar effects to those most often reported in the international migration literature, with internal migrants generally reporting lower levels of happiness than the native population, attributed to poor social capital, lower self-esteem, stress, and lower engagement in activities (Ek et al., 2008;Hendriks et al., 2016). The vast majority of studies on both internal and international migration have focused on European and other Western countries, highlighting a gap regarding internal migration within lower-income countries. ...
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Communities with high levels of in-migration can experience substantial social, cultural, and economic change due to the upheaval in social dynamics and changes to the economy. Such upheaval can result in between-group inequalities amongst the native and migrant populations, with migrants tending to have lower levels of wellbeing compared to those who were born in the area. Through utilising a culturally adapted wellbeing measurement tool, the Indonesian Wellbeing Scale, this study examines the native-immigrant wellbeing gap in Papua, Indonesia. Papua has historically experienced high levels of conflict, and is highly ethnically diverse, making it a unique context to examine the native-immigrant wellbeing gap. Drawing on data collected in 2020, the results indicate that the immigrant population has significantly higher levels of wellbeing when controlling for a number of socio-demographic characteristics. This finding is driven by all wellbeing dimensions within the Indonesian Wellbeing Scale: spirituality, social relations, material needs, and self-acceptance. Possible explanations for this include the happy migrant hypothesis, levels of wellbeing pre-migration, and impacts of the migration process. These findings have important implications for migration within both Indonesia, and in similar contexts throughout the world, highlighting that care must be taken when implementing migration policies to ensure that receiving communities are not negatively affected. Furthermore, the study emphasises the value in using a multidimensional, culturally adapted wellbeing measurement tool that was developed in consultation with individuals in the community to ensure we are more closely measuring what matters to people.
... As a result, they acquire knowledge and skills beyond their agricultural expertise and must alter their expectations accordingly. Internal migrants, who move from rural to urban areas within their own countries, have stressful experiences and less happiness, so they need a good way to deal with stress if they want to get along with the locals and be accepted by them (Güngör, 2020;Hendriks et al., 2016). In the context of Nepal, people from different rural areas prefer moving to Kathmandu and settling there for various reasons, such as education, trade, employment, marriage, health treatment, and learning new skills for international migration. ...
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This article explores the socio-economic adjustment of rural migrants in the cities of Kathmandu Valley. This study was conducted among Sampang Rai migrants and utilizes the network theory of migration. Information was gathered through questionnaire using KoBoToolbox, in-depth interviews, and observation in the study areas. Sampang Rais migrate to the Kathmandu Valley to get an education, find better work, experience city life, help their families, get medical treatment, and learn new skills. The already established and available networks facilitate the selection of migration destinations and socio-economic adjustment in Kathmandu Valley. Friends, families, earlier migrants, and institutions assisted migrants to adjust socially and economically in the destination areas by providing information, physical resources, material resources, and sociocultural support. Sampang Rai migrants also made efforts to diversify their livelihood, keep strong connections with friends and families, join religious communities, learn new skills, exchange labour and encourage one another while they go through the process of socio-economic adjustment.
... Moving often means that one is displaced to an environment with few social connections, and one must start establishing social relationships from scratch (Watson et al., 2019). Especially, they may not know what resources or activities exist in their new neighborhood or community, and even if they do know, they may have no one to go with (Hendriks et al., 2016). Considering overwhelming to-do lists and errands postmove, people may not have time and opportunities to connect with others in the first few months post-move, which might lead to higher loneliness. ...
Background People with serious mental illnesses (SMI) have higher levels of loneliness than the general population. Furthermore, people with SMI tend to be less satisfied with their housing and tend to move more frequently. Aim This study aims to examine relationships between housing variables (whom they live with, duration of residence, and satisfaction) and loneliness among individuals with SMI. Methods Data were collected from 188 adults with SMI in greater Philadelphia area. Classification and Regression Trees (CART) were used to examine whether whom they live with, duration of residence, and housing satisfaction were associated with loneliness. Results Housing satisfaction was found to be the most prominent predictor of loneliness. Those who were unsatisfied with their overall housing conditions always had the highest level of loneliness, regardless of other factors. Even if they were satisfied with their housing conditions, their loneliness was higher if they had just moved to the new residence. Participants had lower loneliness the longer they lived in a residence and had the lowest loneliness levels after about three years. Conclusion Housing is associated with loneliness among people with SMI. Psychiatric service providers should increase support to factors contributing to housing satisfaction and duration of residence, including active engagement in the community.
... Residential mobility-that is, the frequency of moves (Oishi, 2010)-is a key socio-ecological factor leading to substantial changes in physical and social environments. In the last decade, many studies have demonstrated how residential mobility is associated with people's psychological processes (Oishi and Talhelm, 2012;Choi and Oishi, 2020), such as self-concept (e.g., Oishi et al., 2007a), group membership and in-group cooperation (e.g., Oishi et al., 2007bOishi et al., , 2009, personality (e.g., Oishi and Schimmack, 2010;Jokela, 2021), and physical and mental health (e.g., Fowler et al., 2015;Hendriks et al., 2016). Although such research has revealed its influence on personal processes (i.e., How do people recognize themselves?) or social processes (i.e., What kinds of social relationships and networks do people construct? ...
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The present study examined the effect of residential mobility on impression formation. In the study, participants were first engaged in a residential mobility priming task where they were asked to imagine and describe either frequent moving life (high-mobility condition) or less frequent moving life (low-mobility condition). They then evaluated their attitudes toward four types of target persons: competent vs. incompetent and warm vs. cold. As a result, in the high-mobility condition, the effect of competence was observed only when participants evaluated a warm person, whereas in the low-mobility condition, it appeared only when participants evaluated a cold person. The potential influence of individual residential mobility on the relationship formation is also discussed.
... Firstly, we show that the negative relationship between subjective wellbeing and its distribution is not confined to countries or to large regions, but also holds at the local city and neighbourhood levels. This contribution is significant because the local scale has possibly the most important bearing on our wellbeing (Hendriks et al., 2016). Our second contribution is to identify several behavioural underpinnings of the wellbeing and wellbeing inequality relationship. ...
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Our subjective wellbeing is a mix of our personal and community wellbeing. One indication of their close relationship is the strong negative correlation between our own subjective wellbeing and the degree of subjective wellbeing inequality within our community. This negative relationship reflects our innate and socialized inequality aversion and holds regardless of whether the group is large as in the case of countries or small in the case of local neighbourhoods. While the country case has been well documented in the subjective wellbeing literature, the relationship between the local community distribution of subjective wellbeing and individual subjective wellbeing has received little attention. In this paper we demonstrate the sensitivity of individual life satisfaction to the distribution of life satisfaction within electoral wards in urban New Zealand and explore several possible behavioural drivers. We find that having social support and feeling a sense of community both reduce the negative effects of local subjective wellbeing inequality, while being less socially engaged exaggerates them. Our results highlight the potential that programmes aimed at reducing wellbeing inequalities within local communities might play in raising individual as well as average wellbeing.
Studies on subjective well-being (SWB) and its influencing factors have attracted much attention during the past years. The proportion of migrant workers has reached 20% in China, but their levels of SWB are usually lower than that of local residents. To facilitate the social integration of migrant workers, it is a necessity to improve the SWB of migrant workers. The phenomena of pseudo-urbanization could be soothed accordingly in China. A large body of literature has looked into the housing types and living conditions of migrant workers, and the impacts on their SWB. However, little research has investigated the impacts of housing pathways on the SWB of migrant workers. This study aims to fill the research gap. Ordinal logistic regression was conducted using the data from China Family Panel Studies (CFPS). Housing pathways were significantly different among migrant workers, although many of them had housing tenure no changed (i.e., keep homeownership), housing size no changed, and no improvements in housing qualities. The improvement of housing size and housing qualities had considerably positive effects on migrant workers’ SWB. It is essential to improve housing conditions of migrant workers to increase their levels of SWB and social integration in China.KeywordsHousing pathwayMigrant workersSubjective well-being
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The present paper sheds light on the motives of economic migrants―an aspect that has not been discussed at a general level so far. Previous work has only focused on specific fields of interest and used different terminologies, hence impeding comparison and the synthesis of findings across studies. Derived from theoretical, empirical, and analytical research outcomes, the paper concludes that economic migrants' movements are influenced by the socio-demographic factors of 'age' and 'education' and are motivated by both the economic motives of 'expected income' and 'employment' and the economic-related motives of 'corruption', 'amenities' and 'happiness'. Furthermore, these motives reveal a typical profile of economic migrants: a typical economic migrant is characterized by being of working age, highly educated and male, and by wishing to migrate to developed countries to achieve a fulfilling life.
Drawing upon data from the China Labor Dynamics Survey, this study examines the mediating role of social exclusion between migrant status and subjective well-being. Our empirical findings suggest that not only current migrants are socially excluded in the cities of destination but also returned migrants are insufficiently reintegrated into their villages of origin. The experienced social exclusion, in particular, the lack of social support, the feeling of vulnerability, and the deficiency in the sense of community persistently undermines the subjective well-being of both current and returned migrants. Our findings shed new light on how migration decisions could affect people’s perceptions of their lives and create inequality across social groups.
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Using data from the Gallup World Poll and Latinobarometro, we examinethe relationship between life satisfaction, vulnerabilities, and migration in LatinAmerica. We look at three kinds of insecurities: nutritional, personal, and job insecurity.We find that controlling for income, migration experience by a householdmember increases life satisfaction of the respondent. We also find, however, thatnutritional insecurities interact negatively with migration. In other words, hungerhas a devastating effect on happiness, especially in households where a member isabsent due to migration.
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The migration literature shows that Latin American emigrants, in addition to immigrants generally, report lower happiness levels and satisfaction with financial success than natives do in their destination country. We use a survey question from the Latinobarometro on intent to migrate to shed light on attitudes and aspirations prior to migration. We find that potential migrants report the qualities of "frustrated achievers" (e.g. respondents with high objective success in terms of income, but who report low satisfaction with their economic gains) and are less happy than average. Our analysis supports the hypothesis that unhappiness drives migration, while not disproving that migration also creates unhappiness; it is likely that these factors are not mutually exclusive and that they reinforce one another. Our work addresses the broader question of whether unhappiness is a necessary condition for major societal change.
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Evaluative processes refer to the operations by which organisms discriminate threatening from nurturant environments. Low activation of positive and negative evaluative processes by a stimulus reflects neutrality, whereas high activation of such processes reflects maximal conflict. Attitudes, an important class of manifestations of evaluative processes, have traditionally been conceptualized as falling along a bipolar dimension, and the positive and negative evaluative processes underlying attitudes have been conceptualized as being reciprocally activated, making the bipolar rating scale the measure of choice. Research is reviewed suggesting that this bipolar dimension is insufficient to portray comprehensively positive and negative evaluative processes and that the question is not whether such processes are reciprocally activated but under what conditions they are reciprocally, nonreciprocally, or independently activated. (PsycINFO Database Record (c) 2012 APA, all rights reserved)
The objective of this research was to investigate the impact of household socioeconomic characteristics on three categories of leisure expenditures. Tobit analysis was applied to data from the U.S. 1988–89 Consumer Expenditure Surveys. The dependent variables were household expenditures on active leisure, passive leisure and social entertainment The results indicated that household income, the number of adults, and the age, race and education of the household head had a significant impact on leisure expenditures.
In response to several special characteristics of the so-called "new immigration" and to the well-known weaknesses of classical assimilation theory several theoretical suggestions have recently been made and discussed, including, in particular, the "Theory of Segmented Assimilation" and the "New Assimilation Theory". In addition to the (classical) structural outcome of assimilation, these theories assume two other possible outcomes: ethnic stratification as an enduring social descent of following generations and selective acculturation as social advancement by using and retaining ethnic resources and identities. This contribution reconstructs these theoretical developments and the presumed structural outcomes as special cases of a comprehensive model, i. e. the model of intergenerational integration, and systematizes sub-processes and single mechanisms outlined by the various theories. An important result is also the identification of conditions and background processes that do not necessarily occur empirically, but that underlie the different theories and structural outcomes as well as the proposed model of intergenerational integration.