Working PaperPDF Available
1
Peter H. van der Meer
Rudi Wielers
16016-HRM&OB
Happiness, unemployment and self-
esteem
2
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SOM RESEARCH REPORT 12001
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Happiness, unemployment and self-esteem
Peter H. van der Meer
University of Groningen, Faculty of Economics and Business, Department HRM & OB
p.h.van.der.meer@rug.nl
Rudi Wielers
University of Groningen, Faculty of Behavioural and Social Sciences, Department of
Sociology/ICS
Happiness, unemployment and self-esteem
By
Peter H. Van der Meer
Faculty of Economics and Business
University of Groningen
P.O. Box 800
9700 AV Groningen
Tel. +31503633663
e-mail: p.h.van.der.meer@rug.nl
and
Rudi Wielers
Department of Sociology/ICS
University of Groningen
Grote Rozenstraat 31
9712 TG Groningen
The Netherlands
r.j.j.wielers@rug.nl
Abstract
Unemployment has a severe lasting effect on the subjective well-being of people. These negative
effects of unemployment have been labeled as psychic costs, because the loss of income cannot
explain these negative effects. In this paper we will contribute to the explanation of the negative effect
of unemployment on happiness. We do so by arguing that the loss of self-esteem is the driving force of
the reduction in well-being. Very recently economists (Almlund, Duckworth, Heckman, & Kautz,
2011; Borghans, Duckworth, Heckman, & Bas, 2008; Cunha, Heckman, & Schennach, 2010;
Heckman, Stixrud, & Urzua, 2006) have paid attention to the effects of non-cognitive factors, like
personality characteristics, on wages and happiness. In this paper we will argue that of these non-
cognitive factors like personality traits and characteristics it is most likely that self-esteem helps to
explain the negative effect of unemployment and so not much other non-cognitive factors like the big
five personality traits. Empirically we will show that self-esteem affects happiness, that unemployment
affects self-esteem and that self-esteem explains a big part of the effect of unemployment on
subjective well-being.
In this study we use the LISS (the Dutch Longitudinal Internet Studies for the Social sciences)
panel to test the main hypotheses. To test our hypotheses we use a variety of methods. We use
different regression models, starting with simple OLS-regressions and ending with instrumental
variables for panel-data models. We estimate two different equations, one with subjective well-being
as the dependent variable and one with self-esteem as the dependent variable.
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Happiness, unemployment and self-esteem
1 Introduction
Unemployment has a severe effect on the subjective well-being
1
of people. This has been shown over
and over again (A. E. Clark & Oswald, 1994; Frey & Stutzer, 2002; Layard, 2005; Winkelmann &
Winkelmann, 1998). An obvious reason for this drop in well-being is of course the loss of income. But
that is not the major explanation as Winkelmann and Winkelmann (1998) already showed. The
psychic costs of unemployment are much bigger than the loss of income. But worse than that:
unemployment has lasting, scarring effects. That is, long term unemployed remain unhappy even if
they find a job again. They feel and stay unhappy. This is remarkable because this differs from other
major life events (A. E. Clark, Diener, Georgellis, & Lucas, 2008). People become unhappy if they
divorce and if a loved one dies. But from these major life events people recover. After a few years
their well-being has returned to the same level as before this life event. In case of marriage and child
birth we see the opposite movement. First an increase in well-being and then after a while a decrease
to the old base level. Only unemployment appears to have a lasting, scarring effect on the well-being
of people. These results not only hold for Germany but are confirmed for Great Britain as well (A. E.
Clark & Georgellis, 2013). The question arises why is this so? Why has unemployment such a major
impact on the subjective well-being of people? This question is until now mainly unanswered and is at
the heart of this paper.
To answer this question we start by summarizing research about the relation between (long
term) unemployment and happiness. We know that unemployment generates financial and psychic
costs and that of these two the psychic costs are much higher than the financial costs (Winkelmann &
Winkelmann, 1998). Even when the unemployed get a generous unemployment benefit, they still feel
unhappy. These are the psychic costs. Van der Meer (2014) explained these costs by a loss in comfort
and social well-being. Frey (2008) would say that unemployed loose self-esteem, relatedness and
commitment. These three, as well as the social well-being are heavily damaged by unemployment. In
this paper we will argue that the loss of self-esteem explains this negative effect of unemployment on
happiness.
We will argue that unemployment affects self-esteem and that self-esteem affects happiness.
Self-esteem is the result of reflected appraisals, social comparison and self-attribution (Rosenberg,
Schooler, & Schoenbach, 1989). Because having a job is such an important of life and is used as the
basis of comparison with others, job loss causes a loss of self-esteem. Becoming unemployed lowers
someone’s reflected appraisal and reduces the outcome of the social comparison, thereby lowering
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In this paper we use the terms subjective well-being, happiness and well-being as synonyms. Subjective well-
being is the encompassing term of both life satisfaction and happiness, but for the readability we mostly use the
happiness or happy where we mean subjective well-being.
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self-esteem. This lower self-esteem reduces happiness as it is part of subjective well-being as
explained by Frey (2008). Becoming unemployed tells you something about yourself and that message
is not always very positive, to say it mildly, and probably will have lasting effects on your self-esteem
and thereby on your happiness. This argument is at the heart of this paper and will be tested in the
empirical part.
In this paper we will contribute to the explanation of the negative effect of unemployment on
happiness. We do so by arguing that the loss of self-esteem is the driving force of the reduction in
well-being. Very recently economists (Almlund, Duckworth, Heckman, & Kautz, 2011; Borghans,
Duckworth, Heckman, & Bas, 2008; Cunha, Heckman, & Schennach, 2010; Heckman, Stixrud, &
Urzua, 2006) have paid attention to the effects of non-cognitive factors, like personality
characteristics, on wages and happiness. In this paper we will argue that of these non-cognitive factors
like personality traits and characteristics it is most likely that self-esteem helps to explain the negative
effect of unemployment and so not much other non-cognitive factors like the big five personality
traits. Empirically we will show that self-esteem affects happiness, that unemployment affects self-
esteem and that self-esteem explains a big part of the effect of unemployment on subjective well-
being.
In the next section we start with an overview of the stylized facts that needs to be explained. In
section three we present a possible explanation of these stylized facts and formulate hypotheses that
we will test in this paper. Section four contains a description of the data and methods that we use to
test the hypotheses. In section five we present some descriptive statistics to show the differences on
the main variables between employed and unemployed. In section six we present the results from
different types of analyses that we did to test the hypotheses. In the final section we summarize and
conclude the paper and make some suggestions for future research.
2 What we know about unemployment and happiness
The main basic finding of earlier research is that unemployed are unhappier than employed people,
even if we control for all factors that affect happiness, even income (A. E. Clark & Oswald, 1994;
Frey & Stutzer, 2002; Layard, 2005; Winkelmann & Winkelmann, 1998). This effect shows that
unemployment comes with psychic costs. These same kinds of analyses show that the psychic costs of
unemployment are much higher and much more severe than the financial costs. The psychic costs are
best shown by the fact that reemployment in a dissatisfying job does not enhance psychological health
relative to that of unemployed persons (O’Brien and Feather, 1990; Winefield, Tiggemann and
Winefield, 1990). So reemployment only has a positive effect if the new job really is satisfying. It
needs to give something extra to compensate the psychic costs of unemployment.
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We know that voluntary unemployed are happier than involuntary unemployed (A. Clark,
Georgellis, & Sanfey, 2001). Involuntary unemployed are (almost) as happy as the employed. We also
know that first time job seekers, starters on the labour market, are as happy as employed people (Frey
& Stutzer, 2002; A. E. Clark & Oswald, 1994; Pichler, 2006; Winkelmann & Winkelmann, 1998). The
young persons who just left school, unemployed looking for a first job are not negatively affected by
unemployment. They probably know or hope that they soon will find a job and will start their career
on the labour market. They have not yet had the experience of a job and what this does to their
happiness. They also did not have the experience of being fired and what that does to happiness. They
simply do not know.
We also know that the elderly are less affected by unemployment (Frey & Stutzer, 2002; A. E.
Clark & Oswald, 1994; Winkelmann & Winkelmann, 1998; Frey, 2008, p. 47). They know that they
will retire soon and they prepare for (early) retirement. We also know that retired people are at least as
happy as employed people (Blanchflower & Oswald, 2008; Lelkes, 2008)
These three findings, the voluntary unemployed, the school leavers and the almost retired,
teach us that unemployment is mainly a problem for the middle-aged individuals who are (very) busy
making a career and who experienced how a job or career affects happiness.
Next to the single effect of unemployment we know that the duration of unemployment has an
additional effect on happiness. People who are unemployed for six month or longer are unhappier than
people who have experienced unemployment of a shorter duration. In that sense we know that the
negative effect of unemployment depends on the unemployment duration (A. Clark et al., 2001; Daly
& Delaney, 2013; Gangl, 2004; Knabe & Rätzel, 2011). Long term unemployment has a lasting,
scarring effect on happiness whereas a short period of unemployment only has a short term negative
effect on happiness, but is as such not scarring. People return to their normal level of happiness after a
short period of unemployment. This corresponds with the effect found by Clark (et al., 2008) that
unemployed do not recover from unemployment. They only investigated the effect of unemployment
on people who remained unemployed up to five years. They did not research what happened to the
unemployed once they became employed again.
We furthermore know that becoming unemployed during an economic crisis is less damaging
than becoming unemployed in an economic boom. To be more precise we know that the level of
unemployment reduces the effect of unemployment. People living in regions or times with high levels
of unemployment are happier than unemployed who live in regions or times with low levels of
unemployment (A. Clark, 2003; Di Tella, MacCulloch, & Oswald, 2003). This is in line with the
results of Stutzer and Lalive (2004) who find that social norms partly explain why unemployment has
negative effects on well-being. Unemployed in Swiss kantons with stricter norms suffer more and
have a shorter duration of unemployment. However one has to keep in mind that until recently
unemployment rates were low in Switzerland.
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3 Unemployment, self-esteem and happiness
What does explain these stylized facts? The main argument that we put forward is that unemployment,
especially a long period of unemployment, comes with a loss in self-esteem (Goldsmith, Veum, &
William Jr., 1996). Unemployment creates a loss in self-esteem, because losing your job implies that
you have failed or that you see yourself as failing. Rosenberg (et al., 1989) write that among the
principles of self-esteem are reflected appraisals, social comparison, and self-attribution. Self-esteem
is thus viewed as a product of social interaction. Reflected appraisals are how people think they are
viewed and seen by others. Becoming unemployed results in negative or lower reflected appraisals.
The principal of social comparison holds that people judge themselves on the basis of comparisons
with others. Self-attribution considers how naïve observers attribute motives, intentions etc. to
themselves on the basis of their observation of their actions. Because having a job is such an important
part of life results in reflected appraisals and is used as basis of comparison with others, job loss
causes a severe loss in self-esteem (i.e. Leary & Baumeister, 2000).
Via self-attribution and reflected appraisals this loss in self-esteem is bigger if you have to
blame yourself for becoming unemployed, than if you can blame someone, or something, else. If you
are unable to perform at the level that is asked for, you are being fired because you underperform. This
shows that you are a looser who is unable to deliver what is being asked for and you cannot uphold the
norm. This will result in lower reflected appraisals and thereby in lower self-esteem. The fact that you
have become unemployed shows to everyone what a looser you are, too. You are unable to take care
of yourself and may be also of others who depend on you. If you are really to blame for your own
unemployment this should have a severe negative effect on self-esteem and happiness, among other
things. If you became unemployed due to other reasons the negative effect of unemployment on self-
esteem and happiness should be smaller.
Self-esteem as a result of social comparison also explains the smaller effect of mass
unemployment on happiness. If you become unemployed in an economic crisis you can blame your
employer, the union, the economic crisis, the government that reduced their own budget, the
competitor that put your employer out of business, the hedge funds that blew up your business, or
anyone else that you can think of. You are not the only one who becomes unemployed. Of course
compared to the employed you will lose some ground, but compared to all the others who become or
are unemployed you lose nothing, making the effect of unemployment less severe. That is very
different from becoming unemployed in an economic upturn. Then you are not able to blame an
outsider. You have to blame yourself of not being able to keep your job. You have to blame yourself
especially if you stay unemployed for a longer period. That really affects your self-esteem, because it
shows that you are someone who is not fit for the labour market or for society. If you could
accomplish something then you would have found a new job quickly in an economic upturn, when the
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economy is booming. Then you really have no self-esteem and the effect of unemployment should be
bigger. And that is what has been found.
A more permanent loss in self-esteem would also explain the scarring and scaring effect of
long-term unemployment, especially if the loss of employment is the result of lower reflected
appraisal. A permanent loss in self-esteem creates a scar which causes a permanent reduction in well-
being. And this loss in self-esteem also causes a scaring effect because low self-esteem makes it more
difficult to perform on the job and increases the probability of future job loss, if employment has been
regained. That is also the reason why a job loss as a major life-event has a more permanent effect than
other life-events as divorce, the loss of a friend, marriage and having children. These life-events
probably have a much smaller impact on self-esteem. In this research we are able to compare the
effects of having a partner and having children at home with the effect of unemployment on self-
esteem.
A further prediction on basis of this idea would be that individuals who became redundant
suffer less from unemployment than individuals who were fired. If you become redundant or are being
laid-off in an economic crisis you can blame someone else for your unemployment. Also you are not
the only one, so the social comparison is not that negative. Things differ if you were fired. That results
in low social comparison and reflected appraisal. This second event therefore comes with a bigger loss
in self-esteem and thus has bigger effects on happiness. If the blame is on yourself than it will become
difficult to find a new job again, your future prospects are diminished (Knabe & Rätzel, 2011).
Unfortunately at this moment we are unable to test this hypothesis.
The loss in self-esteem also explains why younger and older persons are less affected by
unemployment than middle-aged persons. Young persons who are at the start of their career still have
to find their way on the labour market. They are still searching for the right employer to work for. In
that stadium being, or becoming unemployed is less harmful. It will hardly affect social comparison
and reflected appraisal. A school leaver will hardly be affected by unemployment until the first job and
may be less affected by the loss of his first job. He is still sure that he will find a second job and if
unemployment is caused by the termination of a temporary contract the self-esteem of the young
person is hardly damaged. A possible test would be to compare the self-esteem between unemployed
school leavers and unemployed young persons who lost their job. We will not do this in this paper.
Someone at the end of his career will also be less affected. An older person knows what he is
worth, because during his career he already showed what he can do and his self-esteem probably will
stay intact. His reflected appraisal will hardly be affected. Unemployment will even be less harmful if
he could leave the organization with a retirement bridge or other allowance (unemployment benefit
that lasts until retirement), so that the drop in income is not too big. In that way his subjective income
remains high until retirement, and he is able to keep up his way of life. Instead of becoming
6
unemployed he is forced into early retirement. That is less harmful than becoming unemployed. Again
we will not test this prediction.
So a loss in self-esteem would explain the stylized facts presented in the previous section.
Therefore we need to look at direct and indirect effects of unemployment on subjective well-being.
The indirect would go via self-esteem, i.e. unemployment lowers self-esteem and thereby subjective
well-being. Becoming unemployed would lower self-esteem, because in comparison with others one
would be lower on the ladder when one becomes unemployed. In that sense would unemployment
have a direct negative effect on self-esteem. In comparison with others one loses when one becomes
unemployed.
We already have direct and indirect results that show that unemployment causes a loss of self-
esteem. Oswald (1997) found that unemployed people are very unhappy. They are so unhappy that the
suicide death rate among unemployed is higher than average. He found that unemployed have a twelve
times greater-than-average chance of attempted suicide, and that the long-term unemployed are
especially at risk. Unemployment appears to be the primary source of unhappiness. Frey (2008, p. 48)
also shows that unemployment produces depression and anxiety and results in losses of self-esteem
and of personal control. Unemployed have a higher death rate and are more likely to commit suicide.
He also showed that individuals who have been unemployed before suffer less. So to some extent they
become used to being unemployed.
According to Kassenboehmer and Haisken-DeNew (2009) unemployment has negative
psychological effects because it leads to a substantial decrease in marital stability, increased mortality,
suicide risk and crime rates. Overall effects of unemployment are large, significant and negative.
Compared to men, women are additionally affected by being fired and company closures. It reduces
their reemployment due to regional immobility. Men relocate to find new employment, women are
attached to their men.
Ayllón (2013) reports a scaring effect of unemployment in Spain. She writes that ‘scarring
effect is known as genuine state dependence’. So unemployment in itself has not such a big effect on
happiness, only because it is a cause of future unemployment. Unemployment increases the
probability of future unemployment, so unemployment scares individuals and because of that we find
the scarring effects of unemployment. The sources of this genuine state dependence may be due to
disincentives effects of unemployment benefits, the decay of human capital, the decline in search
intensity, discouragement of habituation and stigma effects. And these stigma effects might result in a
loss of self-esteem.
Goldsmith (et al., 1996) find evidence on basis of the NLSY that unemployment affects self-
esteem. They directly test and show that becoming unemployed lowers self-esteem. This is one of the
rare researches which shows this direct connection between unemployment and self-esteem. However,
7
they did not look into a possible reverse effect, namely that a lower self-esteem lowers the probability
of finding employment.
From recent research we know that self-esteem has a positive effect on wages (Drago, 2011;
Heckman et al., 2006). De Araujo and Lagos (2013) tested the relation between self-esteem,
educational attainment and wages. They estimated a three equation simultaneous equation model that
treats self-esteem, educational attainment, and real wages as endogenous. They found that wages
directly affect self-esteem, but self-esteem does not directly affect wages, only indirect through
education.
We now also know that non-cognitive factors, like i.e. self-esteem have a bigger impact on
employment than cognitive factors (Heckman et al., 2006). They report similar effects on work
experience. Within this research economists have shown interest in the effects of personality
characteristics on earnings and other labour market outcomes. Personality as measured by the big five
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personality traits does have an impact on earnings (Fletcher, 2013). These big five personality traits
appear to be stable and they cannot be linked to major life events (Cobb-Clark & Schurer, 2012; Lucas
& Donnellan, 2011; Specht, Egloff, & Schmukle, 2011). But Becker, Deckers, Dohmen, Falk, and
Kosse (2012), conclude, on basis of the GSOEP, that the big five explain, independent from other
factors, life outcomes including unemployment.
Another personality trait that has been looked upon is locus of control. This trait refers to the
extent to which individuals believe they can control events affecting themselves. Cobb-Clark and
Schurer (2013) show that locus of control (inside or outside) is surprisingly stable over a four-year
period, particular for those of working age. Changes in locus of control are unrelated to the
demographic, labour market and health events that individuals experience. The intensity of negative
employment life events (i.e. unemployment) is not associated with changes in men’s and women’s
control tendencies. Locus of control is stable, but not time-invariant.
So of these personality traits self-esteem is the only one that is being affected by
unemployment. Contrary to the big five and locus of control, self-esteem is not stable and does vary
with time. So if we would like to test through which personality traits unemployment has an effect on
subjective well-being we should look at self-esteem and not at the big five or locus of control. The big
five can hardly be affected by unemployment because the big five are supposed to be stable over time.
That is after a certain age personality has been formed and will not change much. Also locus of control
has been shown to be surprisingly stable over time. Thus self-esteem is the only personality trait that is
not by definition stable over time and is a.o., a product of social interaction and reflected appraisals,
that will be affected by unemployment.
2
Psychology has a long tradition of research into personality characteristics. It has resulted into what is known
as the big five: openness to experience, conscientiousness, extraversion, agreeableness and neuroticism
8
4 Data and method
In this study we use the LISS (Longitudinal Internet Studies for the Social sciences) panel to test the
main hypotheses. This panel is administered by CentERdata (Tilburg University, The Netherlands).
The LISS panel data were collected by CentERdata through its MESS project funded by the
Netherlands Organization for Scientific Research (NWO), see Scherpenzeel and Das (2010) for more
information.
The LISS panel is a representative sample of Dutch individuals who participate in monthly
internet surveys. The panel is based on a true probability sample of households drawn from the
population register. Households that could not otherwise participate are provided with a computer and
internet connection. A longitudinal survey is fielded in the panel every year, covering a large variety
of domains including work, education, income, housing, time use, political views, values and
personality. The use of this data is open to everyone. More information about the LISS panel can be
found at: www.lissdata.nl. The first wave was held mainly throughout 2008. The sixth wave was held
mainly throughout 2013. At the time of performing the analyses data from six waves were available.
However in wave three and five the personality traits were only asked to twenty per cent of the
respondents instead of all of them. Therefore we limit the analyses to four waves: wave one, two, four
and six.
We chose the LISS panel because it contains measures of the main variables of interest and
because it is a longitudinal data set which makes it possible to do causal analyses and to control for
unmeasured characteristics.
The LISS panel contains two questions that are related to subjective well-being. The first
question is about happiness: ‘On the whole, how happy would you say you are?’. The second question
is about life satisfaction: ‘How satisfied are you with the life you lead at the moment?’. The reliability
(chronbach’s alpha) of these two questions combined is .90, in all separate waves. We therefore
combine these two questions to measure subjective well-being. In doing so, we capture both the more
cognitive evaluation of life as well as a more affective evaluation (Dolan, Peasgood, & White, 2008, p.
95). By combining the measures of happiness and life satisfaction we measure the overarching concept
of subjective well-being.
We differentiate between employed and unemployed. The employment status is captured in
the background variables of the study. Everyone in paid employment is employed, (belbezig = 1),
everyone searching for a job is unemployed (belbezig = 4, 5 and 6). We do not have a reliable measure
of the duration of unemployment. This is not asked in the questionnaire and is very difficult to
construct. We can only see if respondents were unemployed in consecutive waves. We will miss a
period of in between employment, but also a period of in between unemployment if one indicates to be
employed in two consecutive waves.
9
The questionnaire includes a measure of self-esteem. Self-esteem is measured with the ten
item scale of Rosenberg (et al., 1989). The reliabilities of this scale are: .89, .89, .90 and .90 in each of
the waves. The scale is highly reliable.
The LISS panel also contains questions to measure the big five. The big five are measured
with the fifty item version of the Preliminary IPIP Scales (ipip.ori.org). The five personality factors
are: extraversion, agreeableness, conscientiousness, neuroticism and openness to experience. The
reliabilities of extraversion are .86, .87, .87 and .87 in waves 1, 2, 4 and 6. The reliabilities of
agreeableness are: .80, .81, .81 and .81. The reliabilities of conscientiousness are: .77, .79, .79 and .78.
The reliabilities of neuroticism are: .88, .88, .88 and .88. The reliabilities of openness to experience
are: .77, .77, .77 and .76 respectively. These reliabilities correspond with the published ones of the
scales. The reliability of the openness to experience scale is somewhat, although not much lower than
the published one. We do not have a measure of locus of control.
We control for gender, having a partner, children living at home, age and age square,
educational level, subjective health, subjective income, satisfaction with leisure spend, satisfaction
with social contacts, and home ownership. All of these variables are known to affect subjective well-
being (cf. Layard, 2005).
We restrict the analyses to respondents older than nineteen years of age but not older than
sixty years of age. Many respondents younger of age than twenty are still in education whereas many
respondents older than sixty years of age have left the labour market for one reason or another.
Appendix A contains the descriptive statistics of the variables for the four waves, including the
coding. We see a steady decrease in subjective well-being between 2008 and 2013. We see a steady
increase in unemployment as a result of the economic crisis in 2008, but overall unemployment stays
low. We also see a decrease in self-esteem between 2008 and 2013. The big five seem to be more
stable over time, although they do change somewhat. This could be an effect of attrition and additional
sampling of the panel study. We see that the sample becomes smaller from wave to wave. Some
respondents do not fill out every monthly questionnaire and commitment seems to decline overtime.
We did not (yet) test for attrition effects.
Although the data set has particular strengths, it is the only one that we are off, that contains
panel measures of personality traits it also comes with a weakness. The number of unemployed in this
panel is quite low. This corresponds with the low level of unemployment in the Netherlands.
Throughout the crisis and the panel we see an increase in unemployment, but the low numbers limit
some of our analyses. We tried to estimate scarring effects of unemployment, but this proved to be
unsuccessful, mainly due to do low level of unemployment.
To test our hypotheses we use a variety of methods. We start with simple descriptive statistics
and t-tests of differences between employed and unemployed. In the next step we use different
regression models, starting with simple OLS-regressions and ending with instrumental variables for
10
panel-data models. We use these different methods to check the robustness of the results. We estimate
two different equations, one with subjective well-being as the dependent variable and one with self-
esteem as the dependent variable. In the final models we combine these equations in an instrumental
variables model because we hypothesize that self-esteem is affected by unemployment and both affect
subjective well-being. Self-esteem affects subjective well-being endogenously, whereas both are
affected by unemployment. We thus have a system of structural equations of both subjective well-
being and self-esteem.
5 Results
Appendix B contains the means of the main variables for the employed and unemployed, for the
separate waves. In this appendix we see that unemployed score lower on both subjective well-being
and self-esteem in every wave. T-tests, corroborated by the correlations, show that these differences
are significant in all the four waves. These results suggest that self-esteem is affected by
unemployment and that subjective well-being is affected by unemployment and self-esteem. We also
see that employed are more emotional stable (less neurotic) and more conscientiousness than
unemployed. Furthermore, in most of the years employed and unemployed have the same level of
extraversion, agreeableness and openness to experience. This corroborates the general finding that the
big five are more stable than self-esteem. These descriptive analyses support our hypotheses about the
relations between self-esteem, unemployment and happiness, even with the relative low numbers of
unemployed.
Appendix C contains the correlations of the main variables of interest for the pooled data
3
.
Only significant correlations are displayed. We see that unemployed are less happy than employed,
that subjective well-being shows a strong correlation with neuroticism, self-esteem, satisfaction with
social contacts, satisfaction with how leisure time is spend, subjective health and subjective income.
Self-esteem shows somewhat lower correlations with these variables than subjective well-being.
Unemployment does not show strong correlations. The biggest one is with subjective income (-.23).
These correlations corroborate the t-tests on the differences between employed and unemployed.
Table 1 contains the results of regressions of subjective well-being on employment, self-
esteem, the big five and the control variables. We first present the results of OLS-regression on the
pooled data set. In the first model we estimate the raw effect of unemployment on subjective well-
being. We see that the unemployed almost have a one full point (-.95) lower level of subjective well-
being than the employed. In the second model we add self-esteem. We see that self-esteem positively
affects subjective well-being and that it mediates the effect of unemployment. The effect of
unemployment almost reduces with one third.
3
Correlation tables for the separate waves are available upon request from the corresponding author.
11
In the third model we add the big five personality traits. The effects of the big five are mostly
smaller than the effect of self-esteem, except for the effect of neuroticism. The big five do not alter the
effect of unemployment. This corroborates our idea that unemployment does affect, or is mediated by,
self-esteem but not the big five. The effect of self-esteem has decreased a little bit. In a next step we
add the control variables. These control variables show familiar effects. Of the control variables we
find significant and considerable effects of having a partner, satisfaction with social life, subjective
health, and subjective income. In this model we see that the effect of unemployment has been reduced
further, but still is negative, substantial and significant. The effect of self-esteem is hardly affected by
the control variables. It is positive and significant and has the same size, but opposite sign as that of
unemployment. Including fixed effects for the separate waves does not alter this picture, but we see
that over time the level of subjective well-being decreases.
Table 2 presents the results for the regression of self-esteem on unemployment and the big five
for the pooled data. We see that unemployment has a strong negative effect on self-esteem. This effect
is reduced by about halve when we add the big five to the model. Neuroticism has a big negative effect
on self-esteem and agreeableness shows to have the smallest effect on self-esteem. The control
variables have only a minor effect on the effect of unemployment on self-esteem. It remains quite
strong, negative and significant. Self-esteem increases with age and we find small positive effects of
having a partner, satisfaction with social life, how leisure time is spend, subjective health and
subjective income. As suggested in section three we find smaller effects of having a partner and
having a child at home on self-esteem than the effect of unemployment. This supports the idea that the
loss of self-esteem causes the scarring effect of unemployment. Adding fixed effects of the waves does
not alter the other estimates, although we see that self-esteem is a bit lower in waves four and six than
in the first wave. All in all we find the biggest effect from neuroticism. Neurotic individuals have the
lowest self-esteem.
Because self-esteem depends on unemployment, we have reasons to estimate a simultaneous
equation model with subjective well-being and self-esteem
4
as endogenous variables. In these models
we used extraversion and conscientiousness as instruments for self-esteem. The OLS regression shows
that they have a small or no effect on subjective well-being, but have strong significant effects on self-
esteem
5
. The results are presented as the fourth model in table 1. We see that the results of the
instrumental variables regression are similar to that of the OLS-regression. Unemployed show the
same effect, whereas the effect of self-esteem has increased somewhat. Of the other variables only
neuroticism and age change a little bit. Of the big five we see that neuroticism has the largest effect on
subjective well-being. Having a partner shows a big effect. Furthermore we have strong effects of
4
A formal test of endogeneity of self-esteem failed. The residuals of the OLS equation of self-esteem show no
effect (t=1.11) in the OLS equation of subjective well-being.
5
T-values are 15.35 and 16.43. A combined F-test (2, 7782) = 231.28 showing that they are useful instruments.
A test of overidentifying restrictions failed (p=.119).
12
having a partner, subjective income, subjective health, and satisfaction with social life. We also see
that women are happier than men. We find no wealth effects and we see a decrease over time in
subjective well-being, which may be due to the economic crises that started in 2008.
We further check the robustness of the results by using the panel structure of the data. We
estimate a fixed effects panel model
6
. This allows us to test more robustly for causality. In the fixed
effects models we also control for time-invariant unmeasured variables. They simply drop out of the
equation. In comparison to the OLS regressions we only miss the effect of gender, because this is a
time-invariant variable. All other variables show enough variance over time to be included in the fixed
effect model. So also the big five, who are thought to be stable over time show enough time variance
to be included in the fixed effect panel models. The results are presented in table 3.
The results of the fixed effect panel models are very similar to that of the pooled estimates.
We find a negative effect of unemployment that is partly explained by self-esteem, but not by the big
five and furthermore by the control variables. The raw effect of unemployment in the first model is
smaller than in the OLS-regression, but in the model including all the variables the effect has the same
size. Again we see that self-esteem has a positive effect on subjective well-being that is partly
explained by the big five. Of the big five neuroticism has the biggest effect on subjective well-being.
This effect is even stronger than that of unemployment. Furthermore we find small effects of
education, satisfaction with social life, satisfaction with leisure time spend and subjective income. We
do no longer find an effect of subjective health.
The fixed effect panel model of self-esteem, as presented in table 4, shows a large effect of
unemployment on self-esteem. This effect is smaller than in the OLS regression. The effect does not
change when we include the big five into the model. Of the big five the effect of neuroticism is the
biggest. Extraversion and conscientiousness have large effects, too. Agreeableness and openness to
experience also show significant effects. The control variables hardly have any effect on the other
estimates. Of the control variables we see that having a partner increases self-esteem. This effect has
the same size as unemployment. Having a child living at home does not affect self-esteem.
Satisfaction with social life increases self-esteem, as subjective income does.
Also these results justify the estimation of a simultaneous equation model of subjective well-
being and self-esteem. Again we use agreeableness and conscientiousness as instruments for self-
esteem. The result is shown in model four in table 3 that contains the fixed effect panel models. Again
the results are similar to what we have found in the regular fixed effect panel model. We see a
negative effect of unemployment and a positive effect of self-esteem on subjective well-being. The
effect of unemployment has the same size as in the regular fixed effect model. That of self-esteem has
become somewhat bigger. Of the big five neuroticism has the biggest effect on subjective well-being.
6
The Hausman test of fixed versus random effects, prefers the fixed effect model (chi2(17) = 295.13, p=.000).
The Breusch and Pagan Lagrangian multiplier test for random effects rejects the randomness of the data
(chibar2(01) = 597.01, p=.000)
13
Of the control variables we find significant effects of satisfaction with social life, satisfaction with
leisure time spend and subjective income. Again we find no wealth effect.
On bases of these analyses we can conclude that unemployment lowers both subjective well-
being and self-esteem. We also showed that self-esteem explains to a large extend the effect of
unemployment. The effect of unemployment is furthermore reduced once we include the control
variables, but remains significant, as well as the effect of self-esteem. We find these effects
irrespective of the specification of the models and are thus very robust. What we not yet did show are
the scarring effects of unemployment and how this is affected by self-esteem. This proved to be one
step beyond our possibilities. To test for the scarring effects of unemployment we estimated two series
of models. The first series of models contained a lagged effect of unemployment in the fixed effects
panel models. This formulation could show if past unemployment still has a negative effect on
subjective well-being and self-esteem. The second series of models contains the unemployment
frequency, i.e. the count of in how many spells a respondent had been unemployed.
The results of these models were that we are able to show a raw lagged effect of
unemployment on subjective well-being. This effect is about -.4 (not shown), just a little bit smaller
than the effect of unemployment. This effect remains significant once we add self-esteem and the big
five to the models. Once we include the control variables the effect of lagged unemployment, or the
frequency of earlier unemployment, becomes small and insignificant, see the last columns of tables 1
and 3. The only indication that we have is the size of the effect of lagged unemployment in the fixed
effect panel model. The effect is -.134, but the estimate is imprecise and therefore not significant, see
table 3. In all other models we do not find a persistent effect of unemployment on subjective well-
being. So we cannot replicate the scarring effect of unemployment for the Netherlands.
The absence of a scarring effect of unemployment in the Netherlands can have several reasons.
The first reason would be that in the Netherlands there is no such thing as a scarring effect of
unemployment. But this seems unlikely given the research results by Clark (et al., 2008), Clark and
Georgellis (2013), Clark (et al., 2001), Daly and Delaney (2013), Gangl (2004) and Knabe and Rätzel
(2011). It also seems unlikely because we find sizeable raw effects of lagged unemployment. The
reason that the effects disappear or become insignificant is that our data is rather thin. Although we
have 3790 respondents, the number of unemployed and or lagged unemployed is rather low.
Unemployment in the Netherlands was low in 2008 and despite the increase remained low in 2013.
Furthermore, the timeline of spells of (un)employment in our data is incomplete. We miss two in
between years because the big five were only asked to a small subset of respondents in these two
years. Furthermore we miss within one year mobility, i.e. the change from job to unemployment to a
job within one year. We only know what the respondent does at the time of interview, not the changes
that occurred since the last time of interviewing.
14
Also, if we control for the number of past unemployment spell, just counting the number of
spells, we see the same results. Current unemployment has a negative effect on subjective well-being,
but the number of spells become insignificant, and the effect rather small once we control for the
background variables. Removing self-esteem increases the effect a little bit, but not enough to make it
significant.
6 Summary and Conclusions
In this paper we tried to answer the question why long-term unemployment is a scarring life event, as
opposed to other major life events. Until now this question is mainly unanswered. We argue that long-
term unemployment causes a permanent loss of self-esteem and that this loss of self-esteem explains
the scarring effect of long-term unemployment on subjective well-being. The loss of self-esteem
explains the stylized facts about unemployment and happiness. It explains why unemployment mainly
causes unhappiness among the middle aged and much less among the young and old. It explains why
long-term unemployment has a scarring effect and a short-term of unemployment not. It explains why
becoming unemployed during an economic crisis is less damaging than becoming unemployed in an
economic upturn. It also explains why unemployed are scared to become unemployed again once they
have found a new job.
Of the personality characteristics that are recently used in the explanation of subjective well-
being and wages, self-esteem is the only one that can explain the effect of unemployment. This is so
because the big five: openness to experience, conscientiousness, extraversion, agreeableness and
neuroticism, and locus of control are mostly time-invariant, i.e. they hardly change over time. Self-
esteem changes over time because self-esteem is a product of social interaction based on reflected
appraisals, social comparison and self-attribution.
This self-esteem is damaged when one becomes unemployed, whereas the other personality
characteristics are not. Self-esteem is damaged by unemployment the more so when you have to blame
yourself, instead of someone else, of becoming unemployed. One is being appraised as unfit and
compared to others one ends up on the lowest sports of the social ladder. You really classify as a loser.
Self-esteem is much less affected by other major life events, and that is why long-term unemployment
has a scarring effect and other major life events not.
A unique Dutch data set, the LISS panel, allowed us to test this explanation. The panel
contains information about subjective well-being, unemployment and self-esteem. On basis of OLS
regressions and fixed effects panel models we found ample support for our claim that unemployment
causes a loss in self-esteem and thereby of subjective well-being. We found that unemployment affects
self-esteem and that both unemployment and self-esteem affect subjective well-being. We found the
effects in single equation models and in instrumental variables models with subjective well-being and
15
self-esteem as endogenous variables. The results prove to be robust. All specifications that we used
showed the same results.
We also found that having a partner and having children much less affect self-esteem than
unemployment. This further supports our idea that the loss in self-esteem explains why of all major
life events unemployment is scarring and the others, like marriage and having children, not.
Unfortunately we were not able to fully show the scarring effect of unemployment in our data.
We did find effects of lagged unemployment on subjective well-being but these became small or
insignificant once we include all control variables into the models. We think that we cannot replicate
the scarring effect of unemployment because of the relatively low numbers of unemployed in our data
set and the few waves that are available. In that sense our data are too thin. Next to the main strengths
of our data set, a panel with enough respondents and repeated measures of subjective well-being,
unemployment and personality characteristics, this is the main weakness of our data. Fortunately for
the Dutch, but unfortunately for us, the rate of unemployment is low and remained relatively low
despite of the economic crisis.
Our claim that the loss of self-esteem explains the scarring effect of long-term unemployment
will be supported if future research shows that employees who are fired, due to underperformance, are
unhappier than employees who are being laid-off, because they are redundant. Our claim will be
supported further if it shown that other major life events, like the loss of a beloved one, a divorce,
marriage and the birth of a child has no effect or a much smaller effect on self-esteem than
unemployment. We found that having a partner or having a child at home has a smaller effect on
subjective self-esteem than unemployment, but this needs further research.
Our results show that it is important for governments to actively combat unemployment, not
only by activating long-term unemployed, but also by creating employment or helping private
organisations to create jobs. Our results also show that governments should help long-term
unemployed to regain self-esteem. This helps the long-term unemployed to regain employment and to
improve subjective well-being.
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18
Table 1. Regression of subjective well-being on unemployment, self-esteem and lagged unemployment, all waves
swballm1
swballm2
swballm3
swballm4
ivallm1
ivallm2
b
se
b
se
b
se
b
se
b
se
b
se
unemployed
-0.945*
(0.07)
-0.699*
(0.06)
-0.675*
(0.06)
-0.222*
(0.05)
-0.212*
(0.05)
-0.154
(0.08)
self-esteem
0.552*
(0.01)
0.368*
(0.02)
0.248*
(0.01)
0.315*
(0.06)
0.290*
(0.09)
extrav
0.099*
(0.02)
0.033
(0.02)
agreee
0.167*
(0.03)
0.073*
(0.02)
0.074*
(0.02)
0.035
(0.03)
conscnt
0.081*
(0.02)
-0.003
(0.02)
neuroticism
-0.394*
(0.02)
-0.248*
(0.02)
-0.208*
(0.04)
-0.168*
(0.07)
openness
-0.234*
(0.03)
-0.081*
(0.02)
-0.093*
(0.03)
-0.077
(0.04)
woman
0.118*
(0.02)
0.116*
(0.02)
0.120*
(0.03)
partner
0.338*
(0.03)
0.334*
(0.03)
0.288*
(0.04)
age/10
0.032
(0.08)
0.013
(0.08)
-0.105
(0.12)
age^2/100
-0.014
(0.01)
-0.013
(0.01)
0.003
(0.01)
Child home
-0.003
(0.02)
-0.004
(0.02)
0.031
(0.03)
education
-0.051*
(0.01)
-0.050*
(0.01)
-0.033*
(0.01)
stf soc cntcs
0.130*
(0.01)
0.128*
(0.01)
0.146*
(0.01)
stf leisure spend
0.082*
(0.01)
0.080*
(0.01)
0.066*
(0.01)
subjective health
0.161*
(0.01)
0.158*
(0.02)
0.164*
(0.02)
subjective incom
0.178*
(0.01)
0.175*
(0.01)
0.204*
(0.01)
home owner
-0.028
(0.03)
-0.03
(0.03)
-0.072*
(0.04)
lagged unemployment
0.033
(0.09)
Constant
7.623*
(0.01)
6.672*
(0.02)
7.521*
(0.07)
4.339*
(0.19)
4.309*
(0.19)
4.232*
(0.29)
N
7800
7800
7800
7800
7800
3790
r2_a
0.03
0.22
0.27
0.45
0.45
0.47
F
207.57
1111.6
405.47
351.83
rmse
1.156
1.034
1.004
0.871
0.871
0.821
Source: LISS panel, our calculations
19
Table 2. Regression of self-esteem on unemployment and lagged unemployment, all waves
estallm1
estallm2
estallm3
estallm3g
b
se
b
se
b
se
b
se
unemployed
-0.447*
(0.05)
-0.231*
(0.04)
-0.136*
(0.04)
-0.104
(0.06)
extrav
0.237*
(0.01)
0.213*
(0.01)
0.185*
(0.02)
agreee
0.048*
(0.02)
0.019
(0.02)
0.019
(0.03)
conscnt
0.315*
(0.02)
0.275*
(0.02)
0.246*
(0.02)
neuroticism
-0.711*
(0.01)
-0.625*
(0.01)
-0.641*
(0.02)
openness
0.160*
(0.02)
0.209*
(0.02)
0.229*
(0.03)
woman
-0.014
(0.02)
0.001
(0.02)
partner
0.059*
(0.02)
0.082*
(0.03)
age/10
0.152*
(0.06)
0.071
(0.10)
age^2/100
-0.01
(0.01)
0
(0.01)
Child home
0.037*
(0.02)
0.026
(0.02)
education
-0.013*
(0.01)
-0.016
(0.01)
stf soc cntcs
0.055*
(0.01)
0.075*
(0.01)
stf leisure spend
0.025*
(0.01)
0.014
(0.01)
subjective health
0.028*
(0.01)
0.043*
(0.02)
subjective incom
0.032*
(0.01)
0.043*
(0.01)
home owner
0.025
(0.02)
0.007
(0.03)
lagged unemployment
0.041
(0.07)
Constant
1.723*
(0.01)
1.805*
(0.04)
0.346*
(0.15)
0.322
(0.24)
N
7800
7800
7800
3790
r2_a
0.01
0.44
0.47
0.49
F
70.24
1018.15
401.13
199.55
rmse
0.94
0.707
0.69
0.676
Source: LISS panel, our calculations
20
Table 3. Regression of subjective well-being on employment, self-esteem and lagged unemployment, fixed effects
fem1
fem2
fem3
fem4
feivm1
feivm2
b
se
b
se
b
se
b
se
b
se
b
se
unemployed
-0.439*
(0.08)
-0.357*
(0.08)
-0.356*
(0.08)
-0.242*
(0.08)
-0.232*
(0.08)
-0.299*
(0.12)
self-esteem
0.388*
(0.02)
0.275*
(0.02)
0.242*
(0.02)
0.333*
(0.14)
0.21
(0.20)
extrav
0.092*
(0.04)
0.079
(0.04)
agreee
-0.006
(0.05)
-0.012
(0.05)
-0.025
(0.05)
-0.07
(0.08)
conscnt
-0.061
(0.05)
-0.061
(0.05)
neuroticism
-0.421*
(0.04)
-0.427*
(0.04)
-0.385*
(0.08)
-0.359*
(0.10)
openness
0.034
(0.05)
0.008
(0.05)
-0.016
(0.06)
-0.009
(0.09)
partner
0.118
(0.08)
0.103
(0.08)
0.103
(0.12)
age/10
-0.487
(0.28)
-0.479
(0.28)
-1.062*
(0.43)
age^2/100
0.016
(0.03)
0.016
(0.03)
0.087
(0.05)
Child home
-0.11
(0.07)
-0.109
(0.07)
-0.022
(0.09)
education
0.087*
(0.04)
0.084
(0.04)
0.095
(0.07)
stf soc cntcs
0.044*
(0.01)
0.040*
(0.01)
0.034
(0.02)
stf leisure spend
0.026*
(0.01)
0.026*
(0.01)
0.021
(0.02)
subjective health
0.022
(0.02)
0.02
(0.02)
0.072*
(0.03)
subjective incom
0.084*
(0.01)
0.082*
(0.01)
0.076*
(0.02)
home owner
0.102
(0.08)
0.1
(0.08)
-0.039
(0.12)
lagged unemployment
-0.134
(0.14)
Constant
7.602*
(0.01)
6.937*
(0.04)
7.686*
(0.12)
8.017*
(0.65)
7.837*
(0.70)
9.183*
(1.05)
N
7800
7800
7800
7800
7800
3790
N_g
3784
3784
3784
3784
3784
2113
r2_o
0.03
0.22
0.24
0.28
0.29
0.28
F
29.12
174.99
73.6
39.59
rmse
0.73
0.703
0.69
0.679
21
sigma_u
1.103
0.985
0.953
0.935
0.925
0.928
sigma_e
0.73
0.703
0.69
0.679
0.681
0.61
rho
0.695
0.662
0.656
0.655
0.649
0.698
Source: LISS panel, our calculations
22
Table 4. Regression of self-esteem on unemployment, fixed effects
estfem1
estfem3
estfem4
estfem5
b
se
b
se
b
se
b
se
unemployed
-0.213*
(0.06)
-0.200*
(0.05)
-0.160*
(0.05)
-0.242*
(0.08)
extrav
0.237*
(0.03)
0.225*
(0.03)
0.164*
(0.04)
agreee
0.127*
(0.03)
0.121*
(0.03)
0.108*
(0.05)
conscnt
0.213*
(0.03)
0.207*
(0.03)
0.287*
(0.05)
neuroticism
-0.472*
(0.02)
-0.471*
(0.02)
-0.401*
(0.04)
openness
0.190*
(0.03)
0.171*
(0.03)
0.202*
(0.05)
partner
0.153*
(0.05)
0.162*
(0.08)
age/10
-0.229
(0.18)
-0.372
(0.30)
age^2/100
0.008
(0.02)
0.027
(0.03)
Child home
-0.006
(0.04)
-0.068
(0.07)
education
0.04
(0.03)
0.077
(0.05)
stf soc cntcs
0.041*
(0.01)
0.041*
(0.01)
stf leisure spend
0
(0.01)
-0.01
(0.01)
subjective health
0.006
(0.02)
0.018
(0.02)
subjective incom
0.022*
(0.01)
0.028*
(0.01)
home owner
-0.037
(0.05)
0.008
(0.08)
lagged unemployment
-0.171
(0.10)
Constant
1.713*
(0.01)
1.463*
(0.08)
1.642*
(0.43)
1.513*
(0.72)
N
7800
7800
7800
3790
N_g
3784
3784
3784
2113
r2_o
0.01
0.43
0.36
0.36
F
14.05
174.17
70.96
25.02
rmse
0.51
0.456
0.452
0.442
sigma_u
0.898
0.683
0.717
0.723
sigma_e
0.51
0.456
0.452
0.442
rho
0.756
0.692
0.716
0.728
Source: LISS panel, our calculations
23
Appendix A. Descriptive statistics of the variables
wave 1
wave 2
wave 4
wave 6
Variable
Mean
Std. Dev.
Mean
Std. Dev.
Mean
Std. Dev.
Mean
Std. Dev.
Min
Max
subjective well-
being
7.67
1.19
7.61
1.15
7.49
1.15
7.51
1.19
1
10
employed
1.03
0.16
1.04
0.19
1.05
0.22
1.06
0.24
1
2
agreee
1.49
0.49
1.46
0.49
1.45
0.50
1.41
0.52
-0.8
2.6
neuroticism
1.33
0.65
1.33
0.65
1.29
0.67
1.26
0.70
-0.2
3.8
extrav
0.31
0.64
0.29
0.63
0.26
0.64
0.25
0.68
-1.9
2
conscnt
1.36
0.50
1.34
0.51
1.33
0.52
1.37
0.51
-0.7
2.6
openness
1.75
0.49
1.72
0.48
1.70
0.49
1.70
0.51
-0.4
3.2
self-esteem
1.75
0.93
1.71
0.93
1.63
0.95
1.70
0.97
-2.4
3
age/10
4.24
1.02
4.30
1.02
4.42
1.06
4.43
1.06
2
6
age^2 / 100
18.98
8.55
19.51
8.59
20.62
9.02
20.72
9.01
4
36
education
3.82
1.39
3.84
1.37
3.92
1.36
3.94
1.35
1
6
gender
1.51
0.50
1.51
0.50
1.52
0.50
1.50
0.50
1
2
partner
0.80
0.40
0.78
0.41
0.75
0.43
0.75
0.43
0
1
child at home
0.55
0.50
0.55
0.50
0.52
0.50
0.54
0.50
0
1
stf social
contacts
7.19
1.66
7.18
1.55
7.08
1.52
7.21
1.54
0
10
stf leisure spend
6.93
1.68
6.89
1.64
6.79
1.60
6.84
1.66
0
10
subjective health
3.22
0.73
3.25
0.72
3.17
0.70
3.22
0.70
1
5
subjective
income
6.76
1.59
6.86
1.62
6.77
1.69
6.73
1.67
0
10
home ownership
0.79
0.41
0.77
0.42
0.77
0.42
0.78
0.42
0
1
N
2410
2111
1744
1535
Source: LISS panel, our calculations
24
Appendix B: differences between employed and unemployed
wave 1
wave 2
wave 4
wave 6
Mean
Std. Err.
Mean
Std. Err.
Mean
Std. Err.
Mean
Std. Err.
subjective
well-being
employed
7.71
0.02
7.64
0.02
7.52
0.03
7.57
0.03
unemployed
6.34
0.23
6.64
0.2
6.95
0.19
6.67
0.17
self-
esteem
employed
1.77
0.02
1.73
0.02
1.65
0.02
1.73
0.03
unemployed
1.18
0.15
1.34
0.13
1.35
0.12
1.22
0.11
extrav
employed
0.31
0.01
0.29
0.01
0.26
0.02
0.25
0.02
unemployed
0.14
0.08
0.2
0.07
0.28
0.07
0.28
0.07
agreee
employed
1.49
0.01
1.46
0.01
1.45
0.01
1.41
0.01
unemployed
1.53
0.05
1.6
0.06
1.43
0.05
1.5
0.05
conscnt
employed
1.36
0.01
1.34
0.01
1.34
0.01
1.38
0.01
unemployed
1.23
0.06
1.25
0.07
1.24
0.06
1.3
0.06
neuroticism
employed
1.32
0.01
1.33
0.01
1.28
0.02
1.24
0.02
unemployed
1.68
0.1
1.58
0.1
1.43
0.08
1.54
0.08
openness
employed
1.75
0.01
1.72
0.01
1.7
0.01
1.7
0.01
unemployed
1.78
0.06
1.76
0.05
1.72
0.05
1.7
0.06
N
employed
2348
2035
1656
1437
unemployed
62
76
88
98
Source: LISS panel, our calculations
25
Appendix C: Significant correlations (p=.05) for all waves (N=7800)
subjecti
ve well-
beingb
unempl
oyed
agreee
neuroti
cism
extrav
conscnt
openne
ss
self-
esteem
age/10
age^2 /
100
educati
on
gender
partner
Child
home
stf soc
contact
stf
leisure
spend
subjecti
ve
health
subjecti
ve
income
unempl
oyed
-0.16
agreee
0.13
neuroti
cism
-0.42
0.08
-0.05
extrav
0.21
0.32
-0.26
conscnt
0.18
-0.04
0.27
-0.20
0.08
openne
ss
0.07
0.26
-0.19
0.32
0.23
self-
esteem
0.46
-0.09
0.17
-0.60
0.34
0.31
0.28
age/10
0.04
0.05
-0.08
-0.05
0.08
-0.05
0.12
age^2 /
100
0.05
0.05
-0.08
-0.04
0.08
-0.05
0.11
0.99
educati
on
0.02
-0.03
0.04
-0.08
0.07
0.04
0.31
0.07
-0.15
-0.15
gender
0.03
0.34
0.17
0.10
-0.07
-0.07
-0.08
-0.07
partner
0.20
-0.07
-0.06
0.03
0.04
-0.08
0.09
0.03
0.03
-0.05
child at
home
0.05
-0.05
-0.03
-0.04
-0.04
0.03
-0.07
-0.10
0.03
0.32
stf soc
contact
s
0.45
-0.07
0.18
-0.29
0.25
0.13
0.07
0.33
0.06
0.07
stf
leisure
spend
0.41
-0.06
0.08
-0.28
0.14
0.13
0.03
0.29
0.08
0.09
0.06
-0.04
0.55
subjecti
ve
health
0.30
-0.09
-0.27
0.08
0.11
0.08
0.21
-0.13
-0.13
0.15
-0.04
0.05
0.04
0.19
0.20
subjecti
ve
0.44
-0.23
0.05
-0.22
0.07
0.14
0.05
0.25
0.07
0.08
0.17
0.14
0.25
0.29
0.23
26
income
home
owners
hip
0.16
-0.11
-0.02
-0.12
0.04
0.07
-0.03
0.12
0.06
0.05
0.09
-0.04
0.34
0.16
0.07
0.08
0.09
0.25
Source: LISS panel, our calculations
1
List of research reports
12001-HRM&OB: Veltrop, D.B., C.L.M. Hermes, T.J.B.M. Postma and J. de Haan, A Tale
of Two Factions: Exploring the Relationship between Factional Faultlines and Conflict
Management in Pension Fund Boards
12002-EEF: Angelini, V. and J.O. Mierau, Social and Economic Aspects of Childhood
Health: Evidence from Western-Europe
12003-Other: Valkenhoef, G.H.M. van, T. Tervonen, E.O. de Brock and H. Hillege, Clinical
trials information in drug development and regulation: existing systems and standards
12004-EEF: Toolsema, L.A. and M.A. Allers, Welfare financing: Grant allocation and
efficiency
12005-EEF: Boonman, T.M., J.P.A.M. Jacobs and G.H. Kuper, The Global Financial Crisis
and currency crises in Latin America
12006-EEF: Kuper, G.H. and E. Sterken, Participation and Performance at the London
2012 Olympics
12007-Other: Zhao, J., G.H.M. van Valkenhoef, E.O. de Brock and H. Hillege, ADDIS: an
automated way to do network meta-analysis
12008-GEM: Hoorn, A.A.J. van, Individualism and the cultural roots of management
practices
12009-EEF: Dungey, M., J.P.A.M. Jacobs, J. Tian and S. van Norden, On trend-cycle
decomposition and data revision
12010-EEF: Jong-A-Pin, R., J-E. Sturm and J. de Haan, Using real-time data to test for
political budget cycles
12011-EEF: Samarina, A., Monetary targeting and financial system characteristics: An
empirical analysis
12012-EEF: Alessie, R., V. Angelini and P. van Santen, Pension wealth and household
savings in Europe: Evidence from SHARELIFE
13001-EEF: Kuper, G.H. and M. Mulder, Cross-border infrastructure constraints,
regulatory measures and economic integration of the Dutch – German gas market
13002-EEF: Klein Goldewijk, G.M. and J.P.A.M. Jacobs, The relation between stature and
long bone length in the Roman Empire
13003-EEF: Mulder, M. and L. Schoonbeek, Decomposing changes in competition in the
Dutch electricity market through the Residual Supply Index
13004-EEF: Kuper, G.H. and M. Mulder, Cross-border constraints, institutional changes
and integration of the Dutch – German gas market
2
13005-EEF: Wiese, R., Do political or economic factors drive healthcare financing
privatisations? Empirical evidence from OECD countries
13006-EEF: Elhorst, J.P., P. Heijnen, A. Samarina and J.P.A.M. Jacobs, State transfers at
different moments in time: A spatial probit approach
13007-EEF: Mierau, J.O., The activity and lethality of militant groups: Ideology, capacity,
and environment
13008-EEF: Dijkstra, P.T., M.A. Haan and M. Mulder, The effect of industry structure and
yardstick design on strategic behavior with yardstick competition: an experimental study
13009-GEM: Hoorn, A.A.J. van, Values of financial services professionals and the global
financial crisis as a crisis of ethics
13010-EEF: Boonman, T.M., Sovereign defaults, business cycles and economic growth in
Latin America, 1870-2012
13011-EEF: He, X., J.P.A.M Jacobs, G.H. Kuper and J.E. Ligthart, On the impact of the
global financial crisis on the euro area
13012-GEM: Hoorn, A.A.J. van, Generational shifts in managerial values and the coming
of a global business culture
13013-EEF: Samarina, A. and J.E. Sturm, Factors leading to inflation targeting – The
impact of adoption
13014-EEF: Allers, M.A. and E. Merkus, Soft budget constraint but no moral hazard? The
Dutch local government bailout puzzle
13015-GEM: Hoorn, A.A.J. van, Trust and management: Explaining cross-national
differences in work autonomy
13016-EEF: Boonman, T.M., J.P.A.M. Jacobs and G.H. Kuper, Sovereign debt crises in
Latin America: A market pressure approach
13017-GEM: Oosterhaven, J., M.C. Bouwmeester and M. Nozaki, The impact of
production and infrastructure shocks: A non-linear input-output programming approach,
tested on an hypothetical economy
13018-EEF: Cavapozzi, D., W. Han and R. Miniaci, Alternative weighting structures for
multidimensional poverty assessment
14001-OPERA: Germs, R. and N.D. van Foreest, Optimal control of production-inventory
systems with constant and compound poisson demand
14002-EEF: Bao, T. and J. Duffy, Adaptive vs. eductive learning: Theory and evidence
14003-OPERA: Syntetos, A.A. and R.H. Teunter, On the calculation of safety stocks
14004-EEF: Bouwmeester, M.C., J. Oosterhaven and J.M. Rueda-Cantuche, Measuring
the EU value added embodied in EU foreign exports by consolidating 27 national supply
and use tables for 2000-2007
3
14005-OPERA: Prak, D.R.J., R.H. Teunter and J. Riezebos, Periodic review and
continuous ordering
14006-EEF: Reijnders, L.S.M., The college gender gap reversal: Insights from a life-cycle
perspective
14007-EEF: Reijnders, L.S.M., Child care subsidies with endogenous education and
fertility
14008-EEF: Otter, P.W., J.P.A.M. Jacobs and A.H.J. den Reijer, A criterion for the number
of factors in a data-rich environment
14009-EEF: Mierau, J.O. and E. Suari Andreu, Fiscal rules and government size in the
European Union
14010-EEF: Dijkstra, P.T., M.A. Haan and M. Mulder, Industry structure and collusion
with uniform yardstick competition: theory and experiments
14011-EEF: Huizingh, E. and M. Mulder, Effectiveness of regulatory interventions on firm
behavior: a randomized field experiment with e-commerce firms
14012-GEM: Bressand, A., Proving the old spell wrong: New African hydrocarbon
producers and the ‘resource curse’
14013-EEF: Dijkstra P.T., Price leadership and unequal market sharing: Collusion in
experimental markets
14014-EEF: Angelini, V., M. Bertoni, and L. Corazzini, Unpacking the determinants of life
satisfaction: A survey experiment
14015-EEF: Heijdra, B.J., J.O. Mierau, and T. Trimborn, Stimulating annuity markets
14016-GEM: Bezemer, D., M. Grydaki, and L. Zhang, Is financial development bad for
growth?
14017-EEF: De Cao, E. and C. Lutz, Sensitive survey questions: measuring attitudes
regarding female circumcision through a list experiment
14018-EEF: De Cao, E., The height production function from birth to maturity
14019-EEF: Allers, M.A. and J.B. Geertsema, The effects of local government
amalgamation on public spending and service levels. Evidence from 15 years of municipal
boundary reform
14020-EEF: Kuper, G.H. and J.H. Veurink, Central bank independence and political
pressure in the Greenspan era
14021-GEM: Samarina, A. and D. Bezemer, Do Capital Flows Change Domestic Credit
Allocation?
14022-EEF: Soetevent, A.R. and L. Zhou, Loss Modification Incentives for Insurers Under
ExpectedUtility and Loss Aversion
4
14023-EEF: Allers, M.A. and W. Vermeulen, Fiscal Equalization, Capitalization and the
Flypaper Effect.
14024-GEM: Hoorn, A.A.J. van, Trust, Workplace Organization, and Comparative
Economic Development.
14025-GEM: Bezemer, D., and L. Zhang, From Boom to Bust in de Credit Cycle: The Role
of Mortgage Credit.
14026-GEM: Zhang, L., and D. Bezemer, How the Credit Cycle Affects Growth: The Role
of Bank Balance Sheets.
14027-EEF: Bružikas, T., and A.R. Soetevent, Detailed Data and Changes in Market
Structure: The Move to Unmanned Gasoline Service Stations.
14028-EEF: Bouwmeester, M.C., and B. Scholtens, Cross-border Spillovers from
European Gas Infrastructure Investments.
14029-EEF: Lestano, and G.H. Kuper, Correlation Dynamics in East Asian Financial
Markets.
14030-GEM: Bezemer, D.J., and M. Grydaki, Nonfinancial Sectors Debt and the U.S.
Great Moderation.
14031-EEF: Hermes, N., and R. Lensink, Financial Liberalization and Capital Flight:
Evidence from the African Continent.
14032-OPERA: Blok, C. de, A. Seepma, I. Roukema, D.P. van Donk, B. Keulen, and R.
Otte, Digitalisering in Strafrechtketens: Ervaringen in Denemarken, Engeland, Oostenrijk
en Estland vanuit een Supply Chain Perspectief.
14033-OPERA: Olde Keizer, M.C.A., and R.H. Teunter, Opportunistic condition-based
maintenance and aperiodic inspections for a two-unit series system.
14034-EEF: Kuper, G.H., G. Sierksma, and F.C.R. Spieksma, Using Tennis Rankings to
Predict Performance in Upcoming Tournaments
15001-EEF: Bao, T., X. Tian, X. Yu, Dictator Game with Indivisibility of Money
15002-GEM: Chen, Q., E. Dietzenbacher, and B. Los, The Effects of Ageing and
Urbanization on China’s Future Population and Labor Force
15003-EEF: Allers, M., B. van Ommeren, and B. Geertsema, Does intermunicipal
cooperation create inefficiency? A comparison of interest rates paid by intermunicipal
organizations, amalgamated municipalities and not recently amalgamated municipalities
15004-EEF: Dijkstra, P.T., M.A. Haan, and M. Mulder, Design of Yardstick Competition
and Consumer Prices: Experimental Evidence
15005-EEF: Dijkstra, P.T., Price Leadership and Unequal Market Sharing: Collusion in
Experimental Markets
5
15006-EEF: Anufriev, M., T. Bao, A. Sutin, and J. Tuinstra, Fee Structure, Return Chasing
and Mutual Fund Choice: An Experiment
15007-EEF: Lamers, M., Depositor Discipline and Bank Failures in Local Markets During
the Financial Crisis
15008-EEF: Oosterhaven, J., On de Doubtful Usability of the Inoperability IO Model
15009-GEM: Zhang, L. and D. Bezemer, A Global House of Debt Effect? Mortgages and
Post-Crisis Recessions in Fifty Economies
15010-I&O: Hooghiemstra, R., N. Hermes, L. Oxelheim, and T. Randøy, The Impact of
Board Internationalization on Earnings Management
15011-EEF: Haan, M.A., and W.H. Siekman, Winning Back the Unfaithful while Exploiting
the Loyal: Retention Offers and Heterogeneous Switching Costs
15012-EEF: Haan, M.A., J.L. Moraga-González, and V. Petrikaite, Price and Match-Value
Advertising with Directed Consumer Search
15013-EEF: Wiese, R., and S. Eriksen, Do Healthcare Financing Privatisations Curb Total
Healthcare Expenditures? Evidence from OECD Countries
15014-EEF: Siekman, W.H., Directed Consumer Search
15015-GEM: Hoorn, A.A.J. van, Organizational Culture in the Financial Sector: Evidence
from a Cross-Industry Analysis of Employee Personal Values and Career Success
15016-EEF: Te Bao, and C. Hommes, When Speculators Meet Constructors: Positive and
Negative Feedback in Experimental Housing Markets
15017-EEF: Te Bao, and Xiaohua Yu, Memory and Discounting: Theory and Evidence
15018-EEF: Suari-Andreu, E., The Effect of House Price Changes on Household Saving
Behaviour: A Theoretical and Empirical Study of the Dutch Case
15019-EEF: Bijlsma, M., J. Boone, and G. Zwart, Community Rating in Health Insurance:
Trade-off between Coverage and Selection
15020-EEF: Mulder, M., and B. Scholtens, A Plant-level Analysis of the Spill-over Effects
of the German Energiewende
15021-GEM: Samarina, A., L. Zhang, and D. Bezemer, Mortgages and Credit Cycle
Divergence in Eurozone Economies
16001-GEM: Hoorn, A. van, How Are Migrant Employees Manages? An Integrated
Analysis
16002-EEF: Soetevent, A.R., Te Bao, A.L. Schippers, A Commercial Gift for Charity
16003-GEM: Bouwmeerster, M.C., and J. Oosterhaven, Economic Impacts of Natural Gas
Flow Disruptions
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16004-MARK: Holtrop, N., J.E. Wieringa, M.J. Gijsenberg, and P. Stern, Competitive
Reactions to Personal Selling: The Difference between Strategic and Tactical Actions
16005-EEF: Plantinga, A. and B. Scholtens, The Financial Impact of Divestment from
Fossil Fuels
16006-GEM: Hoorn, A. van, Trust and Signals in Workplace Organization: Evidence from
Job Autonomy Differentials between Immigrant Groups
16007-EEF: Willems, B. and G. Zwart, Regulatory Holidays and Optimal Network
Expansion
16008-GEF: Hoorn, A. van, Reliability and Validity of the Happiness Approach to
Measuring Preferences
16009-EEF: Hinloopen, J., and A.R. Soetevent, (Non-)Insurance Markets, Loss Size
Manipulation and Competition: Experimental Evidence
16010-EEF: Bekker, P.A., A Generalized Dynamic Arbitrage Free Yield Model
16011-EEF: Mierau, J.A., and M. Mink, A Descriptive Model of Banking and Aggregate
Demand
16012-EEF: Mulder, M. and B. Willems, Competition in Retail Electricity Markets: An
Assessment of Ten Year Dutch Experience
16013-GEM: Rozite, K., D.J. Bezemer, and J.P.A.M. Jacobs, Towards a Financial Cycle for
the US, 1873-2014
16014-EEF: Neuteleers, S., M. Mulder, and F. Hindriks, Assessing Fairness of Dynamic
Grid Tariffs
16015-EEF: Soetevent, A.R., and T. Bružikas, Risk and Loss Aversion, Price Uncertainty
and the Implications for Consumer Search
16016-HRM&OB: Meer, P.H. van der, and R. Wielers, Happiness, Unemployment and
Self-esteem
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... Prolonged unemployment negatively impacts the finances of affected individuals, worsening their physical and mental health [7]; in addition, it accentuates the relationship between social support and health [8] and can give rise to a permanent lack of self-esteem because, in addition to having feelings of failure and blame, unemployed people can feel excluded from society and believe that they will not be able to reintegrate into the workforce [9]. ...
... Moreover, social support decreases when a person is unemployed [4], negatively affecting mental health [3,5] and self-rated health in participants of the program. Unemployment also lowers self-esteem, which worsens health [6,9]. Among participants in "Employment in the Neighborhoods", self-esteem and social support were interrelated; having low self-esteem reduces a person's social support [9] and, in turn, low social support negatively affects self-esteem [5]. ...
... Unemployment also lowers self-esteem, which worsens health [6,9]. Among participants in "Employment in the Neighborhoods", self-esteem and social support were interrelated; having low self-esteem reduces a person's social support [9] and, in turn, low social support negatively affects self-esteem [5]. This indicates that negative psychosocial factors in unemployed people, and specifically in the study sample, are closely linked to health; consequently, some of the high prevalence of poor mental health in this population could be explained by the lack of social support and low self-esteem. ...
Article
Full-text available
Background Unemployment affects the physical and mental health of affected individuals, which can be explained by its direct effect on worsening finances due to the lack of income as well as by its negative psychosocial effects. “Employment in the Neighborhoods” return to work program was implemented in Barcelona specifically in the neighborhoods characterized with a greater economic deprivation and by high unemployment to improve personal and occupational abilities and skills of the participants to reintegrate them into the workforce. The aim of this study is to determine the association between the lack of economic resources and psychosocial factors with respect to mental health and self-rated health in unemployed persons participating in the program “Employment in the Neighborhoods”. Methods Cross-sectional study. Data collected from a self-administered questionnaire. Generalized linear models were constructed, adjusted by age and social class, to estimate prevalence ratios and analyze any possible association between economic resources, psychosocial factors and poor self-rated health and mental health. Results Nine hundred forty-eight persons of 2763 participants in the “Employment in the Neighborhoods” program completed the questionnaire. 46.9% were women. 72.5% of women and 61.9% of men were at risk of poor mental health and 25.5% of women and 21.1% of men reported poor self-rated health. Low self-esteem [women: PR 1.88 95%CI (1.24–2.84); men: PR 2.51 95%CI (1.57–4.02)] and medium social support [2.01 (1.30–3.09)], in men, and low social support [1.74 (1.13–2.68)] in women are associated with worsening of self-rated health. In men, low self-esteem [1.40 (1.19–1.64)] and delay in paying bills [1.38 (1.17–1.64)] were associated with the risk of poor mental health; in women were associated low self-esteem [1.27 (1.11–1.44)] and received a non-contributory allowance [1.37 (1.09–1.74)]. Conclusions Economic resources, self-esteem and social support are necessary for good general and mental health among unemployed persons. The high prevalence of poor mental health among persons participating in the active labor market program “Employment in the Neighborhoods” could be due to a substantial deficit in these factors.
... Being jobless can have a detrimental effect on an individual's self-esteem, especially when the person has decided to blame themselves for being jobless. Joblessness also influences a person's well-being (Meer/ Wielers, 2016). ...
Article
Full-text available
The purpose of this research is to revisit the meaning of development by seeking to answer the question; what is development? Also, we question whether the common and old wisdom of development objectives, economic growth (GDP), should continue to be the focus of studies. It concludes that development is when human aspects are become the objectives
... Loss of self-confidence is one of the effects of unemployment on the individual. Being employed gains more importance for an individual when he/she compares himself/herself with others ( Van der Meer et al., 2015). It is proposed that the happiness level of an unemployed individual shall be affected from the happiness levels of individuals in the reference group and that the number of individuals affected from unemployment will be less when unemployment becomes a social norm within the group (Clark, 2003;Lalive and Stutzer, 2004). ...
Article
Unemployment is an important economical concept indicating the economic development of countries. In addition, unemployment is studied quite frequently in a sociological context since it also affects the level of welfare, quality of life and psychological tendencies of individuals living in a country. In this study, unemployment was examined not as a macroeconomic variable but with micro data acquired from the household surveys carried out by the Turkish Statistical Institute (TUIK). Based on 2015 data, the demographic factors with impact on the employment status of people in Turkey were studied in addition to examining whether or not they are related with the happiness of individuals. Non-parametric tests were preferred since the analysed variables had a categorical structure. Log-linear models from among the advanced contingency tables analysis methods were used for examining the more than two way relationships of variables. It was determined as a result of the analyses carried out that the employment is related with happiness and gender and that there is a statistically significant difference between happiness and gender.
... Loss of self-confidence is one of the effects of unemployment on the individual. Being employed gains more importance for an individual when he/she compares himself/herself with others ( Van der Meer et al., 2015). It is proposed that the happiness level of an unemployed individual shall be affected from the happiness levels of individuals in the reference group and that the number of individuals affected from unemployment will be less when unemployment becomes a social norm within the group (Clark, 2003;Lalive and Stutzer, 2004). ...
... Further, moderate negative correlations were found between happiness and unemployment (r = -.515 and -.480 for men and women, respectively). This result is consistent with previous studies (Ohtake, 2012;van der Meer & Wielers, 2016;Winkelmann & Winkelmann, 1995). ...
Article
Full-text available
Happiness surveys have been conducted extensively by psychologists. More recently, economists have used happiness to assess welfare by combining the techniques typically used by economists with those more commonly used by psychologists. The aim of this study was to explore the happiness associations with per capita income and unemployment rate, using the single-item Self-Rating Scale of Happiness with samples of college students from six Arab countries, the UK, and USA (N = 3,023 total). The high-income countries (Qatar, Kuwait, UK, USA) obtained higher self-ratings of happiness than did the low-income countries (Egypt, Lebanon, Algeria). The correlations with per capita income (positive) and unemployment rate (negative) ranged from .48 to .67, but they were not statistically significant as a result of the small sample size. However, using descriptive statistics and t-tests, it was found that the high-income countries had significantly higher mean scores on happiness than the low-income countries. The correlations were significant with both Gallup World Poll (males and females) and the World Values Survey (males only), supporting the validity of the Self-Rating Scale of Happiness. It is recommended to replicate this study using a larger number of countries. © 2018 Ulster Institute for Social Research. All rights reserved.
... There is a broad consensus that work is crucial to the physical and psychological well-being of both nondisabled and disabled people, and that disabled people should remain in work or return to work as soon as possible (see Waddell & Burton, 2006 ). Studies conducted among nondisabled people show that unemployment increases the incidence of depression and anxiety disorders (Dooley, Catalano, & Wilson, 1994 ;Kim & von dem Knesebeck, 2016 ;Linn, Sandifer, & Stein, 1985 ) and alcohol use (Dooley, Catalano, & Hough, 1992 ;Popovici & French, 2013 ), and impacts self-esteem ( Van der Meer & Wielers, 2015 ). Moreover, unemployment generally decreases quality of life (Carlier et al., 2013 ;Van Dongen, 1996 ), although some people claim to have attained a better quality of life becoming unemployed (Axelsson, Andersson, Edén, & Ejlertsson, 2007 ). ...
Article
In spite of general positive attitudes of employers toward disabled people, there are persistently low employment rates for this demographic. One possible explanation is that there has been insufficient adjustment of needs and job preferences to suit disabled people and demands of employers. The objective of the present paper is to present results of empirical research on disabled people's and small and medium-sized enterprises' preferences, expectations, and needs in relation to employment in small and medium-sized enterprises (SMEs). We present a multistage study involving quantitative research conducted among 1041 disabled people and 150 SMEs, and qualitative research including case studies conducted in three SMEs that employ disabled people. On this basis, recommendations for the professional development of disabled people are proposed.
Article
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This paper tries to explain why unemployment has such a severe effect on the subjective well-being of people. It is already known that unemployed have among the lowest levels of subjective well-being of all people. This paper explains and tests why this is so. The explanation is based on the social production function theory. This theory states that ultimately people strive for physical well-being and social approval. Because unemployment affect both physical well-being and social approval its effect is so large. We elaborate this explanation to account for the differences between men and women. Because men and women have different ways of achieveing social approval unemployment is more detremental for men than for women. We further analyze differences between single men and women and married men and women to test the explanation that is put forward. Using the European Social Survey held in 2004 the hypotheses are tested. We do find that having a job is one of the main factors affecting subjective well-being, that this effect is bigger for men than for women and that women profit from the jobs of their partners whereas men do not.
Article
Full-text available
This article shows how stigma effects and discouragement counterbalance as sources of state dependence in unemployment throughout the business cycle.
Article
Past research has treated self-esteem either as a social force or as a social product. However, this research has not given adequate attention to the reciprocal effects of the self-concept and various social and personal factors. A panel of 1886 adolescent boys is used to explore the reciprocal relationships between self-esteem and three problems of youth: juvenile delinquency; poor school performance; and psychological depression. We find that low self-esteem fosters delinquency and that delinquency may enhance self-esteem. These reciprocal effects differ among socioeconomic status groups. The relationship between self-esteem and school performance is primarily attributable to the effect of school performance on self-esteem. Finally, the causal relationship between self-esteem and depression is bidirectional. Substantive, methodological, and policy implications of these findings are discussed.
Article
We look for evidence of adaptation in wellbeing to major life events using eighteen waves of British panel data. Adaptation to marriage, divorce, birth of child and widowhood appears to be rapid and complete; this is not so for unemployment. These findings are remarkably similar to those in previous work on German panel data. Equally, the time profiles with life satisfaction as the wellbeing measure are very close to those using a twelve-item scale of psychological functioning. As such, the phenomenon of adaptation may be a general one, rather than being found only in German data or using single-item wellbeing measures.
Article
Personality undoubtedly plays a role in determining educational attainment and labor market outcomes. We investigate the role of self-esteem in determining wages directly and indirectly via education. We use data from the 1979 wave of the National Longitudinal Study of Youth (NLSY79) to estimate a three equation simultaneous equation model that treats self-esteem, educational attainment, and real wages as endogenous. We find that, while self-esteem has a positive and significant impact on wages indirectly via education, it does not significantly affect wages directly once we control for locus of control. We find that the indirect effect of self-esteem comprises upwards of 80% of the total effect of self-esteem on wages after 1980. Additionally, we find that wages and education both affect self-esteem. We discuss gender differences in the relationships between wages, education, and self-esteem and conclude that females experience a higher rate of return on education than males, and self-esteem is a stronger determinant of educational attainment for males than females.
Article
While large literatures have shown that cognitive ability and schooling increases employment and wages, an emerging literature examines the importance of so-called "non-cognitive skills" in producing labor market outcomes. However, this smaller literature has not typically used causal methods in estimating the results. One source of heterogeneity that may play an important role in producing both personality and other non-cognitive skills and labor market outcomes is family background, including genetic endowments. This paper is the first to use sibling differences to estimate the effects of personality on employment and wages and is also able to control for many other sources of heterogeneity, including attractiveness, cognitive ability, schooling, occupation, and other factors. Overall, the findings suggest that personality measures are important determinants of labor market outcomes in adulthood and that the results vary considerably by demographic group. The findings also highlight the potential role of extraversion in leading to favorable labor market outcomes, which has not been documented in many other studies.
Article
The article examines whether, through supporting workers’ search for adequate reemployment, the decommodification achieved by welfare state transfers reduces the longer‐run scar effects of unemployment. Drawing on employment history data from the Survey of Income and Program Participation and the German Socio‐Economic Panel, the analysis establishes positive effects of unemployment benefits on workers’ post‐unemployment jobs: workers’ risks of incurring severe earnings losses, of experiencing occupational mobility, and of entering unstable job arrangements are considerably reduced in both the United States and West Germany. As workers face constrained choices in labor markets, however, this institutional protection of workers’ economic status comes at the economic cost of prolonged unemployment. Simulation analyses suggest that higher benefit coverage alone might account for up to 20% of the smaller cumulative disadvantages associated with unemployment for German workers.