Gender, Unemployment & Happiness – Why being unemployed is worse for men than for women

Master Thesis, MSc Human Resource Management University of Groningen, Faculty of Economics & Business

June 19, 2011

Florian Hemme

Student ID: 2052865 Antillenstraat 94-1 9714 JT Groningen

e-mail: f.hemmesd@gmail.com

Supervisor: P. H. van der Meer

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ABSTRACT

Being employed is one of the main contributing factors to happiness because it enables individuals to

satisfy innate human needs. However, as men and women differ in the ways they enact and pursue

their careers, their attitudes towards women in work and family and the extent to which they place

importance on being in paid work, they are also suggested to react differently to unemployment. In

addition to reproducing said relationship, I hypothesized that for women the relationship between

unemployment and well-being is moderated by their marital status, their partner’s employment status,

their values towards their own role in family and work interface, and the proportion of income

contribution. The results of this research indicate that unemployed women are in fact happier than

unemployed men. While the effect of marriage is ambiguous, women whose partner is employed are

happier than when both partners are unemployed. Contrary to my expectations, unemployed women

with more traditional attitudes are unhappier – and not happier – than those with more progressive

value systems. The proportion of the contribution to the household income does not moderate well-

being in the employment, although this could possibly be attributed to the fact that the present research

was not done longitudinally and can therefore not capture the amount of income contributed before

entering unemployment.

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TABLE OF CONTENTS

1. INTRODUCTION................................................................................................................ 4

2. THEORY............................................................................................................................... 6

2.1 About Happiness...........................................................................................................................6 2.2. What makes people happy?........................................................................................................7

2.2.1 Past findings ............................................................................................................................8 2.2.2 Income – Is it all relative? .......................................................................................................9 2.2.3 Is any job better than no job? ................................................................................................11

2.3 Happiness and the satisfaction of needs ...................................................................................12 2.4 Gender, Values & Attitudes towards Work.............................................................................14

3. DATA & METHOD........................................................................................................... 17

4. RESULTS............................................................................................................................ 19

4.1 Average well-being in unemployed men and women ..............................................................19 4.2 Marital Status .............................................................................................................................22 4.3 Respondent’s partner’s employment........................................................................................23 4.4 Attitudes towards women’s roles in family and work.............................................................24 4.5 Proportion of contribution to the household income ..............................................................26 4.6 Summary of Results ...................................................................................................................27

5. DISCUSSION ..................................................................................................................... 28

REFERENCES....................................................................................................................... 30

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1. INTRODUCTION

The question what makes people happy has been entertaining scholars for a long time.

Conceptions of happiness can be traced back to the sages of ancient Greek whose elaborations on

happiness evolved from the thousand-year old notion of eudaimonia (Miller, 2010). Despite this long

history and the fact that scholars in the field of psychology have occupied themselves with the

antecedents of individual happiness for several decades (Rogatko, 2010), only recently has there been

a significant increase in scientific interest in the field of happiness by economists. In the words of

(Oswald, 1997: 1816), “[responses to questions about subjective well-being] have been studied

intensively by psychologists, studied a little by sociologists, and ignored by economists.”

Among the numerous factors affecting happiness, it is being employed, which has a positive

influence on the judgments people form about how satisfied they are with their life. An individual’s

relative income (Clark, Frijters & Shields, 2008), and having a job at all (Korpi, T., 1997) are found to

be essential factors underlining the role of employment as one of the most important contributors to an

individual’s happiness. Therefore, the crucial effect of being employed on people’s happiness warrants

special attention and shall be the main focus of this research.

Said research focus corresponds with the proposition that people can only function as adequate

members of society – and be happy – when they can satisfy three deeply-rooted, fundamental needs:

the needs for competence, autonomy and relatedness (Ryan & Deci, 2000). If the satisfaction of any of

these needs is somehow stymied, the human being suffers severe negative consequences for mental

health and satisfaction (Howell, Chenot, Hill & Howell, 2011; Ryan & Deci, 2000). In a society where

employment is not only the central means to provide for yourself and your family but also source of

status and contact with others, employment contributes to the satisfaction of these – and other – needs,

and it is not surprising that research has revealed that those without employment are considerably

unhappier than those who enjoy having a steady, paying job (e.g. Clark & Oswald, 1994). Researchers

suggest that even having a mediocre job is more conducive to happiness than having no job at all

(Layard, 2009). But how does becoming unemployed lead to such a profound decline in happiness?

When looking at the detrimental consequences of unemployment one needs to account for the

possibility that the pain from non-pecuniary costs attributed to psychological and social factors (Di

Tella, MacCulloch & Oswald, 2003) might well exceed the strain placed upon the individual by loss

of income. Researchers distinguish between psychic and social costs (Frey & Stutzer, 2002b), costs

which seem to weigh differently on different individuals, and notably different on men and women.

Despite female advancement in a lot of areas, men and women still exhibit profound

differences in how they choose, enact, and further their careers. The traditional standard of the man as

the main, if not sole, breadwinner and all its implications for the importance of employment for men

and women is still very pervasive and helps maintain inequalities in what is expected from men and

women inside and outside the family (Forret, Sullivan & Mainiero, 2010).

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Mostly influenced and perpetuated by societal norms and expectations (Powell & Mainiero,

1992), the different educational and career-related choices mentioned above also play an important

role in how women and men will experience unemployment and how they respond to the loss of their

job. When women create their own social identities, they are more likely to do so by drawing from a

variety of sources and roles, such as being a mother, wife or friend, that go beyond the work sphere,

whereas men’s social identity centers primarily around their work (Cinamon & Rich, 2002).

Supporting the intuitively following, previous research has shown that men are affected more severely

by unemployment than women (Blanchflower & Oswald, 2004; Jahoda, 1982; Stokes & Cochran,

1984). However, findings are not unanimous and further research to solidify this relationship is

needed. The first purpose of the current research is therefore to see if past findings on the gender

differences in regard to the impact of unemployment on happiness can be replicated.

In addition to the still inconclusive picture of gender differences, the question remains

whether, if confirmed, these findings hold under all circumstances and what happens when specific

moderators are introduced. For example, researchers established that people with higher education

suffer more from unemployment than individuals who have received a lower education (Clark &

Oswald, 1994). So will a woman with high education still suffer less from unemployment than a man

with low education? Other authors have found that children and marriage significantly affect people’s

happiness and show that employed married women are the happiest, while employed single men seem

to be least happy (Forret, Sullivan & Mainiero, 2010).

In spite of the numerous previous research efforts, it has yet to be uncovered whether and how

intra-relational dynamics affect the relationship between unemployment and happiness and how

norms, values and role perceptions moderate the effects of unemployment on happiness.

Consequently, in addition to an attempt at the replication of previous research findings, the underlying

research question of this paper is to find possible moderating factors, which can explain the gender

differences in reaction to unemployment. Utilizing and building on the role of norms, values and

gender identities mentioned above, the differences in how men and women see themselves in regard to

their work will guide the subsequent analysis. Particular attention will be paid to the question of

whether someone’s partner is unemployed as well and the role of the primary earner and contributor to

the household income, since these might alter the perceptions of individuals regarding the gravity of

becoming unemployed.

This research paper is divided in five main sections. Following this introduction, I will present

relevant theory regarding the direction and purpose of this paper. After a short description in the third

section of the data and methods used, I will turn to the results of my research in section four. The fifth,

and final, section consists of a discussion of the results, its implications and possible limitations of this

research. The different strands of underlying theory will be united at the end of the theory section in

the formulation of specific hypotheses.

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2. THEORY

In the following section I introduce the essential theoretical framework and ideas the present

research is grounded on. The concept of happiness as the underlying principle of this thesis is

presented first, followed by a closer look on theories on need-satisfaction. Insights on gender

differences regarding norms, values and role identity formation conclude this theory section. Laying

this theoretical foundation will further the reader’s understanding of the topic and illustrate the

rationale behind the research questions presented above.

2.1 About Happiness

There exist plentiful definitions of happiness, which usually incorporate similar aspects but

differ in their interpretation and usage. One I found particularly endearing is the definition given by

one of the main proponents of happiness as a new and important topic for economic theorists and

national policy-makers, Richard Layard (2006): “So by happiness I mean feeling good – enjoying life

and wanting the feeling to be maintained. By unhappiness I mean feeling bad and wishing things were

different” (Layard, 2006: 12). By talking about the desire to maintain good feelings and alter bad ones,

Layard (2006) already sets the tone for one of his underlying principles of happiness: it is not so much

the fleeting emotion of the moment that counts but our average long-term happiness, which is

influenced by experiences, events, personality and circumstances. This approach shall be kept in mind,

as it is important for the elaborations below. To set Layard’s (2006) approach against other

conceptualizations of happiness, let us take a look at a different definition: “Happiness is an emotional

state, which is sensitive to sudden mood changes“ (Tsou & Liu, 2001). Clearly, this approach is much

more strict in its explicit focus on the transient character of emotions and feelings.

The contrasting approaches towards happiness play an important role in one of the main issues

surrounding the economics of happiness in theory and practice: the different and at times confusing

use of the terms happiness, subjective well-being (SWB) and (life) satisfaction. Subjective well-being

is traditionally conceptualized as an “umbrella term” (Dolan, Peasgood & White, 2008: 95), which

consists of partial measures such as stress, fulfillment, life satisfaction and personal happiness (Kim-

Prieto, Diener, Tamir, Scollon & Diener, 2005). This differentiation reflects the assumption that an

individual’s well-being needs to be defined in terms of both cognitive (satisfaction) and affective

(happiness) evaluations of their life (Davern, Cummins & Stokes, 2007; Diener, Larsen, Levine &

Emmons, 1985). The question whether one is satisfied with his or her life can only be answered

through an active, cognitive evaluation against a certain standard, e.g. one’s relative standing

compared to others. Being happy or not is seen as something innately ungraspable we feel deep within

ourselves without knowing why (Sirgy, 2001). Proponents of this approach see it as paramount to

assess each of the underlying constructs separately when trying to understand an individual’s well-

being (Diener, Suh, Lucas, Smith, 1999). Contradicting Layard’s (2006) conceptualization of

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happiness outlined above, the affective aspect – happiness – should also be treated differently due to

its more short-term oriented and volatile character, which can change drastically over time (Kim-

Prieto, Diener, Tamir, Scollon & Diener, 2005; Moons, Budts & De Geest, 2006). It should be noted,

that this traditional classification of SWB into strict cognitive and affective categories has been

challenged by some who call for a closer reexamination of the dichotomous character of SWB

(Crooker & Near, 1998; Haller & Hadler, 2006).

Instead of distinguishing between the different components subsumed under subjective well-

being as an all-encompassing concept, a large number of authors follow a “pragmatic approach”

(Dockery, 2003: 2) and use SWB, life satisfaction and happiness interchangeably (e.g. Dolan,

Peasgood, White, 2008; Graham, 2005). Some authors do so while explicitly acknowledging the

differences in the constructs (Frey & Stutzer, 2002b).

While cases can be made for all approaches outlined above, I will follow the example of Frey

& Stutzer (2002b) and mention the precise concept used whenever referring to other authors’

empirical research, while otherwise using the terms interchangeably. This, I feel, also accounts for

Layard’s (2006) more long-term understanding of happiness described above.

Finally, it is neither the purpose nor within the scope of this research to evaluate whether

subjective evaluations of one’s happiness are in fact suitable to effectively gage the construct it

supposedly measures. Traditionally, economic theory has modeled utility or well-being according to

how a rational, fully informed individual can satisfy his or her preferences by making a number of

choices with the intent to maximize utility. These choices are then reflected in the individual’s

observable actions in the market (e.g. Boyes & Melvin, 2007). I will simply take heed of the

contributions of previous research and treat subjective overall assessments of someone’s life as valid

indicators of an individual’s happiness (Dolan & White, 2007; Veenhoven, 2010). I agree with other

researchers on the premise that “ such accounts of well-being will add important information beyond

existing social and economic indicators, and as such prove highly useful for all kinds of policy-

makers“ (Diener, Kesebir & Lucas, 2008: 38). The emphasis here is on the supplementary character

of the subjective accounts. By no means should the acceptance of these personal evaluations be seen

as a call to abandon traditional utility theory, but rather as an opportunity to understand how they can

add to the discussion of happiness from a different perspective that directly captures an individual’s

well-being on a broader conceptual basis, including different aspects of utility (Cummins, Lau, Mellor

& Stokes, 2009; Frey & Stutzer, 2002b).

2.2. What makes people happy?

Past research has identified a plethora of factors that influence people’s happiness. Naturally,

in a research paper with limited space available, the accounts presented below can only depict a

fraction of the vast empirical research conducted on people’s happiness to date. For more extensive, in

depth reviews please consult Frey & Stutzer (2002a) and more recently Dolan, Peasgood & White

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(2008). In addition to these scholarly accounts, a more popular scientific approach to happiness

research can be found in (Layard 2006) who presents “the big seven factors affecting happiness”

(Layar, 2006: 63).

2.2.1 Past findings

Frequently identified contributors to happiness include personality traits such as: extraversion

(Parker, Martin & Marsh, 2008; Doyle & Youn, 2000) emotional intelligence (Furnham &

Christoforou, 2007) and self-efficacy (Strobel, Tumasjan & Spörrle, 2011). Happiness also appears to

be positively influenced by health (Bishop, Martin & Poon, 2006; Rogatko, 2010) and religion

(Ellison, Gay & Glass, 1989; Green & Bong Joon, 2004). Some researchers suggest that there exist a

U-shaped relationship between age and happiness (Gerdtham & Johannesson, 2001).

Furthermore, well-being seems to be positively related to democracy (Dorn, Fischer,

Kirchgässner & Sousa-Poza, 2007; Owen, Videras & Willemsen, 2008), governance quality (Ott,

2010; Sanfey & Teksoz, 2007; Whiteley, Clarke, Sanders, Stewart, 2010), forms of direct democracy

(Frey & Stutzer, 2000) and a country’s life expectancy and natality rate (Heukamp & Ariño, 2011).

One very extensively examined mechanism in happiness research is the relationship between

marital status and well-being. Several studies underline the positive impact marriage has on an

individual’s happiness and evidence for this relationship is found for a number of different countries,

at times even when individual differences in age and gender are controlled for (Peiró, 2006; Schoon,

Hansson, Salmela-Aro, 2005; Williams, Francis & Village, 2010). In fact, this positive effect can be

extended to all kinds of different forms of romantic relationships, with married couples being the

happiest, followed by cohabiting partners and steady-dating partners (Kamp Dush & Amato, 2005).

Singles display the lowest level of happiness (Soons & Liefbroer, 2008). Within married couples, the

quality of the marriage seems to play an additional role in determining well-being (Kamp Dush,

Taylor & Kroeger, 2008). Further research has found that friends and a reliable social network in

general also contribute significantly to someone’s happiness (Martikainen, 2009; Requena, 1995).

The overall effect of children on happiness still remains inconclusive. On the one hand, recent

research indicates that being a parent has a positive influence on people’s happiness (Van der Meer &

Wielers, 2011), and some authors explicitly refer to the beneficial “emotional rewards of parenthood”

(Hansen, Slagsvold & Moum, 2009: 353). Empirical results from the work-life-balance domain, on the

other hand, caution that children might in fact exacerbate conflicts between the family and work

domain, thereby contributing to greater distress and reduced well-being (McLanahan & Adams, 1989).

Also, there appears to be a gender difference in the extent to which someone values children as a

contribution to his or her happiness with men seemingly not experiencing the positive relationship

described above (Hansen, Slagsvold & Moum, 2009).

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2.2.2 Income – Is it all relative?

The relationship between income and happiness has received a lot of attention, with much of the

discussion revolving around the “Easterlin Paradox.” On the one hand, within a given country those

with higher income are happier than those who earn less (Fernández-Ballesteros, Zamarrón & Ruíz,

2001; Lever, Piñol & Uralde, 2005). On the other hand, income growth does not seem to spur an equal

rise in happiness over time or across countries (Easterlin, 2001, 2005a, 2005b). So even in countries,

which have experienced tremendous economic growth over the past decades, happiness has seemingly

stagnated or only risen by a tiny fraction. Empirical studies have corroborated these findings for

different country settings (Blanchflower & Oswald, 2004; Di Tella & MacCulloch, 2008; Easterlin,

McVey, Switek, Sawangfa & Zweig, 2010).

The quest to reconcile these perplexing findings has prompted researchers to come forth with

different explanations. One approach emphasizes the importance of relative rather than absolute

income (Bookwalter & Dalenberg, 2010; Clark, Frijters & Shields, 2008; Mentzakis & Moro, 2009).

Putting this approach into perspective to the “Easterlin Paradox”, it essentially means that people do

not become significantly happier when overall income rises because their friends, colleagues,

neighbor’s income rises as well, leaving the individual in the same position relative to others

surrounding him. Such comparisons to others, and also to oneself at a different time (Steffel &

Oppenheimer, 2008), are suggested to determine how strongly someone values his or her income.

Empirical research conducted in Germany showed that people’s happiness is e.g. determined by their

status relative to the neighborhood they live in (Dittmann & Goebel, 2010). However, an American

study cautioned that, while individuals do indeed compare themselves to others to determine their

happiness, they still seem to prefer to live in richer neighborhoods, indicating that individuals are

happier when they live among the poor, “as long as the poor reside at a distance” (Firebaugh &

Schroeder, 2009: 826).

In addition to the findings described above, a study on 274 married couples conducted over a

10-year period (North, Holahan, Moos & Cronkite, 2008) found that the impact of income on

happiness diminishes the higher the income level, which corresponds with findings by Layard, Nickell

& Mayraz (2008). According to Drakopoulos (2008) there indeed exists a threshold level of basic need

satisfaction, after which the impact of income growth ceases. Correspondingly, income seems to have

a higher effect on low-income than on high-income countries (Howell & Howell, 2008; Sarracino,

2008), with comparisons being mostly up-ward, meaning that poorer individuals relatively suffer more

from being poorer than their reference group while richer individuals do not become significantly

happier from being better off than the average (Ferrer-i-Carbonell, 2005).

A different explanation of the Easterlin Paradox is based on the premise that human beings

eventually adapt to changes in their environment, both positive and negative. Adaptations can be

defined as “defense mechanisms” (Graham, 2011: 106), which allow us to recover from almost

anything that can go wrong in our lives: health problems, divorce, unemployment, just to name a few.

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It also keeps our aspirations in line with our achievements: the more we have the more we want.

Ultimately, adaptation causes our innate level of satisfaction to return to its original state, or “set-

point.” Put differently, people’s happiness does not change over the long term. While this mechanism

has been confirmed e.g. for rises in income (Di Tella, Haisken-De New, & MacCulloch, 2010), the

original hedonic adaptation theory by Brickman & Campbell (1972) has been revised to allow for

some subtle yet very important alterations, the most notably being that there in fact exist certain

important life events that do alter our happiness levels for good (Diener, Lucas & Scollon, 2006).

In contrast to previous research specifically becoming or being divorced and unemployment

seem to have a lasting impact on people’s happiness, with hardly any adaptation taking place (Clark,

Diener, Georgellis & Lucas, 2008; Lucas, 2007). Also, people seem to differ in the way they react and

the extent to which they adapt to important changes in their lives (Lucas, 2007). To account for and

underline the importance of employment for individual well-being, I reserved an in-depth

consideration of unemployment for the next section.

To conclude this section on relative income, researchers’ findings and opinions are not

unanimous when it comes to the Easterlin Paradox and its possible explanations. For instance, neither

Hagerty & Veenhoven (2003) nor Diener, Diener & Diener (1995) could confirm that comparing

yourself to others has significant influence on your own well-being. Another study conducted on data

from East Germany before and after reunification indicates that growth in real income per household

was in fact a main contributor to significant increases in satisfaction (Frijters, Haisken-DeNew &

Shields, 2004), and Veenhoven & Hagerty (2006) point out that throughout the second half of the 20th

century in most countries growing wealth was accompanied by significant increases in quality of life.

More resistance to Easterlin and his followers also comes from a remarkably extensive

empirical research endeavor based on “all of the important large-scale surveys now available“

(Stevenson & Wolfers, 2008: 4). Indicating that it is in fact absolute, rather than relative income,

which plays a significant role in determining happiness, their findings “put to rest the earlier claim that

economic development does not raise subjective well-being and undermine the possible role played by

relative income comparisons“ (Stevenson & Wolfers, 2008: 3).

The Easterlin Paradox will likely continue to capture scholars’ interest and future research and

closer inspection of simple methodological differences in the studies might be necessary to possibly

reconcile the opposing views on relative/absolute income and adaptation theory. One possible

approach here is to acknowledge the importance of both absolute and relative income, with the

provision that relative income plays a relatively greater role. To conclude, here are the main points of

this section:

• Both on the individual as well as on the aggregate level, financial factors play an important role

in a person’s happiness

• People compare themselves and what they have to others, the so-called reference groups

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• While people adapt to a lot of changes in the environment, unemployment seems to alter our

happiness in the long run

2.2.3 Is any job better than no job?

The second factor research has identified as essential for well-being is employment. As with

income, interest in the relationship has increased dramatically and there exist a vast number of

empirical studies on the effect of (un)employment on satisfaction.

The benefits of being employed are considered to extend far beyond the earning of pecuniary

income (Winkelmann & Winkelmann, 1995), meaning that employment not only makes us happy

because we can use the salary to buy material things but also because being employed satisfies

something deeper within the individual. This explains why the detrimental effects of unemployment

on happiness usually hold even when income is controlled for (Latif, 2010). Employment seems to be

an essential achievement people evaluate themselves and their lives against: having a job is better than

being without work, no matter what else we could do with the time spent in the office (Knabe, Rätzel,

Schöb & Weimann, 2010). To take this one step further, any job seems to be better than no job at all,

regardless of the satisfaction with the job itself (Grün, Hauser & Rhein, 2010). Put differently, there

appears to be no situation in which being unemployed makes us happier than being in paid work. It

should be noted that this position is being challenged by other findings, e.g. for Australia (Dockery,

2003), where the satisfaction with the job spills over into general well-being and the quality of the job

seems to be of greater importance than simply being employed.

Correspondingly, being unemployed has been repeatedly linked to lower levels of well-being

(Cole, Daly & Mak, 2009; Di Tella, MacCulloch & Oswald, 2001; Mckee-Ryan, Song, Wanberg &

Kinicki, 2005; Welsch & Bonn, 2006), and higher levels of distress, self-doubt and dissatisfaction

(Paul & Moser, 2009; Stokes & Cochrane, 1984, Theodossiou, 1998). The negative influence of being

unemployed seems to increase with the length of unemployment (Brenner & Bartell, 1983).

Some studies add to this body of evidence while at the same time providing new insights. An

empirical study conducted in Ireland e.g. found that those who lose or give up a previously held job

are indeed unhappier than those employed but this relationship does not hold for recent graduates

looking to find their first employment (Brereton, Clinch, & Ferreira, 2008). Evidence from a German

study indicates that the relationship between unemployment and unhappiness only holds for those

individuals who are intending to work but not for the minority group of the voluntarily unemployed

(Chadi, 2010). A different study concluded that there might be an interplaying mechanism between

unemployment and psychological distress, where psychologically impaired people become more

unemployed and unemployment leads to a significant increase in psychological distress (Berth,

Förster, Stöbel-Richter, Balck & Brähler, 2006). Furthermore, Ouweneel (2002) found that the

difference in happiness between the employed and the unemployed is not any smaller for countries

where the unemployed find a very well-built and generous safety net of social security policies. On the

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other hand, an empirical study based on data from 94 countries points out that the negative impact of

unemployment on happiness seems to be greater in both richer countries and countries with higher

employment rates (Stanca, 2010). Finally, there appears to be a class effect, at least for the UK, with

those entering unemployment from the medium social class experiencing a greater negative change in

well-being than those from high or low social classes (Andersen, 2009).

Some authors found evidence that an individual not only suffers from being jobless himself but

that well-being is also negatively related to the general employment prevalent around us (Gandelmann

& Hernandez-Murillo, 2009; Hooghe & Vanhoutte, 2011). However, someone who is already

unemployed might find it easier to deal with his fate if others around him are in the same position

(Clark, 2003; Clark, Knabe & Rätzel, 2009).

In contrast to the findings presented above, Bökermann & Ilmakunnas (2006) found no

relationship between rising unemployment rates and average well-being in Finland. An unprecedented

increase in the national unemployment rate during the early 1990s was not accompanied by a

corresponding drop in subjective well-being. However, the authors concede that their results are at

least partly due to regression analysis restrictions, and once these are lifted unemployment does indeed

seem to have some negative effect. Also, according to a Danish study the effects of unemployment on

happiness are hardly as bad as other studies indicate, with the unemployed being actually happy about

more time to spend with friends and family (Andersen, 2002). These results however might be clouded

by the fact that Denmark is traditionally very generous towards the unemployed.

There are several points to remember regarding employment and happiness, with the last point

leading up to the next section on the satisfaction of needs:

• Being in paid work seems to be highly beneficial for an individual’s happiness

• Seemingly, a mediocre job is still better than no job at all

• There is more to work than simply earning a living

2.3 Happiness and the satisfaction of needs

The importance of employment for personal happiness corresponds with the proposition that

people can only function as adequate members of society – and be happy – when they are able to

satisfy three deeply-rooted, fundamental needs: the needs for competence, autonomy and relatedness

(Deci & Ryan, 2000). If the satisfaction of any of these needs is somehow muted or stymied, the

human being suffers severe negative consequences for mental health and satisfaction. Let us take a

closer look at the three needs introduced above as presented by Deci & Vansteenkiste (2004): the need

for competence describes the striving for a sense of control and affectivity in our dealings with the

environment. The need for relatedness symbolizes human desire for social connection with others.

Lastly, the need for autonomy encompasses our need to be able to control our own actions and make

our choices in accordance to our values and goals.

Now, consider how employment can play a vital part in the satisfaction of the aforementioned

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needs. Most people live in societies where employment is not only the central means for people to

provide for themselves and their family – the manifest need – but work also provides people with an

opportunity to satisfy five so called latent needs: time structure, social contact outside of the

immediate family, being part of a collective purpose, being engaged in meaningful activities, and

having social status (Jahoda, as cited in Creed & Watson, 2003). Work, therefore, is a much-needed

ingredient for our happiness, happiness we cannot achieve with leisure alone.

Correspondingly, previous research has found that not being able to satisfy these latent needs

will lead to mental distress and reduced well-being (Creed & Bartrum, 2008, Paul, Geithner & Moser,

2009), shedding more light on why the unemployed are unhappier than those who are in paid work. It

is important to note here, that different individuals might attach different weights to the different needs

and that not all latent needs seem to contribute equally to well-being. In fact, status has been identified

as the single most important latent need to be satisfied (Cree & Macintyre, 2001). In fact, women’s

status to a great extent is co-determined by the socioeconomic status of their husband (Nilson, 1976).

A male partner in paid work gives the wife a possibility to fall back on and seek employment to fulfill

non-economic desires such as approval, self-actualization or simply to socialize (Lindenberg, 1991).

Another essential finding is that, when financial strain is present, it seems to crowd out the

latent need deprivation (Creed & Klisch, 2005), indicating that although the latent needs play a

significant role in determining an individual’s happiness, the manifest worries of financial strain

cannot and should not be neglected (Ervasti & Venetoklis, 2010).

The ideas presented above fit well with the general proposition that employment serves to

satisfy both economic and psychosocial needs. If such needs are high, an unemployed individual will

have lower mental well-being than an employed person (Nordenmark & Strandh, 1999) because they

do not have the means to satisfy their needs. This also corresponds with Lindenbergs’s (1991)

proposition that fundamental human goals can be divided into physical well-being and social approval,

with social approval consisting of status, behavioral confirmation and affect. If these goals, especially

status and behavioral role confirmation cannot be satisfied through the private sphere, then it is

employment through which people seek to balance out their goal attainment.

Again, let us sum up the main ideas and important points to remember:

• Unemployment seems to prevent us from satisfying financial and psychosocial needs

• Different people most likely have different preferences regarding their latent needs

• Despite the importance of the latent needs, financial strain has to be accounted for

Next, I show how different norms and values towards family and work explain gender differences in

how employment can satisfy the human needs.

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2.4 Gender, Values & Attitudes towards Work

Despite female advancement in a lot of areas, and stronger male involvement in the family

domain, men and women still exhibit profound differences in how they choose, enact and further their

careers. These differences are mostly influenced and perpetuated by societal norms and expectations

(McKeen & Bu, 2005; Powell & Mainiero, 1992). Beliefs about gender roles are still somewhat biased

towards men as the main, if not sole, breadwinner, and people still “cling to traditional gender roles in

the areas of work, family, and politics” (Hildenbrand, 2008: 78). This helps maintain inequalities in

what is expected from men and women inside and outside the family (Forret, Sullivan & Mainiero,

2010). For instance, a common belief is that “women have a greater responsibility than men to

subordinate themselves to the needs of children and family” (Badgett & Folbre, 1999: 323).

Correspondingly, men who are not pursuing paid work but spend their time e.g. as stay-at-home

fathers are often stigmatized and met with disapproval (Rochlen, McKelley & Whittaker, 2010).

One has to realize though, that the endorsement of such beliefs cannot be attributed uniquely to

malicious men, who do not want to share their work domains with women. In fact, women on average

seem to have a more positive attitude than men toward housework duties such as cleaning, cooking,

and child-care (Poortman & Van Der Lippe, 2009), and overall place higher importance on family

(Cinamon & Rich, 2002). A study conducted on a sample of unmarried Israeli students (Cinamon,

2010) showed that of the women, about 30% were family oriented, while the ratio for the men was

only about 19%. Consequently, with women actually enjoying family life and domestic duties more

than men and also feeling a greater degree of responsibility towards them, the domestic domain is

apparently still perceived as women’s work – by men and women.

Accordingly, when women create their own social identities, they are more likely to do so by

drawing from a variety of sources and roles, such as being a mother, wife or friend, that go beyond the

work sphere (Graham, Sorell & Montgomery, 2004), whereas men’s social identity centers primarily

around their work (Cinamon & Rich, 2002). Underlining this mechanism, a study conducted in

Australia (Booth & Van Ours, 2009) has found that partnered women’s life satisfaction decreases

when working full-time themselves but increases when their partner is working full-time. Male

partners’ life satisfaction on the other hand is unaffected by their partners’ working time but

significantly rises if they themselves are working full-time, indicating that full-time work for the male

partner is a main contributor to both partners’ life happiness. Also, men do not seem to have a

preference over their partners’ working time, but women are happiest with part-time work, which

allows them to fulfill family commitments and other identity enhancing activities. For instance,

working part-time promotes volunteering for women (Taniguchi, 2006). The results of the same study

also suggest that men’s volunteering efforts are not influenced by their working time. However,

unemployed men volunteer less, regardless of the fact that they have more time on their hands, another

piece of evidence for the stigma attached to men heavily devoting themselves to anything else than

paid labor.

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The different norms, expectations and attitudes towards work, and the resulting educational and

career-related choices also play an important role in how women and men will experience

unemployment and how they respond to the loss of their job (Stokes & Cochrane, 1984). Men are

reportedly affected more severely by unemployment than women (Blanchflower & Oswald, 2004;

Hultman, Hemlin & Hörnquist, 2006; Jahoda, 1982) and married men with responsibilities as provider

for the family report greater mental distress from becoming unemployed than married women, for

whom marriage seems to act as a buffer (Artazcoz, Benach, Borrell, & Cortès, 2004). According to an

Israeli study, men are also more likely than women to think that being unemployed has a stigma

attached to it (Kulik, 2000). Ultimately, Chung (2009) suggests that unemployment increases the

gender differences in suicide rates of married people because men suffer from a greater loss of human

capital than women when losing their job. Interestingly, Ollikainen (2006) found that having a family

negatively influenced the female position in the labor market in Finland. For men, this relationship

was either insignificant or slightly positive, suggesting that having a family motivates women to stay

at home while men seek employment. At the same time, past unemployment seems to be particularly

damaging for men, again, because they are confronted with a greater stigma associated with

unemployment.

However, findings are not unanimous and further research to solidify this relationship is needed.

Drawing from the previous research on happiness, unemployment, and gender differences in values

and attitudes regarding work, I seek to contribute to the existing research by answering the follwing

five hypotheses:

Hypothesis 1: Unemployed women will generally report greater happiness than unemployed

men.

Hypothesis 2: Single unemployed women will react more strongly to unemployment than their

married counterparts and be more similar to men in their reaction because

marital status moderates the relationship between unemployment and well-

being.

Hypothesis: 3: Having a partner who is not in paid work will moderate the relationship between

unemployment and well-being for women. Women who are the sole earner in

the relationship will be similar to men in their reaction to unemployment.

Hypothesis 4: Attitudes towards women’s role in family and employment will moderate the

relationship between unemployment and well-being. Women with more

progressive attitudes will be similar to men in their reaction to unemployment

than women with traditional value patterns.

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Hypothesis 5: The proportion of household income contribution will moderate the relationship

between unemployment well-being. The more women contribute to the household

income the more will they be similar to men in their reaction to unemployment.

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3. DATA & METHOD

To test the hypotheses, empirical data was obtained from the second edition of The European

Social Survey (ESS) round two dataset (ESS round 2, 2004). This repeat cross-sectional survey charts

and explains the interaction between Europe's changing institutions and the attitudes, beliefs and

behavior patterns of its populations. The data can be obtained freely via internet-download from the

Norwegian Social Science Data Services’ website (http://ess.nsd.uib.no/ess/round2/download.html).

It includes data from 26 countries and contains a number of questions that are directly

pertaining to the purpose of this research. The well-being of respondents is measured with two

questions: (B24) “All things considered, how satisfied are you with your life as a whole nowadays?“

and (C1) “Taking all things together, how happy would you say you are?“ The answers are measured

on an eleven-point scale ranging from 00 (lowest) to 10 (highest), with the option to answer “I don’t

know” available to the respondents as well. Data was restricted to those respondents who answered

both questions and the two measures were combined into a single, averaged category called “well-

being” to account for the high correlation (.70) and to simplify subsequent analysis. “Well-being” was

the dependent variable of this research.

To assess respondents’ employment status I made use of question (F8d), which asks for the

main activity over the past seven days. I distinguished between those in paid work and those who are

unemployed (no distinction was made whether the unemployed were looking for a job or not). People

in education or community/military service were excluded from the analyses, as were the permanently

sick and disabled, the retired and those who spend their time primarily on housework or dependent

care. Data analysis was also confined to those respondents between 25 and 65 years old. The first step

of the analysis sought to reproduce past findings on the difference in happiness between unemployed

men and women. At this point the sample consisted of 23058 people. To account for the possible

differences in country variances regarding well-being, I used multi-level modeling.

For the second part of the analysis a number of moderators were introduced. First, in accordance

with the previous elaborations on the “safety net” of a partner for women and the fact that value

formation takes place within the family and often in regard to one’s significant other, marital status

was the first moderator for the relationship between unemployment and happiness. Second, I

introduced the moderating effect of having a partner who is in paid work. This should reflect the

economic need of having to work for the respondents themselves.

In the original survey, the values and attitudes in regard to family and work were assessed by

the following group of questions: (G6) “A woman should be prepared to cut down on her paid work

for the sake of her family”, (G7) “Men should take as much responsibility as women for the home and

children“, (G8) ”When jobs are scarce, men should have more right to a job than women“, (G9)

“When there are children in the home, parents should stay together even if they don’t get along”, and

(G10) “A person’s family ought to be his or her main priority in life.” Recoding of question (G7) and

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a subsequent reliability analysis showed that Cronbach’s Alpha was highest (.615) for questions (G6),

(G8) and (G9), encouraging me to combine these three questions into a single measure I called

“Values” and use this measure as my third moderating variable. In order to have higher scores

represent a more progressive stance towards women and family, “Values” was reverse coded.

Furthermore, the analysis of how “Values” acts as a moderator was restricted to respondents in a

relationship because I expect different attitudes and values to be more salient and influential in

partnerships. Finally, the contribution an individual made to the household income was constructed

according to question (F32a) “Around how large a proportion of the household income do you provide

yourself?” Answers were to be chosen from a seven-point scale ranging from 01 (“None”) to 07

(“All”). Original concerns that this scale would only constitute a different representation of whether

the survey subject was employed or not could be rebutted with a preliminary correlation analysis,

which revealed that the correlation coefficient between employment status and income contribution

was relatively small (.18). Therefore, the degree of income contribution could be included as the

fourth and final moderator.

Finally, the effects of health (C7), the respondent’s education (F6), the presence of children

under 12 years old (G42) and the respondent’s subjective income (F33) were being controlled for in

all analyses conducted. Covariate scores were centered using the grand mean and analyses in this

research were conducted for men and women separately.

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4. RESULTS

In the following section I present the results of my analyses, following the order of my

hypotheses. I will first touch upon the difference in general well-being between men and women,

followed by the results for each of the moderator variables used. As a quick reminder, the moderators

examined in this research were marital status, employment status of the partner, attitude towards

women’s role in family and work and, finally, the proportion of income contribution.

4.1 Average well-being in unemployed men and women

I hypothesized that, on average, women suffer less from unemployment than men. Before I

answer this question I would like to present descriptive data for a better understanding. While TABLE

4.1 below displays the average well-being of the unemployed, I chose to omit a full complementary

table for the employed to facilitate reading, however, total numbers are presented in TABLE 4.3.

TABLE 4.1

Average Well-Being of the Unemployed in 25* European Countries

Men Women Total Country N Mean SD N Mean SD N Mean SD Austria 56 6.30 2.09 21 5.74 2.21 77 6.15 2.13 Belgium 36 5.96 2.26 45 7.17 1.73 81 6.63 2.06 Czech Republic 44 5.50 2.38 72 5.31 2.49 116 5.38 2.44 Denmark 33 7.98 1.30 31 7.85 1.78 64 7.92 1.54 Estonia 52 4.31 2.17 31 5.02 2.29 83 4.57 2.23 Finland 45 6.52 1.89 51 7.38 2.06 96 6.98 2.02 France 30 4.60 2.36 55 5.41 2.10 85 5.12 2.22 Germany 116 6.25 2.18 96 5.36 2.00 212 5.20 2.10 Greece 53 5.48 2.51 73 5.84 2.05 126 5.69 2.25 Hungary 34 3.78 2.40 19 3.97 2.45 53 3.85 2.40 Ireland 26 6.42 2.19 21 6.55 2.44 47 6.48 2.28 Italy 30 5.85 2.47 52 5.47 2.42 82 5.61 2.43 Luxemburg 16 4.69 2.12 9 6.61 1.56 25 5.38 2.12 Netherlands 35 6.71 1.68 29 6.53 1.89 64 6.63 1.77 Norway 27 6.17 2.05 21 6.83 1.94 48 6.46 2.01 Poland 52 5.01 2.84 53 5.58 2.54 105 5.30 2.70 Portugal 36 5.58 1.89 73 5.69 1.88 109 5.66 1.87 Slovakia 54 4.53 2.25 59 4.86 2.42 113 4.70 2.33 Slovenia 25 5.84 1.66 27 6.26 2.59 52 6.06 2.18 Spain 28 6.54 1.97 32 6.28 2.14 60 6.40 2.05 Sweden 27 6.09 2.49 42 7.06 1.89 69 6.68 2.18 Switzerland 21 6.43 2.56 17 6.65 2.26 38 6.53 2.40 Turkey 94 5.44 2.72 30 5.73 2.36 124 5.51 2.63 Ukraine 45 3.88 2.44 50 3.73 1.86 95 3.80 2.15 United Kingdom 34 6.25 2.14 30 6.52 2.21 64 6.38 2.16 Total 1049 5.52 2.42 1039 5.83 2.33 2088 5.67 2.38 N=Number of Respondents; SD=Standard Deviation * Iceland was removed from the analysis because the number of respondents (N=7) was too low

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Overall, unemployed women have a higher average in happiness than unemployed men.

However, the difference is rather small, with their means being 5.83 and 5.52 respectively. TABLE

4.1 also shows that the countries examined are not homogenous in regard to the differences in well-

being. While the data of 17 countries indicates that unemployed women are better of than unemployed

men, for the remaining eight countries, with results shown in italics, it is the other way around. As a

final remark, note that countries also differ in the extent to which unemployed women are happier than

men. In the case of Portugal, for example, the difference in average well-being is only 0.11, while

unemployed women in Luxemburg are 1.92 points higher on average well-being than men. To test

whether the difference in average well-being between men and women is indeed significant I

conducted an independent t-test. TABLE 4.2 shows that the difference is significant; therefore, on

average, unemployed women are indeed significantly happier than unemployed men.

TABLE 4.2

Independent t-test for significant Gender Differences in average Well-Being in the Unemployed

t-test for equality measures 95% Confidence

Interval of the Difference

t df Sig.

(2-tailed) Mean

Difference Std. Error Difference Lower Upper

Anxiety - 3.05 2084.12 .002 - .32 .10 - .52 - .11 * Levene’s Test for Equality of Variances was insignificant

TABLE 4.3 below shows the average well-being of employed and unemployed men and

women. In accordance with past research findings the unemployed are lower on average well-being

than the employed. Note also that the standard deviations for the unemployed are considerably higher,

indicating that the effects of not having a paid job vary more across respondents. Again, an

independent t-test showed that the difference is significant (p < .001). Note that the t-test also revealed

that gender differences in the well-being of the employed are not significant (p = .065).

TABLE 4.3

Average Well-Being of the Employed and the Unemployed

Men Women Total Empl. Status N Mean SD N Mean SD N Mean SD Employed 11285 7.19 1.79 9678 7.24 1.83 20963 7.21 1.80 Unemployed 1049 5.52 2.42 1039 5.83 2.33 2088 5.67 2.38 N=Number of Respondents; SD=Standard Deviation

While the descriptive statistics above convey an important first impression, further analysis is

needed to unveil the gender differences in the mechanisms behind the relationship between

unemployment and happiness. Therefore, I turned to multi-level modeling (MLM) with a random

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intercept for the respondents’ country, controlling for health, education, children under 12 years old

and subjective income. The main results are presented in TABLE 4.5, the covariance parameters of the

empty model can be found in TABLE 4.4

TABLE 4.4

MLM with a random Intercept: Covariance Parameters

95% Confidence Interval Parameter Estimate Std. Error Wald Z Lower Bound Upper Bound

Residual 3.04* .028 106.57 2.98 3.09 Intercept Variance .70** .20 3.45 .40 1.24 (Subject = Country) N 22740 Restricted log likelihood 89919.18 Dependent Variable: Well-Being * p < .001; ** p < .005

TABLE 4.4 shows that the country intercepts differ significantly, with a variance of .70 (p <

.005). With these general results in mind, I created sub-groups according to gender and employment

status and compared the model with this interaction affect of unemployment status and gender to the

baseline model without gender to see whether women suffer significantly less than men from

unemployment. Here I conducted the analyses multiple times for varying reference categories to

develop as clear an impression as possible. TABLE 4.5 shows the estimates of the fixed effects of the

analysis conducted with employed women as a reference group while TABLE 4.6 shows the

equivalent results for the reference category of unemployed men.

TABLE 4.5

MLM with a random Intercept & Dummy Groups “Gender & Employment”

Parameter Estimate Std. Error Intercept 6.62* .11 Employed Men .43* .06 Employed Women .54* .06 Unemployed Men - .23** .07 Unemployed Women Reference Category N 21014 Restricted log likelihood 78368.31 dfChange 2 χ2

Change 33.00 Dependent Variable: Well-Being * p < .001; ** p < .05; *** not significant Controlled for: health, education, children under 12 years old, subjective income

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TABLE 4.6

MLM with a random Intercept & Dummy Groups “Gender & Employment”

Parameter Estimate Std. Error Intercept 6.38* .11 Employed Men .66* .05 Employed Women .77* .05 Unemployed Women .23** .07 Unemployed Men Reference Category N 21014 Restricted log likelihood 78368.31 dfChange 2 χ2

Change 33.00 Dependent Variable: Well-Being * p < .001; ** p < .05; *** not significant Controlled for: health, education, children under 12 years old, subjective income

First, the interaction model provides a significantly better fit for the data than the model

without the interaction (dfChange = 2; χ2Change = 33.00). Second, both for men and women,

unemployment significantly affects well-being (p < .001). However, the effect of changing from being

employed to being unemployed is greater for men (- .66) than for women (- .54). In light of these

results and in combination with the descriptive statistics presented above, hypothesis one is supported:

women suffer less from unemployment than men.

4.2 Marital Status

According to my second hypothesis married unemployed women are not only significantly

happier than their single counterparts but single unemployed women are also more similar to men in

their reaction to unemployment. Again, splitting the respondents in groups, now according to gender,

employment status and marital status, helped arrive at an answer. I ran the analysis both for a model

with the interaction of gender, unemployment and marital status, using eight sub-groups, and without

the interaction with marital status, using four sub-groups. The results, presented in TABLES 4.7 and

4.8 below, show that the interaction model is a better fit than the baseline model without the

interaction with marital status (dfChange = 4; χ2Change = 315.49). Furthermore, the interaction model

shows that single unemployed women are significantly unhappier than married unemployed women

(- .48). However, the same mechanism holds for men, and single unemployed men are affected worse

than unemployed single women (-.62). Therefore, I can only find partial support for my second

hypothesis: although marital status moderates the effect of unemployment on well-being and single

women are affected worse by unemployment than married women, single women are still happier than

singe men.

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TABLE 4.7

MLM with Dummy Groups “Marital Status, Employment & Gender”

Parameter N Mean Std. Dev. Estimate Std. Error Intercept 6.85* .13 Single Employed Women 3462 6.99 1.91 .06*** .08 Single Employed Men 3471 7.04 1.83 - .08*** .08 Single Unemployed Women 459 5.69 2.34 - .48* .10 Single Unemployed Men 521 5.43 2.35 - .78* .10 Married Employed Women 5294 7.41 1.75 .45* .08 Married Employed Men 6748 7.30 1.74 .33* .08 Married Unemployed Men 449 5.69 2.48 - .16*** .10 Married Unemployed Women 454 6.13 2.28 Reference Category N 20936 Restricted log likelihood 77738.28 dfChange 4 χ2

Change 315.49 Dependent Variable: Well-Being * p < .001; ** p < .05; *** not significant Controlled for: health, education, children under 12 years old, subjective income

TABLE 4.8

MLM with Dummy Groups “Marital Status, Employment & Gender”

Parameter N Mean Std. Dev. Estimate Std. Error Intercept 6.70* .13 Single Employed Women 3462 6.99 1.91 .22** .08 Single Employed Men 3471 7.04 1.83 .08*** .08 Single Unemployed Women 459 5.69 2.34 - .32** .10 Single Unemployed Men 521 5.43 2.35 - .62* .10 Married Employed Women 5294 7.41 1.75 .61* .08 Married Employed Men 6748 7.30 1.74 .48* .08 Married Unemployed Women 454 6.13 2.28 .16* .10 Married Unemployed Men 449 5.69 2.48 Reference Category N 20936 Restricted log likelihood 77738.28 dfChange 4 χ2

Change 315.49 Dependent Variable: Well-Being * p < .001; ** p < .05; *** not significant Controlled for: health, education, children under 12 years old, subjective income

4.3 Respondent’s partner’s employment

My third hypothesis was concerned with the role of the respondent’s partner’s employment

status. I expected that for women their partner’s employment status moderates the relationship

between unemployment and well-being. The analysis was once again conducted using dummy

variables to test for significant interaction effects of unemployment and employment status of the

respondent’s partner. The results are shown in TABLES 4.9 and 4.10.

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TABLE 4.9

MLM with Dummy Groups “Employment & Employment Partner” for Men

Parameter N Mean Std. Dev. Estimate Std. Error Intercept 6.67* .13 Both Employed 5039 7.45 1.63 .49* .09 Employed/Partner Unempl. 2656 7.16 1.86 .51* .09 Unemployed/Partner Empl. 232 6.02 2.29 - .08*** .13 Both Unemployed 316 5.61 2.53 Reference Category N 8241 Restricted log likelihood 30003.32 dfChange 2 χ2

Change .73 Dependent Variable: Well-Being * p < .001; ** p < .05; *** not significant Controlled for: health, education, children under 12 years old, subjective income

TABLE 4.10

MLM with Dummy Groups “Employment & Employment Partner” for Women

Parameter N Mean Std. Dev. Estimate Std. Error Intercept 6.53* .15 Both Employed 5330 7.51 1.67 .73* .13 Employed/Partner Unempl. 795 6.99 2.06 .66* .13 Unemployed/Partner Empl. 378 6.44 2.16 .38** .14 Both Unemployed 148 5.54 2.37 Reference Category N 6667 Restricted log likelihood 24145.32 dfChange 2 χ2

Change 8.11 Dependent Variable: Well-Being * p < .001; ** p < .05; *** not significant Controlled for: health, education, children under 12 years old, subjective income

According to the results presented above, the interaction does not significantly improve the

model for men (χ2Change = .73). However for women, the value of χ2

Change = 8.11 indicates a significant

improvement. As for the models itself, they show that unemployed women whose partner is employed

are significantly happier than women who live in a relationship where both partners are unemployed,

lending support to my third hypothesis. No such relationship can be found for men. Note that

employed women also react strongly to their partner’s unemployment, with well-being decreasing by

.07. These findings support my third hypothesis and underline the different degrees of importance of

work and partner’s employment in men and women.

4.4 Attitudes towards women’s roles in family and work

In Hypothesis 4 I postulate that women’s attitudes towards their role in family and

employment will moderate the relationship between unemployment and well-being. Women with

more progressive attitudes will therefore be similar to men in their reaction to unemployment than

women with traditional value patterns. I restricted the analysis to married respondents to account for

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the fact that value formation often takes place within the framework of one’s partnership.

TABLE 4.11

MLM with a random Intercept and Moderator “Values”

Men Women Parameter Estimate Std. Error Estimate Std. Error Intercept 7.15* .10 7.26* .10 Unemployed - .60* .09 - .44* .08 Values - .06** .02 .05*** .03 Unemployed X Values .19** .08 - .15*** .08 N 7213 5753 Restricted log likelihood 26491.80 20980.65 Dependent Variable: Well-Being * p < .001; ** p < .05; *** not significant Controlled for: health, education, children under 12 years old, subjective income

At a first glance, the results of the MLM, presented in TABLE 4.11 above, do not support this

hypothesis. The interaction term does not significantly predict well-being in women (p > 0.05).

Interestingly, the interaction term does significantly predict well-being in men (p < 0.05). At this point

I decided to re-run the analysis for those respondents with very traditional values versus those with

very progressive attitudes towards women’s role in family and work. Please find the results below in

TABLES 4.12 and 4.13.

TABLE 4.12

MLM with Dummy Groups “Values in the Unemployed” for Men

Parameter N Mean Std. Dev. Estimate Std. Error Intercept 6.73 .17 Progressive Employed 1392 7.99 1.37 .60* .16 Traditional Employed 58 6.43 2.55 .28*** .15 Progressive Unemployed 1071 6.64 2.01 - .06*** .25 Traditional Unemployed 148 5.45 2.54 Reference Category N 2676 Restricted log likelihood 10003.03 dfChange 2 χ2

Change 16.30 Dependent Variable: Well-Being * p < .001; ** p < .05; *** not significant Controlled for: health, education, children under 12 years old, subjective income

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TABLE 4.13

MLM with Dummy Groups “Values in the Unemployed” for Women

Parameter N Mean Std. Dev. Estimate Std. Error Intercept 6.35* .20 Progressive Employed 1587 7.78 1.52 .88* .18 Traditional Employed 110 7.07 2.20 1.07 .18 Progressive Unemployed 498 6.88 1.94 .80* .22 Traditional Unemployed 78 5.28 2.53 Reference Category N 2278 Restricted log likelihood 8165.02 dfChange 2 χ2

Change 19.45 Dependent Variable: Well-Being * p < .001; ** p < .05; *** not significant Controlled for: health, education, children under 12 years old, subjective income

For both gender, the interaction model provides a better fit and the results indicate two main

mechanisms. First, men’s reaction to unemployment does not seem to be significantly affected by their

values towards women’s role in family and work. Second, there is a significant difference between

women with traditional and those with progressive attitudes. Interestingly, this relationship manifests

itself in direct opposition as hypothesized. In fact, it is women with more progressive values who are

significantly happier in unemployment and not those with more traditional values. In conclusion, I

could not find any support for my fourth hypothesis.

4.5 Proportion of contribution to the household income Finally, I hypothesized that the proportion of household income contribution will moderate the

relationship between unemployment well-being and that he more women contribute to the household

income the more will they be similar to men in their reaction to unemployment. TABLE 4.14 displays

the results.

TABLE 4.14

MLM with a random Intercept and Moderator “PropIncome”

Men Women Parameter Estimate Std. Error Estimate Std. Error Intercept 7.00* .10 7.09* .10 Unemployed - .70* .06 - .58* .06 PropIncome - .04* .01 - .10* .01 Unemployed X PropIncome .02*** .03 .05*** .02 N 11048 9494 Restricted log likelihood 41309.97 35290.38 Dependent Variable: Well-Being * p < .001; ** p < .05; *** not significant Controlled for: health, education, children under 12 years old, subjective income

Contrary to my hypothesis, the interaction term of unemployment and proportion of income

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contribution does not significantly predict well-being in women – or men for that matter (p > 0.05).

However, proportion of income contributed itself does seem to predict well-being and it seems to

differ between men and women. To take a more in-depth look at the influence of the proportion of

income I reran the analysis for both men and women combined to see whether there exists an

interaction effect of gender and proportion of income. The results are presented below.

TABLE 4.15

MLM with a random Intercept and Interaction Term “Gender X PropIncome”

Parameter Estimate Std. Error Intercept 6.87* .10 Gender .11* .02 Unemployed - .67* .04 PropIncome .03*** .02 Gender X PropIncome - .06* .01 N 20542 Restricted log likelihood 76521.20 Dependent Variable: Well-Being * p < .001; ** p < .05; *** not significant Controlled for: health, education, children under 12 years old, subjective income

As shown above, there exists a significant, albeit small, interaction effect of gender and

proportion of income. The effect of income contribution on well-being seems to be higher in women

than in men. However, in regard to the unemployed, the proportion of income contributed did not

significantly affect well-being.

4.6 Summary of Results Overall, I was able to find support for two of my original hypotheses and was able to partially

back up a third. First, I was able to reproduce past findings that unemployed women are happier than

unemployed men. Second, whether or not women’s partners are in paid work exerts a significant

moderating influence on women’s reaction to unemployment. Having a working partner to fall back

on alleviates the burden of unemployment, and women who are the single earner in the relationship

are significantly unhappier than those women, whose partner is employed. Also, although marital

status moderates the effect of unemployment on well-being and single women are affected worse by

unemployment than married women, single women are still happier than single men. I found a

significant interaction affect for unemployment and the attitude towards women’s role in family and

work. Interestingly, the direction of the effect ran counter to my expectations, in that unemployed

women with more progressive attitudes seem to be happier than their more traditional counterparts. I

will comment on this in the following section.

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5. DISCUSSION

Being employed is one the main contributors to people’s well-being and the interest in this

relationship has spurred a vast amount of research, while still compelling researchers to try to dig

deeper and deeper to unravel the mechanisms behind employment and happiness.

My goal with the present research paper was to contribute to the existing knowledge by

focusing on gender differences in well-being in reaction to unemployment. By specifically

concentrating on moderating factors I sought to find additional information on what determines

especially female reaction to unemployment. It is the strength of this research that it concentrates

specifically on a number of factors from the work-gender-family realm to uncover some of the

processes leading to increased well-being. I also wanted to specifically answer questions left

unanswered by previous research such as e.g. the role of normative beliefs about women and work in

influencing well-being (Forret, Sullivan & Mainiero, 2010).

My results showed that, in accordance with previous research, unemployed women are in fact

significantly happier than unemployed men. While marital status did significantly affect well-being in

unemployed women, the same mechanism holds for men and single unemployed men are still

significantly unhappier than single unemployed women. When it comes to being unemployed, being

married does seem to make up for the loss of happiness it for both men and women.

Furthermore, it significantly matters whether the respondent’s partner is employed or not. In

direct extension of my elaborations on the importance of the husbands’ status and role for women’s

happiness, unemployed women are happier when their partner is employed. The fact that this

relationship holds although I controlled for subjective income indicates that the mechanisms behind

this relationship go beyond simple economic necessities and the result underlines how men and

women react differently to unemployment. While for men, their own unemployment seems to be the

overwhelming negative force influencing their well-being, women seem to evaluate their

(un)happiness more in the broader context of the relationship duality. It is also possible, considering

that men react stronger to unemployment than women, that men bring more of their unemployment-

induced unhappiness into the relationship, putting additional strain on themselves and their partners. If

this is the case, unemployed women with unemployed partners suffer more from their partner’s

reaction to unemployment than by the actual dual unemployment itself. This argument is strengthened

by the fact that women react strongly to their partner’s employment status regardless of their own

position in the labor market. There still appears to be a big difference between the way unemployment

is perceived in men and women.

One of the more astonishing findings was that the values towards women’s role in work and

family influenced well-being in unemployed women in the opposite way than I expected. Contrary to

my hypothesis, women with more traditional values were not happier but unhappier than those women

with more progressive attitudes. I can only make assumptions as to why this is the case, my best guess

RESEARCH PAPER FH

29

is that women who hold progressive values in general are that much happier than the ones with more

traditional beliefs that even in the case of unemployment this does not change. Future research could

take a closer look at this.

Finally, I did not find any significant moderating effect of the proportion of income to the

household income. I believe there exist some possible explanations for this. First, the effect of

proportion of income might be captured by unemployment and subjective income. Second, and most

importantly, having a measure of the income contribution before becoming unemployed might alter

the results of the analysis. Unfortunately, such data was not available and could be hard to come by.

Still, I believe that the question of who is the main earner in the relationship is a very important one in

regard to unemployment and future research with possible longitudinal analyses might be able to

provide a clearer picture.

While there still remains work to be done in the field of unemployment and happiness, such as

dealing with the question of who is the main breadwinner in the relationship, I believe that the present

research contributes to the status quo by unraveling part of the underlying mechanisms in regard to

gender differences in the reaction to unemployment. The results of my research, especially the insights

on gender differences, therefore can add another piece of credibility to the cause of those who call for

a “re-examination of the traditional utilitarian principle that the maximization of happiness should be

adopted by governments as an aim of law and public policy“ (Duncan, 2010: 163) and also underline

the persistent differences in gender ideologies we have yet to overcome as developed industrial

nations.

Naturally, there are some limitations to this research and the general applicability of its results.

In addition to the points I mentioned earlier, it is certainly possible to argue for a closer look at

mediation effects between the different factors I examined. For example, Del Boca, Locatelli &

Pasqua (2000) found that women’s employment decisions in response to their partner’s unemployment

depend on their inherent attitudes towards work. A similar process, among other cross-dependencies,

can be imagined for female well-being and could be a venue for future research.

To conclude, although a lot of progress has been made in the field of happiness research, the

need for a more thorough entanglement of the numerous interdependencies remains, with the role of

employment being one of the main areas where special attention is warranted.

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30

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