Gender, Unemployment & Happiness –

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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

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ABSTRACT

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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

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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.

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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.

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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.

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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?

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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).

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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).

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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

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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).

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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.

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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

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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.

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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

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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-“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.

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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

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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 (2-tailed) Sig. 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

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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

χ2Change 33.00

Dependent Variable: Well-Being

* p < .001; ** p < .05; *** not significant

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TABLE 4.6

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

Intercept 6.38* .11

Employed Men .66* .05

Employed Women .77* .05

Unemployed Women .23** .07

Unemployed Men Reference Category

N 21014

dfChange 2

χ2Change 33.00

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

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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

dfChange 4

χ2Change 315.49

TABLE 4.8

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

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

dfChange 4

χ2Change 315.49

4.3 Respondent’s partner’s employment

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TABLE 4.9

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

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

dfChange 2

χ2Change .73

TABLE 4.10

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

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

dfChange 2

χ2Change 8.11

According to the results presented above, the interaction does not significantly improve the model for men (χ2

Change = .73). However for women, the value of χ2Change = 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

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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

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

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

dfChange 2

χ2Change 16.30

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TABLE 4.13

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

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

dfChange 2

χ2Change 19.45

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

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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”

Intercept 6.87* .10 Gender .11* .02 Unemployed - .67* .04 PropIncome .03*** .02 Gender X PropIncome - .06* .01 N 20542

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

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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.

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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.

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