Happiness and Childbearing Across Europe - Springer Link

Soc Indic Res (2012) 108:65–86 DOI 10.1007/s11205-011-9866-x

Happiness and Childbearing Across Europe Arnstein Aassve • Alice Goisis • Maria Sironi

Accepted: 9 May 2011 / Published online: 24 May 2011 Ó Springer Science+Business Media B.V. 2011

Abstract Using happiness as a well-being measure and comparative data from the European social survey we focus in this paper on the link between happiness and childbearing across European countries. The analysis motivates from the recent lows in fertility in many European countries and that economic wellbeing measures are problematic when considering childbearing. We find significant country differences, though the direct association between happiness and childbearing is modest. However, partnership status plays an important role for both men and women. Working fathers are always happier, whereas working mothers are not, though mothers’ happiness tends to increase with household income. Keywords

Happiness Childbearing Comparative European social survey

1 Introduction When looking across European countries we find important differences in happiness, desired and realized fertility levels, social norms, and institutional constraints, as well as differences in the way welfare provision is organised. Is it possible that differences in fertility are reflected, at least partly, by differences in the level of happiness couples associate with childbearing? This would be the case if European couples during their A. Aassve Carlo F. Dondena Centre for Research on Social Dynamics, Universita` Bocconi, via Guglielmo Ro¨ntgen 1, 20136 Milan, Italy e-mail: [email protected] A. Goisis Department of Social Policy, The London School of Economics and Political Science, Houghton Street, London WC2A 2AE, UK e-mail: [email protected] M. Sironi (&) Graduate Group in Demography, Population Studies Center, University of Pennsylvania, 3718 Locust Walk, Philadelphia, PA 19104, USA e-mail: [email protected]

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childbearing age faced differences in the resources available to them. For instance, we know that European countries differ tremendously in the way the state provides support to couples with young children. Rather than exploring how these factors impact childbearing, we take a more indirect approach by asking whether childbearing is associated with individuals’ subjective wellbeing—here measured by individuals’ self reported level of happiness. The focus of our analysis is two-fold. First, interest lies in whether there are differences across countries in the association between happiness and childbearing. Is it possible that average levels of parental happiness are lower in countries where fertility is lower? Moreover, would such an analysis reveal patterns consistent with how governments organise their support to couples with young children? With the comparative data source, we investigate if the predicted levels of happiness seen as a function of childbearing fits well-established typologies of welfare provision. Second, it has been argued that there is an important link between happiness, childbearing and partnership status. In particular, happiness associated with childbearing might be considerably lower for single parents. We investigate and expand the literature by considering the importance of these links using information from a range of European countries. Moreover, one argument for why in some countries there are now extremely low fertility levels is that women find it increasingly difficult to combine work and childbearing. Again, we test to what extent this is a European wide phenomenon by predicting how happiness from childbearing differs for those women who are working from those who are not. Finally, we also assess the role of income, the argument being that high income might facilitate outsourcing of family activities (such as external childcare) and enhance happiness associated with childbearing. By taking a comparative perspective and using data from the 3rd round of the European Social Survey (ESS from now onwards) we aim to shed insights into these questions. The ESS is ideal for comparative analysis as it is run on a large number of countries. It includes information about childbearing and a specific question where individuals are asked to grade their level of happiness on a scale from 0 to 10, the latter indicating the highest level. Consequently, we are able to consider not only how childbearing is related to individuals’ happiness, but also how this relationship differs across European countries. The analysis is limited to a cross-sectional presentation of the association between happiness and childbearing, the main aim being to map differences across countries with rather different institutional arrangements. Clearly, the survey with its cross-sectional perspective, does not answer the obvious causal question: to what extent do children make individuals happy as opposed to the extent happy individuals go on having children. Here our aim lies in answering if there are systematic differences across countries in its association, and whether systematic associations with work, income and partnership status are present across a range of European countries. The paper is organized as follows: Sect. 2 presents the background, Sect. 3 describes the European Social Survey, in Sect. 4 we present the descriptive analysis of the sample, Sect. 5 contains the outcomes obtained from the regressions where we investigate the relationship between childbearing and happiness, progressively adding controls for country differences and individual characteristics. Section 6 concludes.

2 Background 2.1 Childbearing in European Countries Is parenthood and childbearing associated with higher happiness? To what extent do parents differ in the happiness they derive from having children? By looking at birth rates

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across European countries over the last few decades, one might get the impression that the happiness associated with having children has declined somewhat. We find reductions in fertility levels particularly severe in Mediterranean countries and in the former socialist countries in Central and Eastern Europe. This is in contrast to the Scandinavian countries, and the Liberal countries of the UK and the US, but also France—where fertility levels have remained relatively high i.e. around replacement level. The factors behind these diverse fertility rates are obviously complex. For the former socialist countries of Central and Eastern Europe, fertility declined sharply after the fall of the Iron Curtain. Prospective couples in these countries faced sudden societal change accompanied with economic decline and increased unemployment (Aassve et al. 2006). In other words, individuals faced a new challenging environment full of uncertainty. These dramatic changes are important in explaining the decline in fertility rate in these countries. The fertility decline in Mediterranean countries is somewhat more difficult to explain. One of the possible explanations is that, during the last decades, European societies have undergone major social and cultural changes, which have hugely affected the perception of traditional values concerning family and reproduction (van de Kaa 2002). For instance, European societies have experienced a postponement of various demographic events: young women and men are devoting more time to education, leave parental home and get married later. As a consequence, they also form families later than before. The timing of childbearing among women is certainly linked to educational attainment (Martin 2000). That is, those opting for higher education tend to postpone the onset of childbearing, but are considerably quicker in having subsequent births compared to those women with lower education (see for example, Aassve and Lappega˚rd 2009). Related to this point, concerns the fact that over the last decades, through massive expansion in education, women have gained stronger economic independence. Currently, women are at level with men in higher education enrolment. Whereas clear gender differences in academic fields persist, which will undoubtedly have an impact on childbearing decisions (Lappega˚rd and Rønsen 2005; Van Bavel 2010), women have become more career oriented compared to a few decades ago, meaning a stronger preference for combining family and work careers (Dex and Joshi 1999; Joshi 1998). An important argument stemming form these structural changes are that individuals’ value orientations are changing, which is a key argument in the Second Demographic Transition (SDT) thesis. SDT is characterized by the progressive independence of the members of a society who started giving increasing importance to their own realization (rather than to their family’s or to their children’s), to their psychological (rather than to their material) well-being and to their personal freedom of expression (Van de Kaa 1987, 1994). Thus, childbearing is no longer the primary goal in individuals’ lifecourse decision making, and thus, the happiness associated with childbearing, might have been diluted. Whether this is a valid argument is however doubtful. It appears that those countries that progressed furthest in the second demographic transition, i.e. the Social Democratic Countries of Scandinavia, scores highly in average happiness and have high levels of fertility. Another possibility is that happiness associated with childbearing depends on how societies facilitate childbearing through generous benefits and parental leave schemes. For instance, high fertility in Scandinavian countries is often attributed to their generous support to families with young children, which has steadily increased with higher educational enrolment of women (Gauthier 1999; McDonald 2000). Interestingly, very few of the policies introduced were directly aimed at increasing fertility per se—instead they key aim has been to improve gender equality. Thus, if women’s aspirations include both childbearing and obtaining a satisfactory working career, we might find that the happiness

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associated with childbearing is higher in these countries. The situation of the Scandinavian countries is in stark contrast to the Mediterranean countries, where state welfare provision is weak, especially for couples with young children. Family relatives, especially grandparents, are expected—more than in most other countries—not only to give support in terms of helping out on childcare, but also to provide more general economic support. Whether such a familialistic organisation of welfare is compatible with new and emerging value orientations is certainly debatable and there are many reasons why it may have a detrimental impact on overall fertility levels and the happiness associated with it. One important aspect is that grand parenting is simply insufficient. For instance, ‘‘young’’ grandparents may themselves be in full employment, whereas ‘‘old’’ grandparents may be too frail to provide extensive childcare, both situations hampering grand parenting. When comparing different European countries, it becomes clear that there are important differences in the way individuals and couples face different constraints in their childbearing decisions, and their levels of wellbeing may differ as a result. 2.2 Subjective Well-Being: Connection with Fertility and Measurement Issues Subjective wellbeing is potentially an important aspect of explaining fertility and there are some good reasons for considering subjective happiness from childbearing as an alternative over more traditional welfare measures. The predominant perspective in economics is to measure wellbeing in terms of some money metric measure. The usual approach for developed countries is to use net household income, which is equivalised by a suitable scale, capturing the composition of the household and economies of scale in household consumption. The approach taken for developing countries follows the same principle, though here wellbeing (or lack thereof) is measured in terms of household consumption expenditure. Independent of whether wellbeing is defined over household income or consumption expenditure, the use of equivalence scales introduces a serious problem, especially when the focus is on children of the household. The problem lies in the fact that adding a child to the household decreases the per head wellbeing all else equal. From a revealed preference perspective, this is a perverse outcome: a couple choosing to have a child, presumably because it increases their subjective wellbeing, will be recorded with a reduced economic wellbeing. In other words, the use of subjective wellbeing measures is particularly useful when considering demographic events. As is well known, the correlation between happiness and income is not always very strong (Easterlin 2001). One popular hypothesis is that well-being is primarily determined by personality traits and other genetic factors and therefore highly stable over the life course (Easterlin 2003, 2005; Kohler et al. 2005). This view is known as the set point theory and predicts that a substantial part of variation in well-being is due to social or biological endowments that are unobserved in social surveys, which thus explains why happiness does not necessarily follow closely observed income levels (Oswald 1997). A corollary of the set point theory is that it is not necessarily obvious that demographic events should impact couples’ wellbeing. For instance, having a child might increase happiness and satisfaction in the short run, but after some time of adaptation, individuals may return to their set level of happiness. A related argument concerns the fact that it is not necessarily the case that the expected level of happiness associated with childbearing prior to the event—which presumably is an important driver behind the behaviour—is wholly consistent with the realised happiness after the event. Consistent with prospect theory (Kahneman and Tversky 1979), individuals have a subjective perception of the increased happiness from having a(nother) child, which affects the gain they expect to receive when

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it happens. However, given the enormity of the event, predicting happiness is difficult. Some might experience an even higher level of happiness, possibly forming a positive attitude towards having another child, whereas for others the realised happiness becomes lower than what was predicted prior to the event. The subjective element of happiness is also important in the Theory of Planned Behaviour as developed by Ajzen (1991), which is now increasingly being applied in demography. Here attitudes, which by definition are subjective, form individuals’ intentions and subsequent behaviour. A positive attitude towards childbearing is positively correlated with predicted happiness from childbearing, and should as a result increase the likelihood of it happening through stronger intentions. Billari et al. (2009) using data from Bulgaria shows that positive attitudes towards childbearing, also increases their intentions in a powerful way. The empirical literature considering how individuals associate demographic events with prospective happiness is extremely limited. One exception is the work by Billari and Kohler (2009) using the Gender and Generation Surveys (GGS). Relying on questions where respondents are asked to evaluate their happiness from future childbearing events, they find systematic differences that are not only driven by individual characteristics, but also from the institutional setting. Thus, the predicted happiness from childbearing appears higher in countries where the institutions are positively geared towards childbearing and that provides generous support to families with young children. Whereas measures of subjective happiness provide many benefits over the use of income, it is easy to see its disadvantages. As brought up by Clark et al. (2006), does a question asking about current happiness on some ordinal scale really provide a good assessment of current circumstances that relates to, for example, family life, job and income? Is it possible that the response also picks up transient factors such as having a cold or toothache, the weather, or their favourite sports team’s recent results? Moreover, can we compare responses of different people and carry out interpersonal or intertemporal comparison in happiness scores? Measurement issues such as the reliability and validity of the replies, whether respondents report their true feelings, and possible biases resulting from the context in which the question is asked, have been extensively studied (Diener 1984; Pudney and Conti 2011; Veenhoven 1993). The general conclusion of this literature is that subjective indicators, though not perfect, do reflect respondents substantive feelings of well-being—in the words of psychologist Diener (1984, p. 551), these ‘‘measures seem to contain substantial amounts of valid variance’’ (Easterlin 2001). Although there is now a substantial literature on the comparative aspects of happiness (see surveys by (Easterlin 1994; Veenhoven 2000), few have considered the links between childbearing and happiness. The analysis by Kohler et al. (2005) based on Danish Twin Registry data collected in 2002, considers the effect of childbearing and partnership on happiness. A key issue concerns genetic endowments and predispositions affecting both the level of happiness (i.e. the outcome variable) and childbearing and marriage (the explanatory variables), thus giving rise to an omitted variable bias. In other words, genetically happier personality traits may be positively associated with both higher likelihood of partnership formation and childbearing. Kohler et al. (2005) overcome this problem by using data on monozygotic twins, which in essence allows them to control for otherwise unobserved traits such as preferences and capabilities driven by genetic dispositions, family background, and the neighbourhood in which the twins grew up. The estimates therefore come closer to revealing the causal contributions of marriage and fertility towards individuals’ happiness. Their analysis suggests a large positive effect of the first-born child on mothers’ happiness and significant positive impact of the first born boy on fathers’ happiness. Interestingly, additional children beyond the first-born do not

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give higher levels of parental happiness. The econometric analysis shows that OLS regression tends to underestimate the happiness gains from the first child for women, while it overestimate the increases in men’s subjective well being resulting from the first child. The results yield interesting insights, namely that certain dimensions of partnership formation and childbearing have appreciable and persistent effects on happiness, which in essence rejects the set point theory. Other relevant contributions include Zimmermann and Easterlin (2006) and Stutzer and Frey (2006). These papers consider the role of childbearing in a general framework of wellbeing and marriage or partnership. The first paper finds no significant effect of children on life satisfaction for both those individuals who remained married and those who did not. The second paper, in contrast, find a positive correlation between childbearing when using pooled estimation techniques. In contrast, the fixed effect specification finds small but negative partial correlations for having one child or more. Billari (2008) presents descriptive analysis from the Gender and Generations Surveys (GGS) of France, Germany, Bulgaria, Georgia, Russia and Hungary, showing a positive, albeit modest, positive effect of children on happiness. Interestingly, it appears that parental happiness is highest in the high fertility country of France. Margolis and Myrskyla (2010) use the World Value Survey to assess how each additional child affects parental reported happiness in different groups of countries. They find that happiness is reduced when having children, but at different degrees across groups of countries, and that the happiness changes with the age of the respondent.

3 The Relationship Between Happiness and Childbearing: A Comparative Perspective The motivation behind our analysis starts from the analysis by Kohler et al. (2005) who considers how fertility and partnerships may affect wellbeing. Our key question concerns how the relationship between happiness as a measure of wellbeing relates to childbearing and partnership in a comparative setting. Whereas Kohler et al. (2005) finds large effects of the first born on mothers’ happiness, a sizeable effect on father’s happiness if the first born was a boy and additional positive effect if the mother was in a stable partnership, one can easily imagine that these effects would differ in other contexts. Denmark is the country where general happiness is one of the highest and they have one of the highest fertility levels in Europe. As we discuss below, other countries fare much worse both in terms of happiness and fertility levels and our focus is on how the relationship between happiness and childbearing differs in those contexts. A natural starting point is to assume that childbearing indeed does make individuals happier, and therefore act as the key motivator behind having children in the first place. Consistent with prospect theory, couples predict their level of happiness to increase and therefore act accordingly. In other words, if individuals predict their level of happiness to increase from having children, they will also go on and have children, whereas those who have a negative valued prediction will not—or at least be less likely to do so. Individuals and couples may differ in the quality of these predictions, of course. This heterogeneity might be part random and part dependent upon observed individual characteristics or dependent upon the characteristics of their social networks (and their experiences of childbearing). More relevant in the comparative perspective is that the characteristics of the country where couples reside may have an impact on their assessment of happiness associated with childbearing and therefore influence their childbearing decisions. Here

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useful insights can be derived from the literature on welfare regimes. As suggested by Esping-Andersen (1999), and elaborated on by Ferrera (1996) and Trifiletti (1999), welfare regimes in Europe can be summarised by: (1) ‘‘Social Democratic’’ (e.g. Denmark, Finland, Norway and Sweden) with generous and universal entitlements, (2) ‘‘Conservative’’, (e.g. Netherlands, Belgium, France, Germany and Austria) where social policies are linked to earnings and occupation, (3) ‘‘Liberal’’, (e.g. Great Britain and the US) where services are to a greater extent provided by the market, and emphasis on means testing, and (4) ‘‘Mediterranean’’, (e.g. Greece, Italy, Cyprus, Spain and Portugal), with strong reliance on family relations with limited public welfare support. Previous research has shown that economic wellbeing (measured either in terms of poverty or deprivation) associated with childbearing indeed differs across these country groups. For instance, Aassve et al. (2005) shows that in Scandinavian countries, there is no difference in poverty rates between households with and without children, whereas in Mediterranean and Anglo-Saxon countries there is a clear gradient—the more children—the higher is the poverty. However, they also report country specific estimates, showing that within some of the welfare groups, there is significant difference. This is particularly the case for Great Britain and Ireland, whereas the Mediterranean countries are rather homogenous with similar effects of childbearing. Other countries appear to be misplaced. Estimates for Austria are similar to that of Denmark, whereas estimates for Germany are similar to those of Mediterranean countries. Interestingly, they also compare results when wellbeing is measured in terms of an index of subjective index of affordability as opposed to standard poverty rates. Individuals’ own assessment of affordability is not compromised in Social Democratic countries from childbearing, but it is in Anglo-Saxon countries and to some extent in Mediterranean countries. Little is known about the relationship between wellbeing and childbearing in the former socialist countries of East Europe. An important reason is lack of comparable data, though the onset of the EU-SILC should change this. There are many good reasons for looking into the intersection of wellbeing and childbearing in these countries. For a start, fertility levels have plummeted whereas levels of happiness are among the lowest in Europe (Deaton 2008). There is lively debate about whether these countries can be grouped within existing and established welfare typologies (Saraceno and Keck 2008) or whether they should be considered as a separate group. There is likely to be heterogeneity and over time, one could imagine that some countries (e.g. the Baltic countries) converge to the Scandinavian Social Democratic model, others towards continental Europe (e.g. Poland and Hungary) whereas others converge towards the Mediterranean model (e.g. Romania and Bulgaria). This is of course too early to tell. What is clear, though, is that these countries have experienced dramatic social upheavals in a rather short period of time. Many countries have experienced periods of reduced real wages, reduced female labour force participation and harder labour markets, all in which must have had important effects on individuals’ sense of optimism. In a time of increased uncertainty, one should not be surprised that couples may delay or decide against big life changing decisions, which childbearing ultimately is. Thus, one suspect that the association between childbearing and happiness is lower in these countries compared to lets say—Scandinavian countries. Given differences across countries in terms of state welfare and general support, one might also expect that the role of partnership in individuals’ assessment of happiness associated with childbearing varies. As we know, single motherhood is much more frequent in Scandinavian countries and not at all frequent in Mediterranean countries. This is not unexpected as the poverty rate, and hence lack of economic wellbeing, associated with single motherhood is much less severe in countries where there is strong state welfare

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support. In general, one would expect a positive interaction between childbearing, partnership and happiness. Partnerships increase the disposable income since couples can pool resources for common expenses. In line with Stutzer and Frey (2006), happiness is closely related to the emotional status and being in a partnership may provide a way to increase self-esteem, possible reducing perceived stress levels, and perhaps especially so with regard to children. Thus, in so far being in a partnership reduces the emotional stress associated with raising children, we should see a positive association with happiness and partnership status. In contrast, a break-up of the partnership may alter the perception of childbearing in a negative way, resulting in lower happiness. Individuals in partnership are less prone to loneliness, and happiness has a clear negative association with loneliness. However, since countries differ in their support for single parenthood, the importance of partnerships may also differ. There might be rather large differences associated happiness associated with childbearing in Italy if you are a single parent compared to being so in Scandinavia. It is useful to sum up our expectations in terms of a set of key hypotheses. First, we would expect a positive relationship between happiness and being a parent (H1). In contrast, the effect of the number of children is less clear. Adopting the assumption that parents have more children because they increase their wellbeing, we hypothesize a positive relationship (H2). There are however several factors that go against such a hypothesis. First, if the set point theory is valid, one would expect adaption effects, which would be stronger with higher order parities. That is, having the first child might have a significant and long lasting impact on happiness since it brings about parenthood, whereas adaption becomes stronger when having further children. In addition, a higher number of children may compromise leisure time and working careers, suggesting that there is an important gender difference in the way the number of children affects happiness. Given the suggestion of a positive relationship between welfare support and childbearing, we would expect the association to be stronger in Scandinavian countries and weaker in the former communist countries of East Europe and in Mediterranean countries (H3). The underlying idea is that children are costly, and as such, generous financial support should make the association between happiness and childbearing stronger. Our fourth key hypothesis (H4) is that happiness associated with childbearing interacts positively with partnership status. We would expect this to be a general feature of childbearing across societies, though its magnitude may differ depending on the level of state support available to single parents. A corollary of this argument is that income should be positively associated with childbearing, suggesting that happiness with childbearing is increasing with income, which forms our fifth hypothesis (H5). Though work status is key for income generation, the prediction for employment status is less straight-forward, and most likely it is gender specific. As women tend to be the ones bearing the burden of childbearing, we would expect work to have a negative interaction with happiness and childbearing (H6). For men the prediction is less clear, and would depend on their level of contribution to home activities (which would affect the happiness of mothers), which depends on gender role expectations, which in turn may depend on the country where the couple resides.

4 Data Information concerning couples’ happiness and childbearing choices is taken from a crosscountry comparative sample survey, the European Social Survey. The ESS is representative of the population aged 15 and over, resident within private households in each

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participating country. The questionnaire contains a ‘core’ module, which is repeated in each survey round, and a series of ‘rotating’ modules, which vary in each bi-annual round. The minimum effective sample size for each country is 1,500 (or 800 for countries with less than 2 million inhabitants). So far, four rounds have been conducted. 22 countries were included in Round 1 (2002), 26 in Round 2 (2004), 25 in Round 3 (2006) and 26 countries in round 4 (2008). The main aim of the ESS is that of outlining the attitudes of the different regions towards religion, politics, and moral issues, while also depicting their social habits and how they are changing over time and as such pertains closely to the US General Social Survey.1 The first part of the survey pertains to individuals’ value and ideological orientations. These orientations are partly the cause of people’s opinions, behaviour and actions, thus becoming an important driver behind the social, political and economic changes within their respective societies. Secondly, the ESS considers individuals’ cultural and national orientations, a feature being of key importance given the process of unification of the Western European countries. The third main area concerns the underlying social structure of society. Since values and social change are strongly driven by the social composition (e.g. education and occupations) identification of these factors is essential in drawing a correct picture of the social climate. Our analyses are based on the 3rd round of the ESS, which was collected in 20062 and includes a total of 19 countries.3 In order to assess the individual level of happiness we use a measure that has become more or less the standard in the literature. The variable is constructed from the question: ‘‘How happy are you?’’ on a scale ranging from 0 (extremely unhappy) to 10 (extremely happy). We restrict our attention to those individuals whose age ranges between 20 and 50, which makes the sample more homogenous, especially with regard to childbearing behaviour. Respondents younger than 20 are excluded from the sample as their level of happiness may be biased due to early pregnancy or particular financial difficulties. Parents older than 50 years of age are also excluded. Subjective levels of happiness change notably with age. Moreover, their response to happiness, and in particular with regard to childbearing, may be affected by their grandparent status. After having reduced the size of the data set by taking out all the missing values for the variables of our interest and restricting the age class, we end up with a sample of 14,419 observations. Table 1 presents descriptive statistics of the sample. The mean level of happiness in the considered set of countries is 7.44, where Bulgaria is the lowest with mean happiness level of 5.6 and Denmark being the highest with a mean of 8.3. We test whether there exist systematic differences in the level of happiness by regressing the variable happiness on country dummies. Using Denmark as the reference group, we find statistically significant differences in well-being levels. Denmark is one of the countries with highest level of happiness, and all countries exhibit statistically lower levels of happiness (see ‘‘Appendix 2’’). Poland is the country which has on average the youngest population (35 years), while 1

Unfortunately, the ESS and the General Social Survey differ in their measure of individual happiness. Whereas the ESS uses a 10-point scale, happiness in the GSS is based on 3 values.

2

In theory an integrated file of the 4 rounds could have been created. In practice, however, this would have caused some problems as some countries are included in all 4 rounds whereas others in only one or two. The result of this procedure would be an unbalanced dataset where some countries would be given a lot more weight than others.

3

The 3rd round potentially contains 25 countries, but we excluded Estonia, Ukraine, Russia, Hungary and Romania since data on income was missing for these countries or was recorded in a different way compared to rest of the countries. We also excluded Cyprus since our analysis primarily focuses on the European context.

123

123

440

763

1,118

647

672

826

925

695

698

885

945

730

498

908

557

518

982

BG

CH

DE

DK

ES

FI

FR

IE

LV

NL

NO

PL

PT

SE

SI

SK

UK

43.4

49.8

47.3

44.0

49.8

41.3

49.6

52.3

48.1

38.1

46.2

47.6

51.7

51.3

51.0

51.5

44.9

38.0

47.8

7.4

6.7

7.6

7.9

6.8

7.1

7.9

7.7

6.6

7.6

7.4

8.1

7.8

8.3

7.1

8.1

5.5

7.7

7.6

Mean

Happiness

2.0

2.0

1.8

1.5

1.7

1.9

1.6

1.4

2.0

1.8

1.8

1.3

1.6

1.3

2.0

1.4

2.5

1.4

2.0

SD

36.7

35.6

36.1

35.4

36.6

35.0

36.3

37.1

35.1

35.6

37.0

35.3

35.6

37.0

37.1

37.9

37.7

36.4

37.6

Mean

Age

8.2

8.8

9.1

8.6

8.2

9.3

8.8

8.0

9.5

8.2

8.1

8.7

8.5

8.1

8.5

7.9

8.9

8.8

9.1

SD

1.4

1.5

1.2

1.3

1.2

1.4

1.5

1.3

1.1

1.6

1.6

1.2

1.0

1.4

1.1

1.4

1.5

1.4

1.3

Number of children Mean

67.9

69.9

64.8

61.9

67.9

65.6

65.4

61.0

62.8

61.0

71.4

59.3

55.1

67.7

57.5

65.3

78.6

65.6

64.2

At least one child %

70.4

70.5

67.3

70.7

69.8

67.4

68.1

74.7

55.7

67.2

76.9

71.4

64.5

73.7

62.0

73.8

74.7

70.3

69.7

Living with partner %

49,566.9

11,111.6

19,431.6

36,833.9

21,112.8

8,807.5

59,694.6

36,167.3

15,048.6

47,995.8

32,620.6

35,731.2

28,058.9

46,009.0

30,578.6

59,504.4

3,594.3

36,636.2

31,618.1

Mean

Income

14.4

12.8

12.9

13.8

9.7

12.8

14.4

14.3

12.7

13.6

13.9

14.7

13.8

14.5

14.2

14.1

11.8

13.4

13.2

Mean

3.4

2.8

3.5

3.0

4.5

2.8

3.3

4.2

3.3

3.2

3.4

3.3

4.7

4.5

3.2

3.6

3.0

3.4

3.0

SD

Years of education

79.4

70.1

75.9

80.4

72.0

71.7

83.0

78.8

77.7

70.4

78.1

78.8

80.6

83.0

73.0

76.9

65.4

77.5

81.1

%

Working

Source Own computations using the ESS (3rd round). Respondents younger than 20 and older than 50 are excluded. In order to obtain accurate estimates the data has been weighted by design and population weights

800

812

% Male

N

BE

Gender

Obs.

AT

Country

Table 1 Descriptive table on happiness and other relevant variables, by country

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75

Switzerland the oldest one (38 years). The analyzed sample appears gender balanced since nearly 50% of the population are males, with the exception of Bulgaria and Latvia where males are 38% of the sample. Overall, there are more women (7,584) than men (6,835). Childbearing experiences can be measured in different ways and the association between happiness and childbearing differs depending on whether one considers the first child or the total number of children. A larger number of children may impose a significant economic cost and/or time commitments to childbearing, which may be related to individuals’ assessment of subjective well-being. In our analysis, we include two variables to capture these effects. The first is labelled ‘‘At least One Child’’ and takes the value 1 if the individual has ever given birth to at least one child (or fathered), 0 otherwise. On average, 60% of the respondents have at least one child; Spain is the country with lowest number—only 55% report to have at least one child, whereas Bulgaria has the highest percentage with 79%. The second childbearing variable refers to the number of additional children the individual has given birth to or fathered beyond the first and captures the potential economic burden of having a large family. Table 1 reports descriptive statistics for the total number of children the respondent declares to have given birth to/fathered.4 The average number is 1.16, where the maximum is found for Ireland (1.6) and the lowest is Spain (1.04).5 Table 1 also reports descriptive statistics for many of the relevant intervening variables. The variable ‘‘living with a partner’’ takes the value one when the respondent is currently living with husband/ wife/partner at home. This means that we are not dividing the sample by the status of the partnership (e.g. cohabitation as opposed to marriage). Whereas there might be a difference depending on the civil status of the partnership, we are here dealing with 19 countries, where the role of cohabitation will differ depending on the country concerned. In many countries, especially the Scandinavian ones, cohabitation is almost as common as marriage and more than half of all children are born outside marriage. Consequently, it does not give much meaning splitting the partnership status into different categories. The vast majority of the respondents (70%) is currently living with a partner. Income is positively associated with happiness (Blanchflower and Oswald 2004); especially in the lower part of the income range (Argyle 1999). Income in the ESS is recorded as a categorical variable, which reflects twelve income brackets ranging from less than €1,800 to €120,000 or more. Each interval corresponds to a precise range (e.g. 0-up to 1,800; 1,800-up to 3,600 etc.). Respondents are asked to place their annual household income in the respective intervals. We construct a variable by assigning to each income interval its mean (e.g. 900 for the first interval etc.). The main shortfall of this method is that we are not controlling for substantial heterogeneity of income levels and purchasing power across countries i.e. we are not dealing with a relative income measure. The descriptive table indeed shows that there is heterogeneity in income levels across countries. Norway is the country with the highest level of income while Bulgaria is the poorest. Education is positively associated with income, and may again be positively associated with happiness. In our sample, Portugal is the country with lowest average education (9.7 years), while Finland has the highest (14.7 years). We also control for the working status of the respondent since having a job increases living standards and to a certain extent well-being levels; on the other hand though, working may also imply difficulties in reconciling work and family life, especially for women. The descriptive statistics presented in 4

The questionnaire refers to ‘‘biological’’ children only.

5

Note that the sample is restricted to individuals aged 20–50, thus the average of this variable does not correspond to individuals’ completed fertility as many of the respondents are still young and in childbearing ages.

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Table 1 refer to general participation rates for both men and women. Denmark shows the highest participation rates (83%), while Bulgaria the lowest (65%).

5 Empirical Analysis The estimation is implemented by using a rank ordered probit model, which is clearly the most appropriate technique in this context given that the dependent variable for all the estimated models, happiness, is measured on an ordered and discrete scale (Wooldridge 2002). The technique is widely used in the literature on happiness, and is preferred over the simpler Ordinary Least Squares estimation (Alesina et al. 2004). We estimate regressions separately for men and women since from our hypotheses we expect the association between happiness and childbearing to be gender specific in several dimensions. A first general model is estimated in order to reveal the association between happiness and childbearing, while controlling for a set of parental characteristics. We then run different model specifications in order to reveal whether parenthood is differently associated with happiness across countries grouped according to welfare regime systems. In the final models a set of interaction effects is included into the models in order to reveal how the association between happiness and childbearing varies according to a set characteristics related to whether the respondent is currently in a partnership and socio-economic conditions, namely household’s income levels and whether the respondent is currently employed. Throughout the different models we will include country dummies to control for the fact that respondents live in very different institutional settings and this can in turn affect their happiness levels in general and ultimately the association between happiness and childbearing.6 All models are estimated with the software STATA (11.1). We start by investigating whether happiness and childbearing are associated generally. We do so by considering the association between declared happiness levels and different childbearing variables i.e. number of children, having at least one child and number of additional children after the first one. These estimates give insight into the first two hypotheses (H1 and H2). In all models, we include controls for education, income (which corresponds to the mean of each income interval), partnership and working status of the respondents.7 The results are reported in Table 2 separately for men and women. Age is negatively and significantly associated with happiness for both men and women, although the relationship is not linear. Interestingly, being in a partnership is strongly associated with happiness for men and women, a feature we explore more in detail below. The effect of income and working status on happiness are statistically significant and positive for both genders. The coefficients remain more or less constant throughout the extensions. Educational level is positively associated to women’s declared levels of happiness, but it is not significantly related to men’s levels of well-being. We analyse the role of children on happiness through three model specifications (denoted Model 1 to Model 3 in Table 2). In Model 1 we consider the association of the number of children with happiness levels. The coefficient is positive and significant for men, but only at 6 Denmark is the reference category. Table 3 will include group country dummies rather than country dummies. 7

Clearly, it would have been appropriate to control for the health status of the respondent since healthy individuals tend to be better off in many domains, including income levels and social status. However, we are not able to control for the health status since the ESS only provides a measure of subjective level of health, which one can argue is directly embedded into our dependent variable.

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Table 2 Happiness and childbearing for men and women Model 1: number of children

Model 2: At least one child

Model 3: Number of additional children (parents only)

b

SE

b

SE

b

Age

-0.118***

0.016

-0.114***

0.016

-0.010

0.013

Age squared

0.014***

0.002

0.013***

0.002

-0.000

0.002

SE

Men

Number of children

0.031*

0.017

Currently in partnership

0.402***

0.034

0.444***

0.027

0.612***

0.053

Working

0.353***

0.039

0.350***

0.039

0.421***

0.091

Annual household income

0.055***

0.014

0.055***

0.014

0.060***

0.018

Years of education

0.010

0.012

0.008

0.012

0.003

0.016

-0.036

0.039 0.061**

0.029

At least one child Number of additional children Pseudo R-squared

0.036

0.036

0.041

Number of observations

6,835

6,835

3,876

Women Age

-0.048**

0.020

-0.054***

0.018

-0.029

0.019

Age squared

0.004

0.003

0.005*

0.003

0.002

0.002

Number of children

0.017

0.012


0.360***

0.040

0.346***

0.037

0.402***

0.064

Working

0.076***

0.025

0.077***

0.024

0.054*

0.029


0.060***

0.008

0.061***

0.008

0.066***

0.012

Years of education

0.012***

0.004

0.013***

0.004

0.009*

0.005

0.086***

0.024 -0.007

0.011

At least one child Number of additional children Pseudo R-squared

0.029

0.029

0.0326


7,584

7,584

5,221

Source Own computations using the ESS (3rd round) and happiness as the dependent variable. Models include country dummies and Denmark is the reference category. ‘‘Age squared’’ and ‘‘Annual household income’’ have been divided by 10 and 1,000, respectively. Data has been weighted using population weights *** p \ 0.01; ** p \ 0.05; * p \ 0.1

the 10% level. Namely having a higher number of children is marginally associated with increased happiness. Conversely, the coefficient is positive but not statistically significant for women. Interestingly and in line with Kohler et al. (2005) the association between number of children and happiness levels is remarkably small, both in terms of coefficient’s magnitude and significance level for both genders. This could be due to the non-linear association between happiness and childbearing. Therefore, model 2 assesses if there are any differences in happiness of parenthood alone (as opposed to the number of children). That is, the key variable of interest is whether the respondents had at least one child, meaning that we are comparing the level of happiness for respondents being parents with those who are not (independent of how many children they have). The association is positive and significant for women only, although the coefficient is, again, quite small. Consequently, the data gives support for the first hypothesis (H1) only for women. In order to address whether there is any difference between the first born and any further children on happiness, thereby keeping in

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line with Kohler et al. (2005), we consider a specification where the childbearing variable measures the number of additional children—conditional on having at least one child. Model 3 shows the results. Here it is clear that there is no significant association for mothers—thus any additional children beyond the first does not increase their level of happiness—rejecting the second hypothesis (H2). This is in contrast to men, where happiness indeed increases with further children. The result for fathers is in contrast with the one observed in Kohler et al. (2005), where it is argued that for them motivations other than increasing happiness must be considered to explain the progression to additional parities. As was already pointed out, one possible explanation of the observed pattern for women is that a higher number of children tend to bring about a higher financial strain and time commitments towards raising children compared to families with only one child. In sum, these results suggest that happiness is positively associated with childbearing but the association is quite modest and does depend, across genders, on how childbearing status is measured. As expected, the association between happiness and childbearing is rather complex and possibly masked by several (observed and unobserved) intervening variables that affect both subjective well-being and childbearing behaviours. In what follows, we disentangle this association further by looking at the role of contextual factors and the interaction between childbearing with a set of individual characteristics. The models presented in Table 3 separate country specific factors to assess whether there exist differences on how parenthood is associated with happiness across countries. Consistent our third hypothesis (H3) the argument is that countries with more favourable conditions for childbearing also bring about higher levels of happiness. To do so, we regress happiness on the explanatory variables including interaction terms obtained by clustering countries into welfare regimes. The groups are (1) Conservative: Austria, Belgium, France, Germany, Switzerland, (2) Former socialist: Bulgaria, Latvia, Poland, Slovenia and Table 3 Being parents in different European countries Model 1: Men b

Model 2: Women SE

b

SE

Age

-0.117***

0.016

-0.052***

0.019

Age squared

0.014***

0.002

0.005

0.003

At least one child

0.068**

0.034

0.214***

0.050

Currently in a partnership

0.438***

0.029

0.346***

0.039

Working

0.358***

0.040

0.075***

0.025


0.061***

0.014

0.067***

0.008

Years of education

0.009

0.012

0.015***

0.005

At least one child 9 MEDITERRANEAN

-0.040

0.032

-0.076

0.051

at least one child 9 CONSERVATIVE

-0.148***

0.022

-0.136***

0.048

at least one child 9 LIBERAL

-0.097***

0.030

-0.110**

0.051

at least one child 9 EASTERN

-0.123**

0.048

-0.343***

0.060

Pseudo R-squared

0.0314

0.0242


6,835

7,584

Source Own computations using the ESS (3rd round) and happiness as the dependent variable. ‘‘Age squared’’ and ‘‘Annual Household Income’’ have been divided by 10 and 1,000, respectively. Models includes group country dummies and the social democratic group is the baseline. Data has been weighted using population weights *** p \ 0.01; ** p \ 0.05; * p \ 0.1

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Slovakia, (3) Liberal: United Kingdom and Ireland, (4) Mediterranean: Portugal and Spain, and (5) Social Democratic: Denmark, Netherlands, Finland, Norway and Sweden. The classification of countries into groups resembles the one described in Sect. 3, but also presents a few differences. The Netherlands is included with the social democratic countries (due to their generous social support systems) and an additional category is defined in order to incorporate Eastern and Central European countries. The interaction terms are consequently constructed by multiplying the dummy for each country group by the variable indicating whether the respondent has at least one child. In other words, the interaction term captures the effect of having none or at least one child in a specific group of countries. In the first and second specifications, we separate out men and women, respectively. The reference category in our regressions is the social democratic group. Results presented in Table 3 reveal that, on average, mothers and fathers living in conservative, liberal, and East European countries all appear to be worse-off than parents living in the social democratic countries. Perhaps not surprisingly, the divide between the coefficients of ‘‘at least one child’’ and the coefficients of the interaction terms is larger for women than for men. This suggests that the association between happiness and childbearing is more subject to contextual factors for mother than for fathers.8 A reasonable explanation is that mothers are more likely to be affected by country specific institutional factors, such as labour market protection, maternity leave, and possibilities of doing parttime employment. Perhaps surprisingly, fathers and, particularly, mothers living in Mediterranean countries are not substantially worse off with respect to those living in northern countries. However, when computing the ‘‘net’’ association between happiness levels and being mothers in a particular group of countries (namely by subtracting from the coefficient attached to the variable ‘‘at least one child’’ (0.214) the coefficient associated to the interaction terms), only the East European cluster shows a coefficient substantially different from zero (-0.13).9 These results suggest that when looking at the association between happiness and childbearing from a comparative perspective, there is not a strong direct support of the standard welfare regime patterns. However, there are important gender differences. Whereas there is very little impact of welfare regimes on fathers’ level of happiness, the welfare pattern is more marked for mothers and, other things being equal, being mothers in social-democratic countries generally results in higher happiness levels compared to the rest of Europe. In terms of our third hypothesis (H3), we find rather clear evidence to suggest that happiness associated with childbearing is stronger in Scandinavian countries, whereas for the other country groups, the results are more mixed. We have seen that partnership status correlates strongly with happiness. Table 4 presents estimates where we consider jointly the association of partnership and childbearing on respondent’s happiness, thereby investigating the fourth hypothesis (H4) in more depth. We construct an interaction term between current partnership status and the childbearing variable ‘‘at least one child’’. From this specification, we are able to assess to what extent being in a partnership enhances the happiness from having children (Kohler et al. 2005). In contrast with Kohler et al., who argued that the utility gains from partnerships do not interact with the presence of children in the Danish context, Table 4 shows a rather strong interaction effect 8

As the Social Democratic group is the reference category, the coefficient of at least one child becomes the average effect of having a child in that group of countries. Including the interaction term one can observe the effect of having a child in another group of countries with respect to Social Democratic.

9

To determine the ‘‘net’’ effect one subtracts the interaction coefficient from the average (i.e. the coefficient of at least one child) to get the association between happiness and having at least one child in a particular group of countries.

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Table 4 Partnership and childbearing for men and women Model 1: Men b

Model 2: Women SE

b

SE

Age

-0.106***

0.017

-0.051***

0.018

Age squared

0.012***

0.003

0.005

0.003

At least one child

-0.282***

0.055

-0.026

0.064


0.293***

0.037

0.235***

0.054

Partnership 9 at least one child

0.366***

0.061

0.191**

0.087


0.054***

0.014

0.059***

0.008

Working

0.353***

0.040

0.080***

0.023

Years of education

0.008

0.012

0.012***

0.004

Pseudo R-squared

0.037

0.030


6,835

7,584

Source Own computations using the ESS (3rd round) and happiness as the dependent variable. ‘‘Age squared’’ and ‘‘Annual Household Income’’ have been divided by 10 and 1,000, respectively. Models include country dummies. Data has been weighted using population weights *** p \ 0.01; ** p \ 0.05; * p \ 0.1

between partnership and childbearing. The coefficients are positive, 0.366 and 0.191 for men and women, respectively, and significant at the 1 and 5% level. The ‘‘net’’ association between happiness and childbearing while being in a partnership is positive for both genders. Hence, being simultaneously in a partnership and having children is positively and significantly associated with declared happiness levels for both men and women. Obviously, the reverse occurs when the respondent is currently not living with a partner. Interestingly, the coefficient associated to the childbearing status ‘‘at least one child’’ is negative and significant at the 1% level for men while it remains positive, but not significant, for women. This suggests that the happiness of both mothers and fathers depends to a large extent on partnership status, but in particular for men as single fatherhood status is negatively associated with happiness. These result clearly points to the fact that partnership and childbearing are strongly interrelated. The interconnection can be seen from two different opposing and complementary points of views: having children increases the gains derived from partnership or raising children while being in a partnership strengthen the association between happiness and childbearing. Whether these results capture the economic burden, the psychological distress, the negative feelings associated with the loss of a partner and the strain of having to raise children alone (or a combination of all these factors) cannot be inferred from our estimates. Finally, in Table 5 we consider the last two hypotheses (H5 and H6) by analysing the interaction between number of children with the annual household income and the working status of the respondent. The analysis is again carried out separately for men and women in order to investigate whether there exist specific gender patterns in terms of family, work and happiness, the idea being that work and income in combination with children, may alter individuals’ happiness. Model 1 includes a new interaction term, obtained by multiplying the variable ‘‘working’’ (binary variable taking the value 1 if the respondent is currently employed) and the number of children the respondent declares to have at the time of the interview. Model 2 assesses whether there exist any correlation between happiness and household income levels interacted with the number of children. Model 1 shows that those fathers who are currently working appear better off with large offspring compared to those who do not work. On the contrary, but not surprisingly,

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Table 5 Work, income and childbearing Model 1: Working and childbearing

Model 2: Income and childbearing

b

b

SE

SE

Men Age

-0.116***

0.016

-0.117***

0.016

Age squared

0.013***

0.002

0.013***

0.002

Number of children

-0.008

0.018

0.015

0.027


0.401***

0.034

0.404***

0.034

Working

0.307***

0.042

0.354***

0.039


0.054***

0.014

0.049***

0.014

Years of education

0.010

0.012

0.009

0.012

Work 9 number of children

0.048**

0.023 0.004

0.005

Income 9 number of children Pseudo R-squared

0.0362

0.0361


6,835

7,584

Women Age

-0.049**

0.021

-0.047**

0.020

Age squared

0.004

0.003

0.004

0.003

Number of children

0.024

0.030

-0.026

0.029


0.361***

0.038

0.362***

0.042

Working

0.092

0.068

0.078***

0.025


0.060***

0.008

0.039**

0.016

Years of education

0.012***

0.004

0.011***

0.004

Work 9 number of children

-0.011

0.040 0.015*

0.010

Income 9 number of children Pseudo R-squared

0.0283

0.0295


6,835

7,584

Source Own computations using the ESS (3rd round) and happiness as the dependent variable. ‘‘Age squared’’ and ‘‘Annual Household Income’’ have been divided by 10 and 1,000, respectively. Models include country dummies. Data has been weighted using population weights *** p \ 0.01, ** p \ 0.05, * p \ 0.1

reconciling work with a large family is negatively associated with happiness for women, but the coefficient is not significant. The interaction between working and childbearing status for women could be affected by the fact that those women who find it particularly hard to reconcile work and care (resulting in lower happiness levels) may simply opt out of the labour market. Model 2, on the other hand, shows that the interaction between household income and the number of children is not significantly associated with men’s happiness. Conversely, the interaction term is positive and significant for women, but the magnitude of the coefficient and the significance level prevent us from making strong conclusions. Having a larger family while enjoying higher income levels is (marginally) positively associated with women’s happiness. There may be several good explanations for this final set of results. For instance, enjoying good living standards and having a large family may allow a mother to satisfy both her fertility preferences and professional aspirations, since higher income levels may mean higher purchasing powers in so far childcare services are concerned.

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6 Conclusion Do children make us happy? In light of recent declines in fertility patterns in Europe one could certainly be tempted to argue that children play a less important role in individuals’ lives. Given the rise of individualization and self-realization (as put forward of the Second Demographic Transitions thesis), children might be perceived more of a burden than what they have been in the past. Children bring about a substantial financial cost to a household, and in terms of measuring well-being, relying on income or consumptions expenditure—as is often done in economic analysis, might give a distorted picture. Our analysis shows that there is a general positive and significant association between subjective levels of happiness and parenting, albeit modest in magnitude and depending on the way childbearing is measured. Our results are in line with those of Kohler et al. (2005). Parents are happier than non-parents, given that, even after controlling for individual and country characteristics, coefficients generally stay positive and significant. When we regress happiness on the number of children together with the binary indicator indicating parenthood, the association between childbearing is positive and significant for men only. At the same time, we find that being a mother (regardless of parity) is positively associated with declared happiness levels. Additional children, after the first born, do not increase mothers’’ subjective well-being while they increase fathers’ subjective well-being. However, childbearing is not associated with higher happiness everywhere and for everyone. It appears, for instance, that being in a partnership is an important precondition for enjoying higher level of happiness from children for both fathers and mothers. An important contribution of our paper is that we are able to assess the relationship between parenting and happiness across different welfare regimes across European countries. Whereas father’s happiness does not seem to vary much by welfare regimes, it does so for mothers, and not surprisingly, mothers are happiest in the Nordic countries. That said, the standard Esping-Andersen welfare regime classification does not appear appropriate in this setting. For instance, the difference in mothers’ happiness in Social Democratic countries is not very different from that of mothers in Mediterranean countries. This is of course interesting in the sense that these countries were originally taken as opposing poles in the Second Demographic Transitions thesis. Whereas those groups of countries may differ in terms of family attitudes and individualisation, these factors do not appear to matter when, ceteris paribus, considering the perceived happiness associated with childbearing. Mothers living in East European countries are those particularly disadvantaged in terms of happiness. As we know, these countries have experienced dramatic societal upheavals over the last two decades, which, of course, were followed by a decline in real incomes and increased uncertainty in the labour markets. It is not surprising that motherhood has become more challenging in these countries, which may of course, be reflected in those rather dramatic fertility declines that we have observed. We also find lower levels of happiness in the Liberal countries, here spearheaded by the UK. The effect here is possibly driven by lack of welfare provision, especially for mothers, and lack of close family ties. The fact that mothers appear to be more strongly affected by country of residence is somehow also reflected by the preliminary analyses presented in the work by Billari and Kohler (2009). Their results seem to confirm the macro-level hypothesis that predicted happiness is positively associated with institutional and cultural factors that favour fertility and more precisely the compatibility between work and motherhood. We find a very strong interconnection between happiness, partnership and childbearing. Through the interactions we are able to estimate a separate association between happiness

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and childbearing for those who are currently in a partnership and those who are not living with a partner. Being simultaneously in a partnership and having children clearly results in higher happiness; conversely having children while being single corresponds to a more disadvantaged situation especially for fathers. Whether this is the result of the fact that having children increases the happiness a couple derives from partnership or its mirror image, namely that raising children without a partner lowers the happiness derived from childbearing, cannot be clarified with our data. Finally, we find that working status and household income interacted with childbearing are strongly associated with mother’s happiness. Having a large family while working is associated with less happiness for mothers, while the opposite is true for men. This result highlights the difficulty many women have in combining family and working careers. Conversely, enjoying higher standard of living and having a large family is generally correlated with higher happiness for mothers. This final set of results reinforces the impression of an important gender gap in parenting and happiness. As posited by Umberson et al. (2010), although some studies reveal that parenting stress is greater for some groups than others, a solid understanding of the various mechanisms through which parenting affects well-being is still missing. Certain groups of the population will perceive the cost of parenting in different ways depending on their SES status, social support, gender and country of residence on top of preferences and attitudes. The intention of our paper is clearly to contribute to this line of research by showing how the association between happiness and childbearing varies according to individuals’ characteristics and contextual factors. As stressed throughout the paper, we do so with some important limitations. One cannot easily generalize our results due to the basic cross-sectional nature of our analysis. There are obvious selection issues here, that we are not able to deal with, which are likely to influence both declared happiness, childbearing status and control variables. Whereas our study provides insight into an issue not much studied in Demography, it also opens many research avenues for the future. The primary one is a clear need to consider the relationship between childbearing and happiness in a longitudinal perspective. By measuring happiness before and after childbearing events, one is coming closer to the core of the research question: are children making us happier? And, to what extent does this vary across settings? Similarly, it is of interest to understand how individuals and couples predict their level of happiness prior to childbearing, for them to measure their realised levels. Some of these questions can be looked upon with the help of long running longitudinal surveys, such as the British Household Panel Survey or the German Socio Economic Panel. Finally, an important expansion would be to bring together the longitudinal perspective with the comparative one. Acknowledgments We are grateful to Andrew Oswald, Andrew Clark, Cristina Ruggeri and Jane Klobas for very useful comments to this analysis. Financial support from the ERC, Starting Grant No. Stg 201194 (Consequences of Demographic Change), is gratefully acknowledged.

Appendix Appendix 1

AT BE

Austria Belgium

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84

BG CH DE DK ES FI FR IE LV NL NO PL PT SE SI SK UK

A. Aassve et al.

Bulgaria Switzerland Germany Denmark Spain Finland France Ireland Latvia Netherlands Norway Poland Portugal Sweden Slovenia Slovakia United Kingdom

Appendix 2 See Table 6 below.

Table 6 Differences in the level of happiness across Europe

Source Own computation based on ESS data (3rd round) and happiness as dependent variable. Denmark is the reference country * p B 0.10, ** p B 0.05, *** pB 0.01

123

b

SE

AT

-0.506***

0.012

BE

-0.405***

0.011

BG

-1.461***

0.032

CH

-0.127***

0.003

DE

-0.756***

0.018

ES

-0.343***

0.010

FI

-0.120***

0.003

FR

-0.638***

0.016

UK

-0.601***

0.015

IE

-0.478***

0.012

LV

-1.035***

0.025

NL

-0.443***

0.013

NO

-0.245***

0.006

PL

-0.707***

0.017

PT

-0.953***

0.025

SE

-0.260***

0.007

SI

-0.434***

0.011

SK

-0.932***

0.023


85

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