A Cross-Country Investigation of the Determinants of the Happiness Gender Gap

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A Cross-Country Investigation of the Determinantsof the Happiness Gender Gap

Sabrina Vieira Lima∗

June 6, 2011

Abstract

This paper investigates the existence and determinants of the happinessgender gap across countries, using a large sample of individuals of around 80countries, built with data from World Values Survey, World Development In-dicators and CIRI Human Rights. We examine the role of rights, achievementand beliefs for female gender, in economical, political and social context. Wefind that women are happier than men in most African and many developingcountries, and less happy in around 15 European and other industrialized coun-tries. Overall, the results indicate that women happiness have a paradoxicalcomponent, where better objective conditions do not grant them happiness.

Keywords : Subjective well-being, happiness gender gap, women’s rights.

∗PhD student at University of Milan-Bicocca, Economics Department, Piazza dell’Ateneo Nuovo1, 20126 Milan, Italy. Telephone: #39 2 6448 3052. E-mail: [email protected]

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1 Introduction

In the last two decades, major developments of the neurosciences provided valuableinformation about differences on male and female brain. This evidence yields newbiological support for the conventional belief that men and women are different, bothfor cognitive processes and behavioural outcomes. This also shapes different pathsof social interactions, and, as such, the entire social process might also result in adifferent gender happiness path.

On the literature of Economics and Happiness, gender is considered generally asa socio-demographic control variable. Few authors have given a bit closer attentionto this topic along the way (Easterlin, 2003; Blanchflower and Oswald, 2004; Marcelliand Easterlin, 2005; Bjrnskov et al., 2007; Plagnol and Easterlin, 2008; Stevensonand Wolfers, 2008, 2009; Guven et al, 2009), while the latest contributions focusedmostly in the work and leisure spheres1 (see, for example, Berger, 2009; Gash et al.,

2010; Gimenez-Nadal and Sevilla-Sanz, 2010; Trzcinski and Holst, 2010). To ourknowledge, little has been done to frame the study in more encompassing terms, orin a worldwide perspective. A first contribution of our paper is an attempt to fillthis gap of the literature.

Moreover, evidences so far show that on average the two genders do not sharethe same subjective levels of happiness; but there is no consensus on who is thehappiest (see, for example, Bjrnskov et al., 2007; Blanchflower and Oswald, 2004).Nonetheless, the works of Stevenson and Wolfers2 (2008, 2009) and Plagnol andEasterlin (2008), respectively, indicate shifts in the happiness gender gap: fromfavouring women to favouring men, or disfavouring women later in life. Followingthis state of art, we do not form a specific hypothesis on who is the happiest. However,

it was women’s life that historically suffered major changes in economic, political andsocial spheres. Therefore we want to investigate these aspects. They are noticeableinstances where women conquered a right that previously were exclusively of maledomain (the right to work, to vote and engage in social activities outside the familycontext). Moreover, regardless any (feminist) theory or efforts for gender equality,to this day women’s life is subjected to important social changes, which impactnaturally both genders3.

1An exception (both methodological and thematically) is the work on fertility of Pakaluk andBurke (2010), which investigates whether changes in the contraceptive technology may have nega-tively impacted female happiness.

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Stevenson and Wolfers’ (2009) paper is noteworthy since, using different sources of data andmeasures of subjective well-being for the USA and 12 European countries, they show that femalehappiness has declined absolutely and relative to male’s over the past 35 years.

3Some recent news (from small to front page articles) can help to illustrate it. See, for example,



Another important contribution of our paper is its test of the women’s rightscontribution to the happiness gender gap, besides assessing the role of institutionalvariables. A noteworthy approach to the issue of reaching a good life (or human

flourishing), which gives a particular attention to the female context, was developedby Martha Nussbaum (Nussbaum and Glover, 1995 (eds); Nussbaum, 1993, 2000,2001). In particular, Nussbaum (1995a) departs from evidence that no country in theworld treats women as well as men, in different respects: longevity, health, education,employment, political participation. Like Sen, she argues that an adequate theoryof gender (and social) justice is possible if we take into consideration individualfundamental entitlements. She defends that the best approach to this end is tocenter in the human capabilities, which means to focus in what people are effectivelyable to do and to be. She argues that it is necessary to guarantee to the each personthe material and social conditions that make possible for each one to opt for whatone thinks is the best for him/herself. Alongside these conditions, she understands

that the internal capabilities of persons should be (institutionally) promoted. Thisis equivalent of saying that is not only the objective conditions that matters butalso the internal perception of what one can do or be in his life. At this point thegovernment role would be to help its citizens to pursue their internal capabilities aswell as the necessary resources and social conditions to act in the way they choose forthemselves. Therefore, Nussbaum’s theoretical work confirms our hypothesis thatinstitutions, achievements and the system of beliefs that surrounds one’s contextwould be of valuable role to people’s well-being.

In what regards institutions, the literature of gender and happiness has not muchspecifically explored their role4. Institutions though, have been shown to play animportant role on individual subjective well-being. A seminal contribution in thisdirection was given by Frey and Stutzer (2000a, 2000b, 2002). Although not focusingin gender aspects, their work provides us with empirical evidence that shows theimportance of democracy to individual well-being. They find that the greater thedegree of democracy, the happier the citizens are. We try to capture these sourcesof happiness to the gender context by using variables of female political rights.

Other contributions consider the varying impact of civil rights on happiness.Veenhoven (2000), for instance, provides intriguing results when exploring the role

on The Economist: Gendercide The worldwide war on baby girls (March, 2010); What happenswhen women are over half the workforce (January, 2010). On The New York Times: The Stigmaof Being a Housewife (July, 2010); Italian Women Rise Up (August, 2009). They talk about

homicide and gender preference in millenary cultures; female work and criticism to the feminism;the controversies of being housewife in the XXI century; sexism in modern, democratic Europe.

4The work of Bjornsvok et al (2007) is an exception. They account also for institution whenincorporating indicators of women rights as a measure of discrimination.

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of freedom in subjective well-being of 46 nations. He finds that freedom is notalways positively related to happiness: it contributes positively to happiness in richcountries, but not in poor ones. On the contrary, he uncovers that economic freedom

is positively related to happiness in poor countries but not in rich ones. Similarly,we try to test these relations in a gender context, using measures of female economicand social rights.

Within this background we form our hypothesis that rights, achievements andbeliefs may respond for the happiness gender gap across countries. We measure itby variables of female rights, female actual achievements and on the national beliefs’environment, all captured in economic, political and social terms.

For the purpose of this study we apply an empirical strategy similar to Stanca’s(2010) methodology. It consists on first, determining the subjective well-being atindividual level; and second, using macro level conditions to explain the differenceson the variable-matter (in our case, differences in gender premium on happiness)

across countries. For the first stage we use data from the World Values Survey(WVS), which contemplates 94 countries, from 1980 to 2008, divided in five waves.For the indicators of macro conditions we use additionally two other sources: WorldDevelopment Indicators (WDI) and Cingranelli-Richards (CIRI) Human Rights dataset.

This work contributes to the literature mainly in three ways. First, it helps todeepen the scanty literature on gender and happiness based in a methodology5 so farunused for gender issues; second, it introduces and tests institutions (understood asfemale economic, politic and social rights) as determinants of the gender happinessgap; third, it investigates the happiness gender gap in an encompassing way, bytaking into account women’s life as a whole instead of focusing in single aspects, asfor example age and work. We pursue the following questions: 1) is there a happinessgender gap at all? and 2) what factors explain it across countries?

The paper is structured as follows: sections 2 and 3 present the methodologyand the data used for the empirical analysis, respectively; the results are presentedin section 4; section 5 concludes with a discussion of the main implications of the

5We highlight the contribution of this method in at least two ways: it permits to control forgender invariants, and allows the right variance for the country level explanatory variables, whichenhances its explanatory power comparing to other methods. In studies that put together in thesame regression equation individual and country level variables (as, for example, Bjornskov et al,2007), the country level variables have minor variance with respect to the individual levels (especiallythe dependent variable), what would, probably, transform some explanatory variables into controls.In our work (as can be seen in the following section), we start at individual level and then, in asecond stage, we move to country level; and in this case, the explanatory country level variablesare indeed explanatory.

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analysis.

2 Methods

We apply an empirical strategy similar to Stanca’s (2010) methodology6. It is com-posed of two empirical steps. In the first, we are interested on performing subjectivewell-being equations at individual level for a large range of countries globally. Atthis stage, the effect of gender on subjective well-being is estimated for each countrysingly. They consist on conditional estimations as we control for a set of factors (eco-nomic (ECO), social (SOC), regional (REG) and demographic (DEMO) aspects) thatis considered in the current literature to influence individual happiness7. In the sec-ond step, we are interested on estimating the happiness gender gap across countries.The dependent variable now are the effects of gender on subjective well-being (from

the first step). This analysis is done taking into account as explanatory variables aset of macroeconomic, institutional and social conditions at country level.The individual level equations (in the first step), where we estimate the effect of

gender on individual well-being, is given by:

SW Bij = α +β 1 jGEN ij +β 2 jEC Oij +β 3 jSOC ij +β 4 jDEMOij +β 5 jREGij +εij (1)

where WBij is the well-being of individual i in country j and GEN standsfor gender, that is set to capture the effects for females. Subjective well-being isproxied by a life satisfaction variable, which is measured in a scale from 1 to 10.For this reason we chose to use ordered probit model, to properly account for thecardinal nature of the dependent variable. The variables that account for economicconditions are income and unemployment; social factors are given by the degreeof education, marital status and a subjective perception of freedom; age and genderform the demographic variables (although we preferred to isolate gender in the aboveequation to emphasize its role in our study); national regional aspects were includedas a measure to capture individual external environment.

In the second step, the effect of gender on determining the individual happiness,is assumed to depend linearly on macroeconomic, institutional and social conditions,

6In a step further his work contemplates spatial patterns to capture the effects of economicconditions on happiness, while here we are interested only in the country level effects themselves

on gender.7Present in a variety of research themes, for instance Blanchflower e Oswald (2000), Alesina et

al. (2001), Wolfers (2003), Frey e Stutzer (2004), Di Tella and MacCulloch (2006). Blanchflower(2008), Clark et al (2008).

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put in terms of female rights (RIGH) achievements (ACHI) and beliefs (BEL). Thecountry level equation is given by:

GAP j = α + β 1RIGH j + β 2ACHI j + β 3BEL j + ε j (2)

where GAP j is the gender gap for country j .

In order to estimate equation (2), the gender gap is proxied by the β̂ 1 j of gen-der from equation (1). In other words, our dependent variable, gender gap, is theestimated coefficient of gender in equation (1), and is estimated by OLS (in step 2).The set of rights contemplates women economic, political and social rights; achieve-ments accounts for women outcomes in the society and include female labor forceparticipation, number of seats of women in parliament, school attainment and lifeexpectancy ratios (women/men), and fertility rate; values (or beliefs) of the countriesare captured by a set of assertives.

In the following section, we detail the data sources and variable definitions.

3 Data

In this study we use three data sources: the World Values Survey (WVS), the WorldDevelopment Indicators (WDI), and the Cingranelli-Richards (CIRI) Human Rightsdata. They are used jointly in the second step. For the individual level, in the firststep, we use only the WVS data. These data provide us sources to asses the impactof female rights, achievements and values to explaining the happiness gender gap.

The World Values Survey is an association that promotes worldwide surveysabout socio-cultural and political change, including values, beliefs, economic andenvironmental aspects. It contemplates 94 countries8, from 1981 to 2008, divided intofive waves (1981-1984, 1989-1993, 1994-1999, 1999-2004, 2005-2008). The countriesinvestigated were not the same in all the waves9. The first wave contemplates 20

8Up to the fourth wave it had investigated over 80 independent countries which covers around85% of the global population.

9More specifically, a country belonging to a certain wave is surveyed within a given year amongthe years corresponding to that wave. The time span of each wave implies that those were the yearswhere the survey was started and concluded for a group of countries (e.g.: Albania and Venezuelawere surveyed in the third wave (1994-1999); Albania in the year 1998 and Venezuela in 1996). Forthe terms in comma and further details, please see Inglehart (2000).

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countries, the second 43, the third 55, the fourth 71, and the fifth 57, totalizingaround 257,000 observations.

We use life satisfaction information to proxy the individual subjective well-being.

It is measured in a scale of integer values from 1 to 10, being 1 the most dissatisfiedand 10 the most satisfied, as the answer for the question: All things considered,how satisfied are you with your life as a whole these days?. The income variableis obtained in a scale from 1 to 10, where these boundaries work as references forindividual subjective perception of his personal position in the countries’ distributionof income; they are not expressed in monetary terms, so that they are comparablebetween countries. Unemployment is a dummy variable from the employment statusthat includes the options retired, student, housewife, part-time, full-time and self-employment. We work with three levels of education - low, medium and high. Ourmeasure of trust consists in a dummy variable assuming the value equal to 1 forthose who think that in general people can be trusted”, or 0 if the person cannot

be too careful when dealing with people”10

. Table 2 provides summary statistics forthe variables used in the individual level analysis, in the first step.

The first dataset in the country-level analysis is the CIRI Human Rights. Thisis a widely used database by political economists and other social scientists. Itsadvantage is that their evaluation distinguishes the human rights polices from itspractices11. This is worthy of notice, since usually there is a difference on whatgovernments say they are going to do and what they actually put in practice. Thisalso converges to what we want to focus on: objective indicators of the degree of rights women effectively enjoy in each country. The CIRI database uses as source of its information the annual United States Department of State’s Country Reports onHuman Rights Practices, and the Amnesty International’s Annual Report12. Theyconsider physical integrity rights, civil liberties, worker’s rights and women’s rightsto equal treatment, for 200 countries in a time span that varies from 1981 to 2007.

From this database we use the following three variables: women’s economic rights,

10For the terms in comma and further details, please see Inglehart (2000).11For practices it is understood all the government human rights-related actions. By government

it is included any and all of its agents, such as police and paramilitary forces (Cingranelli andRichards, 2008). Since they consider only practices, human rights conditions are not accountedfor. Conditions would enclose all that can be happening within a country besides the government’saction, such as guerrilla groups. Although it seems that conditions would be more informativethan practices, practices give very reliable information, since it transcends the policies showing theenforcement (or not) of the laws.

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In case of disagreements among the reports, the Amnesty International report is taken asauthoritative, in order to avoid any US American bias. (Despite that it is highlight that the tworeports joy of high accordance please, see Poe et al (2001).

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women’s political rights, women’s social rights13. They account for a series of inter-nationally recognized rights. Each variable assume a value that ranges from 0 to 3,where 0 is assigned if there is none of the (specific) right for women in law and that

sex discrimination might have been brought into law; 1 if women have some rightsunder law but not effectively enforced; 2 if women grant of some rights under laweffectively enforced allowing low level of discrimination; and 3 if women have all oralmost all rights under law, fully enforced in practice. Additionally, we created afourth variable which is an average of these three, called simply women’s rights. Inour work the three of them are not treated categorically (by dummies), but as themean of each variable for all the years corresponding to a given country (the samefor women’s rights variable). The expected sign for their coefficient is positive, sincethey reflect provision of means women have to be equal to men in economic, politi-cal and social lives, and we assume that this can impact positively the happiness of women.

The other source of data is the World Development Indicators, provided by theWorld bank, with data for 234 countries, covering the period 1960 to 200914. This isour source of female achievement (or outcome) in the society. As Nolen-Hoeksemaand Rusting (1999, p. 341) affirm, inequities of power leave women feeling helplessand devalued and contribute to their higher rates of internalizing disorders, thereforewe expect that their achievement in the society would contribute to enhance femalehappiness. We use five variables to capture this achievement. The first is femalelabor force participation, which is the female percentage of the total labor force.The second is the percentage of seats held by women in national parliaments. Thethird is a ratio of the educational gender gap, that serves as the female achievementin educational terms with respect to male; it is given by the ratio of girls to boys inprimary and secondary education. The fourth is the life expectancy ratio, used as aproxy for the female health outcome in comparison to male’s; the WDI provides uswith the life expectancy at birth (in number of years) for females and males, that

13Women’s economic rights goes from the right to equal pay for equal work, to job security,right to work or exercise a profession without male’s consent, and to be free of sexual harassment.Women’s political rights accounts for right to vote, to run for political office, join political partiesamong others. Women’s social rights consider right to inheritance, enter marriage in equality withmen, participate in socio-cultural and community events, freedom from genital mutilation (seeCingranelli and Richards, 2008c).

14For the WDI, as for CIRI data, the number of observations and the time series perspectiveare disadvantaged since the informations are not available equally to all the countries within all

the years. The further junction of the three data sources constrained us to use the informationas long-run averages (for the maximum time span available in each case), which, nonetheless, is aprocedure used in the literature.

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permits us to constructing the ratio of female to male life expectancy at birth. Thefifth variable (that can be interpreted by a control) is the fertility rate, given by thenational number of births given by women15.

All these variables were averaged out in the available period and the percentagerates were transformed in decimals. For all of them we expect positive coefficients aswe assume that they enhance women’s feeling of participation in the social/nationallife and as so would help to increase their happiness within a country.

Lastly, we select a set of variables that can serve as a proxy for the system of beliefs women face within each country. We use WVS data for the two genders,averaging it out to transform the data from individual to national levels. They areobtained in base on statements for which individuals are asked to express agreementor disagreement choosing from an ordering that indicates 1 for strongly agreement,up to 4 strongly disagreement. We rescaled these variables so then they express anagreement ordering16. The statements are: when jobs are scarce, men should have

more right to job than women; men make better political leaders than women do;university education is more important for a boy than for a girl; being a housewifeis just as fulfilling as working for pay. We assume that the disagreement to thesebeliefs would enhance women happiness17.

Table 3 provides summary statistics to all the variables used in the macro levelanalysis.

15Fertility indicators are the core of development economics and demography, and it may alsowork as a synthetic measure of women status within a society, since fertility choices are correlatedwith several domains (women’s role in the family, labour force participation etc.). It is importantto recall also that one of the reasons women quit job and give up their career is exactly due tomotherhood. If having and bearing children would not be important to women’s satisfaction this

trade off would not be made elsewhere (even with different degrees across women and countries).Hence fertility may be a proxy for women’s achievement on being able to express their maternity(specially in the countries were female work is more noticed). Our hypotheses is that higher levelsof national fertility is positively related to female happiness.

16All these variables were rescaled to express an agreement ordering, varying now from -1 (agreestrongly) to -4 (strongly disagree). Exception for one variable which have only a binary response(agree or disagree) when jobs are scarce, men should have more right to job than women.

17With respect to the statement being a housewife is just as fulfilling as working for pay weare a bit dubious on its effect. If it is understand as a discriminatory belief that would prevent ordiscourage women from working despite their personal will, then a disagreement with this statementwould contribute to female happiness. But, if it can be understood as a belief that is supportiveto women’s choice of working or not, than a disagreement could represent a decrease in femalehappiness. So, we depart somehow neutral regarding this variable.

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4 Results

The results of the estimation of equation (1) for the individual level are shown in table4. To synthesize them, the variables that provide a strong and significant impacton subjective well-being (at the 1% significance level) are income, unemployment,gender, education, married status, freedom and trust. The increase of one decile inthe income scale represents a strongly significant increment in life satisfaction (0.07).In the opposite direction, being unemployed has a wide strong negative significantimpact on subjective well-being (-0.19). Education (middle and high education,compared to lower levels) has a positive effect on individual life satisfaction (0.04 and0.03 respectively). With respect to singles, being married reveals a strong positiveeffect to individual well-being (0.10). Self perception of freedom (0.16) and trust(0.10) are also positive and strongly significant to individual life satisfaction. Lastly,compared to females, males are less happy, presenting negative significant coefficient

(-0.03).

4.1 The happiness gender gap

Analysing the estimate of equation (1) we can answer our first question, affirmingthat indeed there is a global happiness gender gap and that it favours women. Thisresult is shown in detail in Table 1, that presents for the country specific regressionsthe estimated coefficients of being female on life satisfaction. They range from -3.57 for Trinidad e Tobago, to 8.41 to Tanzania. Out of 94 countries, 59 (almost63%) present a positive gap (favouring women) and 35 (37%) show a negative gap(favouring men).

Surprisingly, the first five countries in the ranking are Tanzania, Uganda, Algeria,Zimbabwe and Jordan, which are developing countries where women’s rights are notwell developed18. This is the pattern that the majority of the continent follows - theexception is Rwanda whose happiness gap does not favour women (-0.74).

On the other edge of the ranking, were women are less happy than men, wecannot verify a particular pattern of any continent; instead, countries of all sortsof socio-economic and geographic characteristics are represented: Singapore (-0.01),Burkina Faso (-0.30), Norway (-0.40), Israel (-0.95), Portugal (-1.23), South Korea

18Indeed, using the CIRI Human Rights data, we calculated the women rights syntactic indicatorfor these countries (that consists on an average of the three CIRI indicators for economic, political

and social rights see section 3), which are: 1.27 for Tanzania, 0.97 for Uganda, 0.91 for Algeria,1.24 for Zimbabwe, and 0.89 for Jordan (in a scale from 0 to 3, where the closer the country scoreis to zero, lower level of rights women have, and the closer to 3, higher level of rights women have).

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(-1.51), Brazil (-2.67), among others. Nonetheless, interestingly there is a consid-erable representation of developed countries such as Japan (-0.04), United States(-0.28) and 14 European countries (including Switzerland (-0.31), Luxembourg (-

0.36), Austria (-0.39) and Italy (-0.47)), although the majority of these countriespresent low happiness gender gap, given their small coefficients.

4.2 The determinants

We now turn to the country level estimates, analysing the potential determinants of the gender gap. Tables 5 to 8 show the results of estimating the effects of aggregateconditions on the happiness gender gap. We recall from section 2 that our dependentvariable, the happiness gender gap, is the estimated coefficient of the gender dummyfeaturing in equation (1) (that measures the country-specific sensitivity of happinessto the female gender with respect to male).

The main results obtained were initially suspicious. Differently from our initialhypotheses, some variables of women achievement and rights presented negative sig-nificant coefficients (female labor force participation and three out of four measuresof women rights). In the same way, two variables that account for social beliefs areinstead surprisingly related to the gender premium in a positive way (they are: when

jobs are scarce, men should have more right to job than women and men make betterpolitical leaders than women do). These paradoxical results will be discussed now indetail.

Table 5 provides the results of regressing the gender gap on women’s rights vari-ables. Contrary to our hypothesis, women’s economic rights are not significant toexplain the happiness gender gap. This result is very intriguing. In the introduction,we affirmed that one of the aspects for which women’s life suffered a major changewas, indeed, the economic sphere. It is one of the first instances where women con-quered a right that previously were exclusively of male domain. The three othermeasures of rights possess a significant negative impact. We offer some possibleexplanation for these facts in the sequence.

The effect of women’s political rights is stronger. An increment of one percentagepoint in political rights19 represents a decrease of 0.48 percentage points on the hap-piness gender gap, whereas the effect of women’s social rights and of the syntheticindicator of women’s rights are respectively, a decrease of 0.22 and 0.33 percentagepoints. These results are significant only if the happiness gender gap is regressed un-

conditionally on the female rights. Their estimated impact, in fact, is not maintained19The original discrete variables of women rights have been rendered continuous once averaged

across the years.

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when we add the variables of achievement and beliefs (table 8).The results for the effect of achievement on the happiness gender gap are reported

in Table 6. Except for female labor force participation (FLFP) and fertility rate, the

other variables are not statistically significant. FLFP has a strong and significantnegative effect on women’s well-being; an increase of one percentage point reduceswomen’s happiness of 3.38 percentage points. Also when regressing conditionallyon all achievement variables, FLFP marginal effect remains strong and significant(equal to -3.22, column 6). This result is robust also in the specification where allthe variables of rights, achievements and beliefs are included (table 8).

Finally, the results for the analysis of the role of the national context of beliefson the happiness gender gap is reported in table 7. Among them, the ideas thatmen should have more right to job and that men make better political leaders aresignificant to explain the happiness gender gap. Surprisingly, they show that livingin a country where the social context is in favour of men’s job over that of women

provides significant positive marginal effect (1.12) on female life satisfaction. Al-though the significance and the absolute value are reduced, the variable men shouldhave more rights to job continues to be significant also in the regression conditionedto other belief variables (column 5); the variable men make better political leaders,this time, loses its significance.

When first thinking on what could explain the eventual difference on happinessamong men and women across the world, we focused on the female case, since it isthe gender which still suffers from inequalities in many domains, and the one thathad major changes in life-style in the past half century. Many of these changes werepromoting women’s rights and their effective achievements in the society. Nations,even if in different degrees, have decreased the gender discrimination in many fronts,specially in the developed and more industrialized countries (for recent years, seefor instance, the Gender Gap Index Reports, 2006 to 2010). Nonetheless, all theseadvantages seem to be not corroborated by our finding women’s happiness. Thisis the reason why Blanchflower and Oswald (2004) referred to this phenomenon asa paradoxical view, and why Stevenson and Wolfers (2009) coined the expressionthe paradox of (declining) female happiness20 . Our results show that most of thevariables that would hypothetically contribute to their happiness, instead seem toproduce a diminishing effect. This paradox needs further investigation and evokessome hypotheses for its existence. We highlight four possible explanations: (i) so-cial costs involved in the transition; (ii) self-perception of freedom/autonomy; (iii)

20Stevenson and Wolfers (2009) analysed women happiness along the time, and this is why theycan point a declining pattern. Our analysis do not account for the time domain, but still confirmsthe paradoxical issue of women happiness highlighted by these two works.

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relational crowding out effect; and (iv) rights-expectations treadmill effect.For hypotheses (i) and (ii) we recall Nussbaum’s work. The first, refers to the

intrinsic dynamic nature of the processes of (gender and) social change, highlighting

an alternative view of the role of social (hence women’s) rights and their impact onindividual happiness. For example, Nussbaum highlights that the conquest of higherrights involve conflicts and social tensions (what I refer to as social costs), whichmight eventually decrease the net benefit of acquiring them at least in the shortand medium run21. Following this line of reasoning, one could collect the subjectivebenefit of social activism only in the long run, perhaps after a generation and thisrequires a proper account of the time dimension of the underlying rights-happinessrelation, which is severely constrained by the predominant cross-sectional nature of our estimation exercise.

The second hypothesis suggests the importance of accounting for the self-perceptionof freedom/autonomy. Nussbaum argues that well-being depends on material and so-

cial conditions as well as on internal capabilities. Without these external conditionsand the internal capability it would not be possible to anyone to choose what to do orto be according to what each one considers valuable for himself. Our results seem toshow that an improvement in external materials and social conditions (representedby female rights and achievements in economic, political and social aspects) in real-ity produce a negative impact on female life satisfaction. Instead, it might simplymean that, without being accompanied by internal personal conditions, rights andachievements themselves are not sufficient to increase female happiness relative tomale’s. Therefore, we might be missing out the role of internal personal capabilities.This is an interesting issue to be further investigated. Indeed, Bavetta and Navarra(2011), show empirical evidence that the individual perception of own freedom orautonomy is complementary to the countrys economic freedom in enhancing one’swell-being.

The third hypothesis refers to the possibility of a relational crowding out effect,where the impact of higher rates of female achievement (we can focus on femalelabor force participation) might be offsetting the consumption of relational goods22

(Bruni and Stanca, 2008). The second shift theory (Hochschild and Machung, 1989),

21Easterlin (2009) provides empirical evidence on this respect. He shows that Eastern Europe’stransition from socialism to capitalism in the 1990’s was not followed instantaneously by an increasein life satisfaction. Instead, around 15 years later subjective well-being records were bellow pre-transition levels. More specifically, he argues that the increased satisfaction with material living

level occurred at the cost of satisfaction with work, health and family life.22Bruni and Stanca (2008) investigates the role of relational goods to individual happiness, findingnot only a significant relation, but also suggesting a relational treadmill, where the effect of higherincome on happiness would be offset by a lower consumption of relational goods.

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indeed, helps to point out this issue. The fact that women work outside home in themarket and then face a second shift at home, leaves little space to opportunities fora richer social life, entertainment or relaxing activities. Despite some evidence that

the time dedicated by men in home production is increasing (Blau, 1998), culturallyperhaps, home making is still womens role, will or responsibility. We should alsocomment that the strong significant and positive effect that when jobs are scarce,men should have more right to a job than women puts in evidence once again therelational character of female kind. Again, a possible explanation is that womenare able to give up something to the other gender if they judge this is important ornecessary, or that they prefer to balance out the professional life with other familiarand social relations, if they were given the choice.

The fourth hypothesis suggests the existence of a rights-expectations treadmill,that would follow in a certain way the income treadmill, which means that somebeneficial effect of rights can be offset by aspirations of more/better rights. Someone

who lives in a developed country, with her rights guaranteed by the democraticState, may feel tempted of judging insufficient what is already available23. Thisline of thinking can be also translated as the more you have, the more perfect youwant it to be, showing a not-satisfying pattern that intensifies as the consumptionof the rights grows. In the other side, there are many women in the world thatprobably do not know (or understand) the existence of rights (we can think of theleast developed African countries, for example). It is worth noticing, in this case,that when they answer how satisfied they are with their lives as a whole (whichoriginates our dependent variable), they are considering what effectively exists inwhat they conceive their universe is24.

Regarding the relation between fertility and happiness, it is interesting to noticefrom the literature that, at the individual level, there is usually a negative associationbetween own fertility and subjective well-being, unless other issues are taken intoconsideration, such as financial satisfaction (Stanca, 2009), or that country level

23For instance, we can mention the German case that offers part-time child care, or the Frenchcase that provides a certain amount of money for mothers who decide to stay at home to bring uptheir children. In the first case, a part of the mothers who make use of this right are not satisfied asthey judge insufficient the amount of time made available by the welfare State. In the second case,some women may judge as not fair or insufficient the amount of money reserved for the finality of raising their children.

24If a woman lives within a burka, and she conceives her life as doing what that restriction permitsher (which means basically having a life limited to the family and the house), then, the right of

living without it and doing other things may not be part of what she foresees for herself. Moreover,it can also be damaging for her, whatever external decision aimed at granting women more rightsa similar episode occurred recently in France, where the burka was publicly banned.

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indicators are incorporated in the analysis (Margolis and Myrskyla, 2010). At thispoint, the negative relation may vanish, and turn to positive. Our result, presentinga positive relation between fertility and women’s happiness, matches this second line

of evidence (though using another estimation strategy). In this case, the differentlevel of analysis and aggregation might capture other dynamics. In fact, we mightsuppose that, while at the individual level to decide to have a numerous familyinvolve substantial costs and trade-offs, at the aggregate level a high fertility ratemight signal a virtuous environment, enhancing women happiness.

5 Concluding remarks

This paper was interested in finding and explaining a possible gap between female andmale subjective well-being across countries. For this purpose, it laid an encompassing

view, considering female rights and achievements as well as the context of nationalbeliefs, all in different domains (economic, political and social).Combining an original dataset from the World Values Survey, World Development

Indicators and CIRI Human Rights, a two-step estimation strategy was used. Thisfound a happiness gender gap, favouring women throughout the world. Surprisingly,we found that many African and developing countries belong to the positive side of the female happiness distribution, while many European and industrialized countriesare responsible for the negative indices of women happiness.

We obtained some paradoxical results, at least at first sight: objective mattersof female rights and achievements display a negative impact on women’s happiness,whereas national beliefs that would favour men at the expense of women in economic

and political terms would grant them happiness. Beyond these findings, fertility hasa positive effect on their happiness.

First, our results show that the work of Stevenson and Wolfers (2009) cannotbe generalized to other countries, with respect to those for which their results hold(USA and 12 European countries). In fact, while they affirm that female happinesshas been declining both in absolute terms and relatively to men in their sample, wefound that, in a larger domain, women are, on average, happier than men.

Concerning our estimates, for interpreting the main apparently counter-intuitiveresults (the greater their rights and objective conditions, the less happy women are),we formulated a few possible hypotheses.

Specifically, our apparent paradox of women happiness can first be solved goingback to Nussbaum’s theory. The extensive work on the subject of this scholar high-lights a few possible lines of explanation, mostly complementary. First, Nussbaum’swork clarifies the personal and social costs involved in acquiring higher rights for

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women, which might eventually decrease the net individual pay-off at least in theshort and medium run. However, the nature of our data, at the moment, does notallow an easy temporal test of this hypothesis.

Next, Nussbaum emphasizes the role of internal and external capabilities forachieving well-being, and argues that objective conditions are just a facilitator forindividual flourishing. Last, the second shift theory and the possible existence of arights-expectations treadmill particularly for women - might add further pieces of sense to the initially puzzling evidence on the main determinants of the happinessgender gap.

Our findings, then, require a more complex discussion than that initially expectedon the basis of the existing literature, and are worthy of further investigations. Theconcerned social phenomena, in fact, involve non trivial methodological complexities.At the moment, this task was severely constrained by the predominant nature of ourcross-sectional estimates, while a more refined test would require additional and

longitudinal evidence, better able to capture the intrinsically dynamic nature of theprocess of socio-economic and political change.

Last, but not least, a certain aggregate evidence of a positive role of fertilityfor women happiness emerges, together with a call for appropriate public policyprograms.

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Nussbaum, M. C. (2000), Woman and Human Development. The Capabilities Ap-proach (Italian translation: (2001), Diventare persone. Donne e universalitadei diritti, Bologna: Il Mulino).

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6.1 Further Readings

Piore, M.J., Sabel, C. F. (1984). The Second Industrial Divide. Possibilities forProsperity, Basic Books.

Moller Okin, S. (1999), Is Multiculturalism Bad for Women? (Italian translation:(2007) Diritti delle donne e multiculturalismo, Milano: Raffaello Cortina).

Nussbaum, M.C. (2000), Duties of Justice, Duties of Material Aid. Cicero’s Prob-lematic Legacy, (Italian translation: (2008), Giustizia e aiuto materiale, Bologna:Il Mulino).

Nussbaum, M.C. (2002), Giustizia sociale e dignita umana, Bologna: Il Mulino.

Sen, A. K. (1980). Equality of What? In: McMurrin, S. (Ed.), Tanner Lectures onHuman Values, i. Cambridge: Cambridge University Press.

Sen, A. (1993). Capability and Well-Being. In: Nussbaum, M. C., Sen. A. (1993),The Quality of Life, Oxford: Clarendon Press.

Tran-Nguyen, A-N, Zampetti, A.B, (2004). Trade and Gender: Opportunities andChallenges for Developing Countries. UNCTAD. United Nations, New Yorkand Geneva.

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Table 1: Gender gap (Female-Male), Life Satisfaction (OLS), by country

Rank Country Coeff. t-stat Rank Country Coeff. t-stat1 Tanzania 8.41 3.33 48 El Salvador 0.40 0.222 Uganda 7.59 4.30 49 Venezuela 0.35 0.243 Algeria 6.83 3.54 50 Egypt 0.30 0.214 Zimbabwe 6.73 3.05 51 Canada 0.23 0.405 Jordan 5.99 3.70 52 Australia 0.21 0.366 Iraq 4.38 2.04 53 Germany 0.21 0.467 Morocco 3.21 3.75 54 Denmark 0.16 0.228 Nigeria 2.83 3.79 55 Albania 0.08 0.059 Malaysia 2.53 2.29 56 Sweden 0.06 0.1110 Taiwan 2.42 3.15 57 Argentina 0.04 0.0611 Uruguay 2.34 1.41 58 Georgia 0.04 0.0512 Hong Kong 2.09 1.64 59 Singapore -0.01 -0.0113 Netherlands 2.02 3.33 60 Russian Fed. -0.03 -0.0514 Bangladesh 1.99 1.35 61 Iceland -0.03 -0.04

15 Iran 1.86 2.01 62 Japan -0.04 -0.0516 Poland 1.82 2.19 63 North Korea -0.07 -0.0517 Czech Republic 1.68 2.13 64 Chile -0.09 -0.1118 India 1.68 2.01 65 Malta -0.22 -0.1419 China 1.67 2.31 66 United Kingdom -0.24 -0.4320 Ghana 1.66 1.19 67 United States -0.28 -0.5721 France 1.63 2.47 68 Burkina Faso -0.30 -0.1822 Hungary 1.60 1.77 69 Switzerland -0.31 -0.4023 Turkey 1.58 1.71 70 Slovakia -0.33 -0.3324 Mali 1.50 0.76 71 Luxembourg -0.36 -0.2825 Croatia 1.47 1.39 72 Bulgaria -0.39 -0.44

26 South Africa 1.32 2.48 73 Austria -0.39 -0.2927 Serbia 1.31 1.54 74 Norway -0.40 -0.5728 Ethiopia 1.20 1.17 75 Cyprus -0.41 -0.2929 Macedonia 1.09 0.95 76 Italy -0.47 -0.7130 Finland 1.08 1.39 77 Romania -0.50 -0.5631 New Zealand 1.06 1.33 78 Ukraine -0.53 -0.6432 Slovenia 1.06 1.49 79 Thailand -0.73 -0.8033 Belgium 0.97 1.57 80 Rwanda -0.74 -0.5834 Armenia 0.82 0.67 81 Peru -0.79 -0.9135 Philippines 0.81 0.71 82 Azerbaijan -0.93 -0.74

36 Latvia 0.77 0.76 83 Israel -0.95 -0.6137 Moldova 0.73 0.83 84 Belarus -1.10 -1.3938 Montenegro 0.73 0.54 85 Colombia -1.13 -2.2939 Mexico 0.69 0.78 86 Pakistan -1.15 -0.7440 Estonia 0.63 0.71 87 Portugal -1.23 -1.3141 Ireland 0.63 0.76 88 South Korea -1.51 -1.5142 Zambia 0.62 0.40 89 Lithuania -1.59 -1.4143 Greece 0.61 0.42 90 Puerto Rico -1.69 -1.4944 Viet Nam 0.57 0.72 91 Dominican Rep. -1.69 -0.5545 Indonesia 0.53 0.56 92 Andorra -2.06 -2.0846 Bosnia-Her. 0.48 0.54 93 Brazil -2.67 -3.23

47 Spain 0.47 1.20 94 Trinidad-Tobago -3.57 -2.28Note: Source: World Values Survey (ICPSR).

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Table 2: Descriptive statistics, individual level

Variable Mean Std. Dev. Min. Max. N

Life satisfaction 66.42 24.58 10 100 340504Income 4.69 2.48 1 10 294490Unemployed 0.08 0.28 0 1 330385Empl. Full time 0.38 0.48 0 1 330385Empl. Part time 0.07 0.26 0 1 330385Empl. Self 0.09 0.29 0 1 330385Empl. other 0.02 0.13 0 1 330385Retired 0.13 0.34 0 1 330385At home 0.14 0.35 0 1 330385Student 0.07 0.26 0 1 330385Education, lower 0.27 0.45 0 1 345102Education, middle 0.45 0.5 0 1 345102Education, upper 0.28 0.45 0 1 345102Married 0.59 0.49 0 1 341234

As married 0.05 0.22 0 1 341234Divorced 0.03 0.18 0 1 341234Separated 0.02 0.13 0 1 341234Widowed 0.07 0.25 0 1 341234Single 0.25 0.43 0 1 341234Number of children 2.15 1.68 0 8 282635Age 40.96 16.4 15 101 337669Male 0.48 0.5 0 1 341580Freedom 6.72 2.43 1 10 325257Importance of religion 2.94 1.07 1 4 304050Trust in others 0.29 0.45 0 1 330569

Honesty 8.59 2.35 1 10 321290Survey wave 1 0.09 0.28 0 1 346324Survey wave 2 0.17 0.38 0 1 346324Survey wave 3 0.24 0.43 0 1 346324Survey wave 4 0.28 0.45 0 1 346324Survey wave 5 0.22 0.41 0 1 346324

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Table 3: Descriptive statistics, country level

Variable Mean Std. Dev. Min. Max. N

Gender gap (female) 0.09 0.68 -1.42 5.99 94Women Economic Rights 1.47 0.52 0 2.5 92Women Political Rights 1.89 0.36 0.54 3 92Women Social Rights 1.48 0.78 0 3 92Female Labor Force Part 0.41 0.08 0.14 0.53 89Woman in Parliament 0.16 0.09 0.02 0.44 89School Enrollment Ratio 0.98 0.07 0.71 1.07 86Life Expec. Ratio 1.08 0.03 1 1.19 90Fertility Rate 3.18 1.57 1.57 7.24 93Men more right to job -1.8 0.23 -2.4 -1.19 79Men better P. Leaders -2.49 0.43 -3.43 -1.43 79Univ. more imp. boys -3.02 0.29 -3.7 -2.31 79Housewife fulfilling -2.25 0.31 -3.16 -1.71 79

Table 4: Determinants of subjective well-being, individual level

LS (OP) LS (OLS)RegressorsIncome 0.07** (55.83) 1.42** (60.52)Unemployed -0.19** (-17.71) -4.15** (-19.47)Empl. Part time -0.01 (-1.06) -0.29 (-1.51)Empl. Self -0.02* (-2.47) -0.52** (-2.96)Empl. other -0.03 (-1.78) -0.85* (-2.26)Retired 0.08** (8.35) 1.33** (6.99)

At home 0.09** (9.93) 1.64** (9.30)Student 0.09** (7.11) 1.75** (7.12)Education, middle 0.04** (5.51) 0.92** (6.76)Education, upper 0.03** (3.73) 0.94** (6.11)Married 0.10** (11.51) 1.97** (11.30)As married 0.02 (1.44) 0.39 (1.47)Divorced -0.13** (-9.22) -2.67** (-9.32)Separated -0.21** (-10.13) -4.25** (-10.29)Widowed -0.04** (-3.00) -0.85** (-3.06)Number of children -0.01* (-2.50) -0.12** (-3.02)Age -0.00* (-2.41) -0.02** (-3.62)

Male -0.03** (-5.96) -0.63** (-5.90)Honesty 0.01** (12.49) 0.27** (11.70)Trust in others 0.10** (18.59) 2.15** (19.93)Freedom 0.16** (115.14) 3.20** (123.60)Importance of religion 0.06** (22.43) 1.14** (20.11)Pseudo R2 / R2 0.08 0.31Number of obs. 185573 185573

Note: Dependent variable: Life satisfaction. Estimator: Ordered Probit (column 1) or OLS(column 2). t-statistics reported in brackets (heteroskedasticity-robust standard errors). *indicates p<0.05, ** indicates p<0.01.

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Table 5: Determinants of the happiness gender gap: rights

(1) (2) (3) (4)RegressorsWomen Economic Rights -0.23

(-1.64)Women Political Rights -0.48*

(-2.49)Women Social Rights -0.22*

(-2.48)Women Rights -0.33*

(-2.40)Constant 0.43 1.00** 0.43** 0.62**

(1.98) (2.70) (2.82) (2.69)

R2 0.03 0.06 0.06 0.06R2 92 92 92 92

Note: Dependent variable: Effect of on Life Satisfaction. t-statistics reported in brackets(heteroskedasticity-robust standard errors). * indicates p<0.05, ** indicates p<0.01.

Table 6: Determinants of gender gap: achievements

(1) (2) (3) (4) (5) (6)RegressorsFemale Labor Force Part -3.38** -3.22**

(-3.85) (-2.87)Woman in Parliament -1.47 -0.66

(-1.72) (-0.69)School Enrollment Ratio -0.71 2.18

(-0.66) (1.59)Life Expec. Ratio -4.24 -0.08

(-1.95) (-0.03)

Fertility Rate 0.09* 0.10(2.10) (1.55)

Constant 1.46** 0.34* 0.79 4.69* -0.21 -0.85(4.04) (2.13) (0.75) (1.99) (-1.31) (-0.27)

R2 0.15 0.03 0.01 0.04 0.05 0.19R2 89 89 86 90 93 82


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Table 7: Determinants of gender gap: beliefs

(1) (2) (3) (4) (5)RegressorsMen more right to job 1.12** 1.04*

(3.35) (2.07)

Men better P. Leaders 0.43* 0.31(2.27) (0.78)Univ. more imp. boys 0.23 -0.58

(0.81) (-1.24)Housewife fulfilling 0.35 0.19

(1.28) (0.73)Constant 2.12** 1.17* 0.80 0.88 1.42

(3.49) (2.45) (0.92) (1.43) (1.19)R2 0.13 0.06 0.01 0.02 0.15R2 79 79 79 79 79

Note: Dependent variable: Effect of on Life Satisfaction. t-statistics reported in brackets

(heteroskedasticity-robust standard errors). * indicates p<0.05, ** indicates p<0.01.

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Table 8: Determinants of the happiness gender gap: all

(1) (2) (3) (4)RegressorsWomen Economic Rights -0.09

(-0.30)

Women Political Rights -0.79(-1.81)Women Social Rights -0.12

(-0.55)Women Rights -0.31

(-0.87)Female Labor Force Part -3.14* -2.55 -3.00* -2.91*

(-2.27) (-1.84) (-2.12) (-2.07)Woman in Parliament -0.60 0.79 -0.47 -0.20

(-0.44) (0.51) (-0.33) (-0.14)School Enrollment Ratio 2.95 3.29* 2.91 2.97

(1.95) (2.22) (1.93) (1.98)Life Expec. Ratio 1.89 1.10 1.84 1.74

(0.54) (0.32) (0.53) (0.50)Fertility Rate 0.09 0.08 0.08 0.07

(1.02) (0.94) (0.86) (0.72)Men more right to job 1.08 0.99 1.10 1.10

(1.70) (1.61) (1.72) (1.74)Men better P. Leaders 0.07 0.04 0.03 0.01

(0.14) (0.08) (0.06) (0.01)Univ. more imp. boys -0.60 -0.59 -0.60 -0.63

(-1.22) (-1.27) (-1.23) (-1.31)Housewife fulfilling 0.07 0.19 0.08 0.12(0.19) (0.54) (0.22) (0.32)

Constant -3.17 -1.58 -3.09 -2.84(-0.76) (-0.38) (-0.74) (-0.68)

R2 0.29 0.33 0.29 0.30R2 71 71 71 71


A Cross-Country Investigation of the Determinants of the Happiness Gender Gap

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