Archive:Quality of life in Europe - facts and views - overall life satisfaction
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Source: Eurostat (EU SILC)
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Note: ‘Other household types’ refers to Other households with and without dependent children
Source: Eurostat (EU SILC)
Note: ‘Other’ includes people permanently disabled/unfit to work, fulfilling domestic tasks, in compulsory military community or service
Source: Eurostat (EU SILC)
Source: Eurostat (EU SILC)
Note: Lower secondary: Pre-primary, primary and lower secondary education (ISCED levels 0-2), Upper secondary: Upper secondary and post-secondary non-tertiary education (ISCED levels 3 and 4), Tertiary: First and second stage of tertiary education (ISCED levels 5 and 6)
Source: Eurostat (EU SILC)
Source: Eurostat (EU SILC)
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Source: Eurostat (EU SILC)
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Note: 'Other household types' refers to 3 or more adults with and without dependent children
Source: Eurostat (EU SILC)
Note: ‘Other’ includes people permanently disabled/unfit to work, fulfilling domestic tasks, in compulsory military community or service
Source: Eurostat (EU SILC)
Source: Eurostat (EU SILC)
Source: Eurostat (EU SILC)
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Source: Eurostat (EU SILC)
This article is focusing on the overall subjective well-being of people in the EU and is part of a set of articles forming the publication Quality of life in Europe - facts and views. This allows the integration of the diversity of the experiences, choices, priorities and values of an individual. The data used on subjective evaluations and perceptions of different domains were collected for the first time in European official statistics through the 2013 Ad-hoc module of EU SILC on subjective well-being.
Subjective well-being encompasses three distinct but complementary sub-dimensions: life satisfaction, based on an overall cognitive assessment; affects, or the presence of positive feelings and absence of negative feelings; and eudaimonics, the feeling that one’s life has a meaning, as recommended by the OECD Guidelines on Measuring Subjective Well-being. In the Eurostat quality of life framework, all three sub-dimensions are covered.
Main statistical findings
On a scale of 0 to 10 nearly 8 in 10 of European residents rate their overall life satisfaction in 2013 with 6 and higher. This represents an average (mean) satisfaction of 7.1, with values ranging from 4.8 in Bulgaria (followed by Portugal, Hungary, Greece and Cyprus, all at 6.2) to 8.0 in Finland, Denmark and Sweden. Women and men are nearly equally satisfied and younger EU citizens are more satisfied than the other age groups. Unemployed and inactive people are on average the least satisfied (5.8) compared to full-time employed (7.4) or people being in education or training (7.8), who report the highest rates of life satisfaction.
Material living conditions, social relationships and health status are clearly related to life satisfaction. Being at risk of poverty or severely materially deprived is of special relevance here. However, a bad health status impacts on life satisfaction most negatively.
The patterns are mostly the same when looking at meaning of life which is referred to as the eudaimonic aspect of well-being though all groups rate the purpose of life on average higher than their overall life satisfaction.
All three aspects of subjective well-being are associated both on the country as well as on the individual level with some exceptions. In general, people who experienced happiness more often in the last 4 weeks also have a higher probability of high scores regarding meaning of life or life satisfaction, though a considerable proportion of 7.1% of those “being happy all of the time” report low levels of life satisfaction.
Life satisfaction
Life satisfaction is measured on an 11 points scale which ranges from 0 (“not satisfied at all”) to 10 (“fully satisfied”). For better understanding and interpretation and to facilitate analyses which identify drivers for low and high satisfaction answer categories were grouped into low, medium and high. As no theoretical or external criteria were available on an international basis this classification was based on a 20:60:20 distribution at European level. That means having 20% of answers in the lower part of the scale, 60% in the middle and 20% in the higher part, which leads to the definition of the following thresholds: 0-5 as being “low”, 6-8 as being “medium” and 9 and 10 as being ”high”. The same classification was adopted for all other satisfaction items
Figure 1 shows that 21.7% of the EU-28 population are highly satisfied with their lives (9 and 10), 57.4% rated their overall life satisfaction between 6 and 8 and 21.0% report a low level of life satisfaction (0-5). One should however bear in mind that the thresholds for life satisfaction levels are defined in this way at European level, as described in the previous paragraph, in order to allow comparisons between countries, socio-demographic groups or different satisfaction items.
Figure 2 shows that means of life satisfaction vary significantly between countries, ranging from 4.8 in Bulgaria to 8.0 in Sweden, Denmark and Finland. Differences between countries regarding proportions of people with low satisfaction are even more remarkable. They range from 5.6% in the Netherlands to 64.2% in Bulgaria. Proportions of people with high life satisfaction are comprised from 5.9% in Bulgaria (followed by Hungary (11.6%) and Latvia (12.6%)) to 42.1% in Denmark. As can be seen in Figure 2 the same averages can reflect different distributions. France and Slovakia show the same average of 7.0 but Slovakia has much higher proportions of people with both low and high life satisfaction.
How is the socio-demographic background associated with life satisfaction?
Previous research has shown that subjective well-being as measured through overall life satisfaction is very much shaped by socio-demographic factors such as age[1], income[2] or education[3] which lead to different living situations as well as to different expectations and preferences. The analysis below considers how such factors relate to the level of life satisfaction of EU residents.
Marginal gender effects on subjective well-being
As shown in Figure 3, women rate their overall life satisfaction slightly lower than men (mean of 7.0 vs. 7.1). Interestingly, the proportion of women with a high level of life satisfaction (22.0%) is slightly above that of men (21.3%). On the other hand, marginally more women than men report low levels of life satisfaction (21.6% vs. 20.2%). This might lead to the conclusion that generally spoken, men and women are equal in terms of life satisfaction. However, when controlling for other variables such as for income, marital status, labour market position etc. (in a regression analysis), women are still significantly more satisfied with their lives than men[4]. The difference ramins however very small.
Younger people tend to report higher levels of subjective well-being
As can be seen in Figure 4, life satisfaction is highest among the youngest age group. It decreases with rising age with the exception of the age group 65-74, which is for most people the period right after retirement, with averages slightly higher than for those aged between 50 and 64 (7.0 vs. 6.9). This “retirement-effect” can be seen in the majority of the participating countries (Table 1), with the exception of eight (mainly Eastern Europe) countries (Bulgaria, Greece, France, Croatia, Italy, Latvia, Poland and Romania), where people in the age group 65-74 do not report higher life satisfaction than those aged between 50 and 64[5]. However, in most of the countries the youngest age group reports the highest scores of life satisfaction, exceptions being Denmark, Netherlands, Sweden, United Kingdom, Switzerland and Norway where people 65 or older are even more satisfied than the young.
The effect of age on life satisfaction is small but statistically significant (also when controlling for other variables). However, it has to be taken into account that health problems in older ages play a crucial role and that age itself is not the driving force here. Also cohort effects have to be taken into account when examining age differences: People of the same age-group in a certain country belong to the same generation, lived their active lives in a certain time and experienced wars and peaceful periods in similar periods of their lives. As a consequence, the fact that people in the age group 65-74 are more satisfied with their lives does not imply that a person who is 58 today has a higher probability to be more satisfied with his/her life when 68.
Life satisfaction is higher among couples and people with children
Figure 5 illustrates that the life satisfaction of people living alone is below the average level of couples (with and without children). Two adults living with children report the highest levels for life satisfaction (7.4). The lowest average values of life satisfaction, on the other hand, can be observed for one-person households younger than 65 and lone parent household (both 6.6).
Single females aged 65+ most frequently report a low level of life satisfaction (29.4%), followed by lone parent households (29.2%). On the other end of the range are people living in a couple with three or more dependent children, out of which 28% report a high level of life satisfaction, and only 15.3% a low one.
Unemployment is associated with very low life satisfaction
Figure 6 highlights a clear relationship between labour status and life satisfaction. The part of the population which is actively participating in the labour market or preparing to do so such as those in education or training is more satisfied with their lives on average than the unemployed, retired or other groups.
The lowest level of overall life satisfaction (average 5.8) is reported by the unemployed, which is 2 points lower than the level of people in education and training (7.8). Within the group of employed, the overall mean of life satisfaction is slightly lower for employees working part-time (7.3) than for their full time counterparts (7.4). As the differences between these groups are quite small and also because of the high proportion of part-timers that are not voluntarily choosing this schedule in many countries they should not be overrated.
In almost all EU countries people in education or training report the highest life satisfaction averages, exceptions being only Denmark, Finland and Ireland, where people in full time employment are more satisfied.
Of all socio-demographic variables unemployment has the most negative impact on life satisfaction. This is true for nearly all EU countries. EU-wide 43.6% of this group report low life satisfaction, and are thus more than three times as likely to rate their life satisfaction low than for instance the full-time employed for which the equivalent is of only 14.2%.
Life satisfaction is clearly associated with income
The analysis of the relationship between income and life satisfaction has a long tradition in empirical research of well-being. First papers date back to the 1970ies. One of the first to investigate the empirical relationship between income and life satisfaction both regarding the individual and the country level was Easterlin (1974). He observed that wealthier persons were happier than poorer ones in a country and that on average wealthier countries report higher subjective well-being than poorer ones, which is common ground today and was confirmed by many studies (e.g. Diener 1984, Boarini et al. 2012, p.10). However, it was also shown by Easterlin that despite economic growth, average scores of subjective well-being stayed approximately constant over that period. This could lead to the conclusion that increasing income is generally accompanied by an increase in life satisfaction, but only up to a certain point (also known as rule of diminishing utility e.g. Sacks et al. 2010).
It emerges also from the analysed data in this article that higher income is related to higher scores of life satisfaction. As can be seen in Figure 7, people in the lowest income tercile[6] have the lowest average score (6.5) compared to the other income groups (2nd tercile: 7.1 / Highest tercile: 7.5).
Only 16.7% of persons in the lowest tercile report to be very satisfied with life in contrast to 27.2% of population in the highest income group. Low life satisfaction is reported by 30.3% of people in the lowest income tercile compared to 12.2% in the highest one.
Strong effect of education on subjective well-being
Education is not only an economic resource enabling people to get satisfying and better paid jobs. Many people see education as a value in itself. So it would not be surprising if higher educational levels turned out to be positively related with subjective well-being. However, scientific studies draw a diverse picture on that. Some researchers found a positive relationship between educational attainment and life satisfaction on an individual level[7], others found a negative relationship particularly for the older population[8]. At an aggregated level, Cheung & Chang (2009) provided evidence that life satisfaction is higher in countries where people spend on average more years in education[9].
Also with view of the EU-SILC data higher educational attainment seems to engender higher levels of life satisfaction (reflecting differences for life satisfaction from an average of 6.6 for people with at maximum lower secondary, to an average of 7.6 for those with tertiary education) (see Figure 8). This can probably be at least partly accounted to the fact that higher education leads to better jobs and higher income, which in turn leads to higher life-satisfaction.
These patterns, however, vary significantly between countries. There is for instance no difference in average life satisfaction between groups with tertiary and lower secondary education in Sweden and only a very marginal difference of 0.1 points in Denmark, while these differences sum up to 2.0 points in Bulgaria or 1.6 points in Hungary and Croatia.
What are other important drivers of life satisfaction? Objective / subjective
As already discussed, there are regional patterns of subjective well-being. Most of the countries with lower life satisfaction were in the near past, and still are characterised by a low level of income (as indicated for example by PPS adjusted GDP per capita). Possibly also important is the fact that a significant part of the population, the older generations, had experienced lasting and dramatic reversals in the economic, social, welfare and political circumstances of their lives.
As the highest levels of satisfaction are recorded in the Northern countries and very low levels can be found in Eastern and Southern countries which suffered strongly from the economic crisis and/or have a weak economic situation, the question arises if average life satisfaction is associated with the general economic situation of a country. As shown in Figure 10 for most countries there seems to be a positive association between GDP and overall life satisfaction. Outliers can be found at both ends of the distribution of life satisfaction: Luxembourg, Norway and Switzerland show high values of overall life satisfaction but they are not as high as a potential linear relationship between GDP and average life satisfaction would imply. However, other factors may be at play as well, especially in the case of Luxembourg[10]. On the other end of the range Bulgaria shows even lower life satisfaction than to be expected by its low GDP. The GDP of Romania is comparable to that of Bulgaria but residents of Romania rate their life satisfaction much higher on average than their Bulgarian counterparts.
Life satisfaction and objective indicators
As is known from a huge body of literature, life satisfaction is not only associated with socio-economic factors, but also and particularly with living conditions and health. In the following, the article will therefore examine some of these relationships.
More than half of the severely materially deprived EU citizens report a low level of life satisfaction
Severely materially deprived persons have living conditions greatly constrained by a lack of resources and cannot afford at least four out of 9 items: to pay rent or utility bills; to keep their home adequately warm; to pay unexpected expenses; to eat meat, fish or a protein equivalent every second day; a week holiday away from home; a car; a washing machine; a colour TV; or a telephone. Together with the “at-risk-of poverty rate” and the indicator “low work intensity” severe material deprivation forms the Europe 2020 indicator “at risk of poverty or social exclusion”[11]. EU-wide, 2013 9.6% of the population are affected by severe material deprivation, 16.6% are at risk of poverty and 10.8% of the population aged between 0 and 59 live in households with very low work intensity. Overall, 24.4% report at least one of these problems and are thus at risk of poverty or social exclusion.
Figure 10a demonstrates that there is also a clear relationship between being severely materially deprived and overall life satisfaction, with an average 1.9 points higher for the non-deprived population (7.2) as of those severely deprived (5.3). This difference is namely due to the particularly low proportion of very satisfied population (7.5%) and very high proportion of those with a low level of life satisfaction (53.2%) among the severely deprived. The risk of monetary poverty, illustrated in Figure 10b, leads to lower well-being as well, but to a far lesser extent.
Social relationships
As already indicated in the chapter on household types, supportive personal relationships play an important role in life satisfaction. In the SILC module 2013 they are covered by two items: “having anyone to discuss personal matters with” and “getting help from others when needed”. Both items show very similar patterns, as can be seen in Figure 11 for social support, which is highly associated with life satisfaction. More than double proportion of people who can’t count on friends or family when help is needed have a low level of life satisfaction (44.8% vs. 19.0%). Only 9.4% of this group report high levels of life satisfaction compared to 22.7% of those who have help available. Fortunately, the proportion in the population of those who don’t have someone to rely on for help or discuss personal matters with is rather small (6.7% at EU level for the former and 7.1% for the latter).
Life satisfaction is strongly associated with health
EU-wide, 67.7% report a very good or good health status, while 9.5% of the population perceives their health status as bad or very bad in 2013[12]. As shown in Figure 12 subjective assessment of one`s own health is a very good predictor for overall life satisfaction, with the proportion of people with low life satisfaction going up as self-perceived health goes down. The opposite is true for the proportion of people with high life satisfaction. While in the group with very good health 36.9% show high life satisfaction, there are only 7.1% with high life satisfaction in the group with very bad health. It seems to be possible to have a good life even in very bad health, although the probability is more than 5 times lower than for those in very good health.
With a proportion of people with low satisfaction of 65.9 % in the group with very bad health, health status is the most remarkable predictor for general life satisfaction. Nothing, not even unemployment or material deprivation puts life satisfaction in danger as much as bad health. The average score ranges from 7.9 for people who say to be in very good health to 4.5 for those with a very bad health status.
Meaning of life and happiness
As already mentioned, subjective well-being encompasses three distinct but complementary sub-dimensions: life satisfaction (or evaluation), based on an overall cognitive assessment; affects or the presence of positive feelings and absence of negative feelings and eudaimonics, the feeling that one’s life has sense and purpose. Evaluation has already been discussed above. In this part we will first analyse the other two aspects and break them down by selected socio-economic variables and will then examine how the three aspects are interrelated. Furthermore, the following part is devoted to the question of what is measured by these three different variables and how it relates to the full picture of subjective well-being.
Meaning of life
In the EU-SILC 2013 data we observe that meaning of life shows an almost identical pattern as life satisfaction, with the difference, however, that meaning of life is constantly rated higher by all groups than life satisfaction. This is true when looking at socio-demographic variables but also when comparing life satisfaction and meaning of life broken down by more objective items such as material deprivation or risk of poverty. Nevertheless, the differences of averages between groups who report disadvantages in a specific domain and those who don’t, are much smaller regarding meaning of life than for life satisfaction. One could therefore conclude that the evaluative part of subjective well-being in a way summarises concrete domain specific satisfactions, while the question of a purpose or meaning in life is answered on a more – even if not total – abstract level.
Compared to life satisfaction, people generally are more positive regarding the meaning of life. Figure 13 shows that 28.2 % of the total EU-28 population rate the meaning of life at a high score (9 and 10), 56.9% assessed it between 6 and 8 and 14.9% report a low level of meaning of life (0-5).
Meaning of life by selected socio-demographic variables
Women on average report slightly higher levels of meaning of life (which is the other way around compared to life satisfaction). Males have an average value of 7.4 and the females of 7.5. Significantly more women than men report high levels of meaning of life (29.6% vs. 26.6%), while there are negligible differences regarding the bottom of the distribution
As compared to life satisfaction, the average meaning of life is quite constant across the various age groups ranging between 7.4 (age group 65-74) to 7.6 (16-24). The exception, however, is the oldest group of people aged 75 or older who report an average score of 7.1, therefore showing a significantly lower level of meaning of life.
Regarding the distribution, the proportion of low meaning of life is very slightly increasing with age but is by far highest in the oldest age group (21.3%). Proportions of high levels are quite constant between the ages 25 and 74 and are most frequently reported by people aged between 16 and 24 (31.9%).
The interrelation of life satisfaction and meaning of life
How are meaning of life and overall life satisfaction related? Do they measure the same or at least a similar construct?
When looking at both items together on the country level, it can be observed that in countries with the highest average values of life satisfaction, meaning of life is more or less at the same level such as in Finland (both 8.0) or Austria (7.8/ 7.9). It is slightly below in the Netherlands (7.8/ 7.7) and Sweden (8.0/ 7.8) or slightly above such as in Denmark (8.0/ 8.2) (see Figure 16). In most other EU countries, people rate the meaning of life notably higher than their level of overall life satisfaction. The gap of life satisfaction and meaning of life is larger in countries where life satisfaction is low with the biggest differences being observed in Bulgaria (1.4 points), Portugal (1.3 points) and Cyprus (1.1. points).
Overall, the eudaimonic aspect of well-being is more concentrated around the average than life satisfaction. As shown above, in most countries the meaning of life is rated higher than the general life satisfaction. Figure 17 illustrates that countries with low average levels of life satisfaction such as Bulgaria or Greece also report comparable low values for meaning of life and the other way round: Higher means of overall life satisfaction are associated with higher rates for meaning of life. Although Figure 17 shows no perfect correlation, the connection is quite strong. There are exceptions as well. Portugal, which is among the countries with the lowest level of life satisfaction (6.2), actually has an average value of meaning of life of 7.5 which is above EU-28 average (7.4). French residents, on the other hand, rate their life satisfaction and their meaning of life at the same level (7.1), which is equal to the EU average for the former, but among the lowest averages in EU comparison for the latter.
Deviations from the regression line need to be further examined but might also be due to language specificities (the concepts of “meaning” and “satisfaction” being interpreted differently in different languages) or other cultural effects.
Happiness
Happiness is measured in EU-SILC by the following question: “How much of the time over the past four weeks have you been happy?” Although this question is asked on verbal 5 point scale in the EU-SILC 2013 and can thus not be directly compared with life satisfaction, we observe similar patterns regarding differences between various groups. However, the differences between groups who report disadvantages in a specific domain and those who don’t are not as pronounced regarding happiness as for life satisfaction.
Figure 18 shows that nearly 6 in 10 EU residents say that over the last four weeks they were all or most of the time happy. Almost a third of the EU population was happy some of the time and a proportion of 13% answered to have been happy only a little or none of the time.
Frequency of being happy in the last 4 weeks by selected socio-demographic variables
As can be seen in Figure 19, happiness (as life satisfaction and meaning of life) is highest among the youngest age group (16-24) with a proportion of 71.5% reporting to have been happy all or most of the time over the last four weeks. It then decreases until the age of 50- 64, goes slightly up again between 65-74 and reaches its bottom in the 75+ group which has the highest proportion of people who were “happy little or none of the time” (17.9%).
Figure 20 illustrates that generally 2 adult households (in many cases couples) are happier than people living on their own and that households with children are the happiest (with the exception of single parents who report rather low happiness levels). 66.8% of people living in households with two adults and three children and 65.8% with two adults and one or two children were happy all or most of the time. At the other end of the distribution, women aged 65 or older living alone are the most often unhappy with a proportion of 20.9% who say that they were happy little or none of the time (followed by males older than 65 (19%) and female 1-person households younger than 65 (18.8%)).
People who are in education and training were the most often happy with more than 7 in 10 answering to have been happy all or most of the time over the last four weeks, followed by part-time employees with 66.5%. The last group differs only slightly from the full-time employees who report high happiness levels as well. On the other hand, unemployment has not only negative consequences for life satisfaction and meaning of life but also severe impacts on happiness. 22.6% of the unemployed said that they were happy little or none of time.
Interrelations of happiness and the other two aspects of subjective well-being
Figure 22[13] illustrates the relationship of low life satisfaction and low happiness (being happy none or little of the time) showing a quite linear association, exception being Romania, Latvia and Greece, where the proportion of the population being happy little or none of the time is higher than could be expected. Three main groups can be identified: Group 1 containing countries with low proportions in both items, group 2 (including the EU-28 average) with medium levels and group 3 with comparable high proportions of people being happy none or little of the time and highest proportions of reported low life satisfaction between 34.4% in Estonia and 40.5% in Portugal.
The picture is not as clear when looking together at the proportion of people “being happy none or little of the time” and “low meaning of life” as shown in Figure 23, though the pattern is quite comparable. For instance, the outliers are again Romania, Latvia and Greece. However, the three clear-cut groups disappear. There is one bunch of countries, including those with proportions of people being happy none or little of the time between 4.6% in the Netherlands and 8.4% in U.K. and proportions of low meaning of life ranging from 4% in Finland to 13% in the U.K. The other group of countries displays proportion of low happiness ranging from 10% in France to 19.7% in Portugal and low meaning varying from 14.7% of the Polish to 23.8% of the Croatian population.
It can be concluded that there is an observable relationship between happiness and satisfaction at least at country level. And how about individuals? Are people who have been happy most or all of the time in the last four weeks highly satisfied with their life? Table 2 shows that in general this is true: a person who experienced happiness more often in the last 4 weeks has a higher probability of a high score regarding meaning of life. On the other hand it can be seen that life satisfaction is not the same as happiness. 7.3% of those who were happy all the time rated their overall life satisfaction between 0 and 5, which is regarded as low. Also, 6.1 % of those who were happy none of the time reported a high life satisfaction, and even 13.5% of people in this group report high values regarding meaning of life. So it can be concluded that life satisfaction does not measure the same as happiness but of course the two are correlated.
Data sources and availability
Ad Hoc module SILC xxxxx
Context
Life satisfaction
Life satisfaction represents how a respondent evaluates or appraises his or her life taken as a whole. It is intended to cover a broad, reflective appraisal the person makes of his or her life. The term «life» is intended here as all areas of a person’s existence[14]. The variable therefore refers to the respondent’s opinion/feeling about the degree of satisfaction with his/her life. It focuses on how people are feeling "these days" rather than specifying a longer or shorter time period. The intent is not to obtain the current emotional state of the respondent but to receive a reflective judgement on their level of satisfaction. Veenhoven (1991, 3) notes that “life satisfaction is conceived as the degree to which an individual judges the overall quality of his/her life-as-a-whole favourably“. This is in line with Pavot and Diener (2008, 137) who define life satisfaction as a “distinct construct representing a cognitive and global evaluation of the quality of one’s life as a whole“. Some economists also discuss the question if satisfaction is the same as utility[15].
While indicators like job satisfaction, satisfaction with the financial situation of the household or satisfaction with the accommodation address certain areas of life, general life satisfaction refers to the individual’s evaluation of all subjectively relevant life domains and is therefore considered as an overall measure for subjective well-being.
Meaning of life - an eudaimonic measure
Meaning of life is a multi-faceted construct that has been conceptualised in diverse ways[16]. It refers broadly to the value and purpose of life, important life goals, and for some, spirituality. The respondent should be invited to think about what makes his/her life and existence important and meaningful and then answer to the question. It is not related to any specific area of life, focuses rather on life in general and refers to the respondent’s opinion.
In the EU-SILC 2013 ad-hoc module (AHM) the item «meaning of life» covers the eudaimonic dimension of subjective well-being. «Eudaimonic»[17] refers to purpose and meaning in life. It is therefore also referred to as the psychological or «functioning» approach[18] to subjective well-being. The meaning of life item intends to capture important factors that are not necessarily measured by evaluative measures such as life satisfaction including purpose, sense of meaning or autonomy. However, as will be seen from the analysis below, the pattern of this item is quite in line with the life satisfaction, though in general people tend to rate their « meaning of life » higher than their life satisfaction.
Happiness - emotional aspect of well-being
The emotional aspect of well-being refers to people’s day-to-day feelings and moods. For this kind of measures, respondents are typically asked to think about their feelings in question (such as happiness or sadness) within a short time period. Large sample sizes and high survey quality should ensure that population estimates are not systematically biased due to temporal variability of moods etc.
In EU-SILC the period on which the respondent should reflect was limited to the last four weeks before the interview. Both positive and negative feelings were measured including happiness, depression, stress and others. In this article, however, we will only focus on a question on happiness. Respondents were invited to answer the following question: “How much of your time over the past four weeks have you been happy?”. They could choose among five answering categories (ranging from “all of the time” to “none of the time”).
In this article overall life satisfaction will have a prominent role as it can be regarded as a key indicator for subjective well-being. First the distribution in general and for different countries will be shown. Then the association of socio-demographic variables such as age, gender, income or household type with overall life satisfaction will be examined. In a further step, the article will look at other relevant variables such as material living conditions and their relation to life satisfaction. In the final part the subjective well-being dimensions meaning of life and happiness are covered and it is discussed how they are related to life satisfaction. Relevant EU-policies are discussed in the concluding passage.
EU policies targeting subjective well-being
Measuring well-being has an inherent appeal: it is arguably the ultimate aim of all EU policies, and the common thread that runs through them all. Promoting the well-being of people in Europe is one of the principal aims of the European Union, as set forth by the Treaty on European Union[19].
Today, in the European Union a broad range of outcomes is considered when evaluating the objectives of social and economic policy including subjective measures of quality of life. Many EU bodies but also Member States themselves report on subjective well-being and publish associated reports going beyond GDP as the overall measure of societal performance.
Well-being began to appear more explicitly at the EU policy agenda in 2006 when the Council of the European Union cited the well-being of present and future generations in its European Sustainable Development Strategy as its central goal[20]. Soon after that the limits of GDP as a measure of well-being were more and more discussed at the international level flowing into the “Beyond GDP” initiative followed by a Conference in the European Parliament in 2007. In 2009 the European Commission published its Communication on “GDP and beyond – measuring progress in a changing world” concluding that EU policies will be ultimately judged on the question if they successfully delivered social, economic and environmental goals[21]. In the same year, the Commission on the Measurement of Economic Performance and Social Progress (Stiglitz-Commission) published its Report[22]. The so called Stiglitz Report was also the basis for the work of the ESS (European Statistical System) Sponsorship Group on Measuring Progress, Well-being and Sustainable Developement which published its report in 2011[23].
See also
- All articles on living conditions and social protection
- Quality of life indicators (online publication)
Further Eurostat information
Publications
Publications in Statistics Explained (either online publications or Statistics in focus) should be in 'See also' above
Main tables
- Income distribution and monetary poverty (t_ilc_ip)
- Monetary poverty (t_ilc_li)
- Monetary poverty for elderly people (t_ilc_pn)
- In-work poverty (t_ilc_iw)
- Distribution of income (t_ilc_di)
- Material deprivation (ilc_md)
- Material deprivation by dimension (t_ilc_mddd)
- Housing deprivation (t_ilc_mdho)
- Environment of the dwelling (t_ilc_mddw)
Database
- Income distribution and monetary poverty (ilc_ip)
- Monetary poverty (ilc_li)
- Monetary poverty for elderly people (ilc_pn)
- In-work poverty (ilc_iw)
- Distribution of income (ilc_di)
- Material deprivation (ilc_md)
- Material deprivation by dimension (ilc_mddd)
- Economic strain (ilc_mdes)
- Economic strain linked to dwelling (ilc_mded)
- Durables (ilc_mddu)
- Housing deprivation (ilc_mdho)
- Environment of the dwelling (ilc_mddw)
Dedicated section
Methodology / Metadata
- Income and living conditions (ESMS metadata file — ilc_esms)
Source data for tables, figures and maps (MS Excel)
The excel file "Quality of life - Material and living conditions" should be added
Notes
- ↑ e.g. Helliwell 2008
- ↑ e.g. Boarini et al. 2012, Sacks et al. 2010
- ↑ Cárdenas & Mejía 2008, Salinas-Jiménez et al. 2010, Cuñado & Pérez de Gracia 2012
- ↑ This is also confirmed in other international studies such as Boarini et al. 2012
- ↑ The official retirement age is currently between 60 (in France) and 65 (eg: Benelux countries, Germany, Ireland, Spain) in most EU countries. In some Member States (for example Austria, Poland, Italy, Greece and the UK) women can retire 5 years earlier than men
- ↑ Income terciles are three equal-sized income groups which refer to the position of income in the frequency distribution. The tercile cut-off value is obtained by sorting all incomes, from lowest to highest, and then choosing the value of income under which 33.3% (lower limit), 66.6% (second limit) and 100% (upper limit) of the sample are located. A tercile as such is associated with the segment boundaries between two terciles. The first segment includes income below the lower tercile cut-off (33.3%), the second segment includes income located between the lower cut-off and the higher tercile cut-off
- ↑ e.g. Cárdenas & Mejía 2008, Salinas-Jiménez et al. 2010, Cuñado & Pérez de Gracia 2012, Boarini et al. 2013
- ↑ Gong et al. 2011
- ↑ Years of education are predicted by enrollment rates at the secondary and tertiary levels
- ↑ The GDP per capita of Luxembourg is artificially high, as a high proportion of people working in Luxembourg live abroad in the neighbouring countries, so they contribute to GDP creation but are not counted when distributing it per capita
- ↑ European Commission (2014): Smarter, greener, more inclusive? Indicators to support the Europe 2020 strategy, 2015 edition, page 145
- ↑ http://appsso.eurostat.ec.europa.eu/nui/show.do?dataset=hlth_silc_02&lang=en
- ↑ The direction of the axis is to be read as follows: the lower the values the better – low proportions of “low life satisfaction” and of “happy none or little of the time” are positive
- ↑ E. Diener, Guidelines for National Indicators of Subjective Well-Being and Ill-Being
- ↑ e.g. Lévy-Garboua 2007, Holländer 2001
- ↑ For an overview see Klemke, Elmer Daniel. "The meaning of life." (2000)
- ↑ Etymologically, eudaimonia consists of the words "eu" ("good") and "daimōn" ("spirit"). It is a central concept in Aristotelian ethics where it was used as the term for the highest human good.
- ↑ Nussbaum 1986
- ↑ http://ec.europa.eu/eurostat/statistics-explained/index.php/Glossary:Treaty_on_European_Union
- ↑ Council of the European Union, 2006
- ↑ Euopean Commission, 2009
- ↑ http://www.google.at/url?sa=t&rct=j&q=&esrc=s&source=web&cd=1&ved=0CCUQFjAA&url=http%3A%2F%2Fwww.stiglitz-sen-fitoussi.fr%2Fdocuments%2Frapport_anglais.pdf&ei=nKL9VMP2C8PyPI3dgJAB&usg=AFQjCNGGNUiuOiyL98AV3smKWiuucnl1sA&bvm=bv.87611401,d.ZWU&cad=rja
- ↑ http://ec.europa.eu/eurostat/web/ess/about-us/measuring-progress
References
- Diener, E.D. & Tov, W (2011). National accounts of well—being. KC Land, AC Michalos 8, 137-158
- Tinkler, L und Hicks, S. (2011). Measuring Subjective Well-being. London: Office for National Statistics
- Oguz, S., Merad, S. & Snape, D. (2013). Measuring National Well-being – What matters most to Personal Well-being? Office for National Statistics, London http://www.ons.gov.uk/ons/dcp171766_312125.pdf
- Burchardt, Tania (2003): Identifying adaptive preferences using panel data: subjective and objective income trajectories. Paper prepared for 3rd Conference of the Capability Approach. 7.-9. September 2003, Pavia
- Baber, H. E. (2007). Adaptive preference. Social Theory and Practice 33 (1):105-126
- Teschl, M., & Comim, F. (2005). Adaptive preferences and capabilities: some preliminary conceptual explorations. Review of social economy, 63(2), 229-247
- Sacks W. D., Stevenson, B. &Wolfers, J. (2010). Subjective Well-being, Income, Economic Development and Growth, NBER Working Paper No 16441, National Institute of Economic
- Boarini, R., Comola, M., Smith, C., Manchin, R. & de Keuenaer, F. (2012). What Makes for a Better Life?: The Determinants of Subjective Well-Being in OECD Countries – Evidence from the Gallup World Poll. OECD Statistics Working Papers, 2012/03, OECD Publishing http://dx.doi.org/10.1787/5k9b9ltjm937-en
- Cárdenas, M. & Mejía, C. (2008). Education and Life satisfaction: Perception or Reality? Draft Paper, Universitá degli Studi di Napoli Parthenope
Research
- Salinas-Jiménez, M.M., Artés. J. & Salinas-Jiménez, J. (2010). Education as a Positional Good: A Life Satisfaction Approach. Social Indicators Research, 103(3), 409-426
- Cuñado, J. & F. Pérez-de-Gracia (2012). Does Education Affect Happiness? Evidence for Spain. Social Indicators Research, 108(1), 185-196
- Gong, H., Cassels, R. & Keegan, M. (2011). Understanding Life Satisfaction and the Education Puzzle in Australia: A profile from HILDA Wave 9. NATSEM Working Paper 11/12 http://www.natsem.canberra.edu.au/storage/WP12%20Final%20for%20Web.pdf
- Cheung, H & Chan, A.W.H. (2009). The Effect of Education on Life Satisfaction Accross Countries. The Alberta Journal of Educational Research 55 (1), 124-136