International Journal of Psychology, 2015 DOI: 10.1002/ijop.12136

Subjective well-being and human welfare around the world as reflected in the Gallup World Poll Ed Diener1 and Louis Tay2 1

Department of Psychology, University of Utah, University of Virginia, The Gallup Organization, Charlottesville, VA, USA 2 Department of Psychological Sciences, Purdue University, West Lafayette, IN, USA

W

e present data on well-being and quality of life in the world, including material quality of life such as not going hungry, physical health quality of life such as longevity, social quality of life such as social support, environmental health such as clean water, equality in income and life satisfaction, and levels of subjective well-being (SWB). There are large differences between nations in SWB, and these are predicted not only by economic development, but also by environmental health, equality and freedom in nations. Improving trends in SWB are seen in many countries, but declining SWB is evident in a few. Besides average differences in SWB between nations, there are also large disparities within many countries. We discuss the policy opportunities provided by national accounts of SWB, which are increasingly being adopted by many societies. They provide the opportunity to inform policy deliberations with well-being information that reflects not only economic development, but also other facets of quality of life as well. National accounts of SWB reflect the quality of life in areas such as health, social relationships and the natural environment, and therefore capture a broader view of societal well-being than afforded by measures of economic progress alone. Keywords: Well-being; International; Happiness; Social indicators; Quality of life.

There are four major goals of the present paper: (1) To give a current update on levels of subjective well-being (SWB) and quality of life around the globe, using the largest and most representative sample of the world’s population to date. (2) To analyse trends in SWB and quality of life over recent years; are things improving or deteriorating? Whereas most articles on world well-being have been based on cross-sectional analyses, we include trends over time for various quality of life variables. Although a number of papers have been published using the Gallup World Poll (e.g., Diener, Kahneman, Tov, & Arora, 2010), to the best of our knowledge this is the first to examine trends in various dimensions of quality of life over time. (3) To determine the degree measures of SWB can capture facets of quality of life that economic measures do not reflect. Does SWB reflect aspects of quality of life that measures of societal income do not fully reflect?

(4) To present the case for including measures of SWB in the accounts of the quality of life of nations. We also present the substantial progress to date in the adoption of measures of SWB by nations. There is increasing interest in nations and organisations in national accounts of well-being, as societies seek not only economic and material progress but also progress in the realm of subjective, environmental and social well-being (Diener, Lucas, Schimmack, & Helliwell, 2009; Diener & Seligman, 2004; Oishi & Diener, 2014). The “Stiglitz commission,” also sometimes labelled the “Sarkozy commission,” was appointed by the president of France, Nicolas Sarkozy (Stiglitz, Sen, & Fitoussi, 2009) and was composed primarily of economists. The commission strongly suggested that measures beyond economic ones are needed to capture the well-being of societies. Our analysis of the quality of life in nations is in accord with their recommendations, which call for the use of multiple indicators to capture various facets of quality of life in societies. In addition

Correspondence should be addressed to Ed Diener, Department of Psychology, University of Virginia, Charlottesville, VA, USA. (E-mail: [email protected]). The authors wish to thank the Gallup Organization for the Gallup World Poll data. Their leadership in obtaining worldwide data on well-being has greatly advanced the science of well-being and quality of life.

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to objective indicators, the commission recommended the inclusion of subjective indicators such as SWB. SWB is defined as people’s evaluations of their lives, and consists of cognitive and affective components, such as life satisfaction, positive feelings and low negative feelings (Diener, 1984; Diener, Sapyta, & Suh, 1998). Based on the idea of capturing societal well-being by assessing multiple and partially independent dimensions of quality of life, we assessed six broad categories: (1) SWB—life satisfaction, positive feelings and low negative feelings (2) Economic and material well-being (3) Physical health—longevity and lack of illnesses (4) Social and institutional well-being—factors such as social support, low corruption, honest elections and respect for others (5) Quality of the natural environment—clean air, clean water and preserving the environment (6) Equality—moderate and fair disparities in income and life satisfaction Using these categories of well-being we seek to present an empirical review of several key questions: What is the quality of life in the world and is it improving or worsening? How are specific nations doing—the best, the worst and the average? Are people happy with their lives, and what societal characteristics predict this? Do factors beyond economic development predict SWB? Each of our six facets of quality of life is discussed as an important aspect of well-being in the Stiglitz et al. (2009) commission report. Although there are other aspects of flourishing beyond those we used (e.g., spirituality, leisure and mastery), the six categories we used provide a broad overview of several of the most important dimensions of well-being and quality of life. The period we examined was from 2005 to 2013, based on the availability of representative samples of the world during that period using the Gallup World Poll (GWP). This period experienced a significant worldwide economic downturn, as well as turbulence within some nations. At the same time there were notable advances such as the spread of the internet and overall economic development in many of the poorest nations. Two broad conclusions are clear in our findings: (a) Vast differences in well-being continue to exist both within and between nations, with the lowest individuals and societies continuing to be of concern, and (b) Many trends are improving, but a few trends crept in a negative direction. METHOD Sample To assess our six categories of well-being we primarily drew on indicators from the GWP, a survey of SWB

and other indicators that has been conducted from the year 2005 to the present and covers 98% of the world’s population. Countries were sampled so as to represent the population of each nation. The samples drawn from the years 2005 through 2013 includes 164 nations, with a total sample size of 1,229,431. Thus, this is the largest and most representative sample of the world yet presented. Many of our analyses included fewer nations because not all countries were surveyed on the variables of interest in all years. Table 1 presents the number of nations for each variable we included. Further information on the GWP can be found on the website of the Gallup Organization. Quality of life variables We drew on relevant survey variables from the GWP that were polled across most nations as well as on other sources that report facets of the six categories of well-being. Each category of quality of life was represented by a number of variables: economic and material well-being (9), physical health (2), social and institutional well-being (6), environmental quality (3), SWB (5) and equality (2). The list of 27 variables and response formats is presented in Table 1. Gross Domestic Product per capita (GDP per capita), adjusted for purchasing power parities and converted to USA dollars was obtained from the World Bank. Annual household income from the GWP was converted from the local currency into international dollars based on the World Bank’s individual consumption purchasing power parity conversion factor so that national income could be compared across countries. Measures of GDP per capita and household income (from the GWP) were log-transformed for the regression analyses (because we were interested in the extent other variables predicted SWB above and beyond income). Life expectancy at birth indicates the average number of years of life expected for people born that year in the nation. Life expectancy data were obtained from the World Bank World Development Indictors, supplemented with more recent data from the CIA Factbook. Concerning the SWB variables, cognitive well-being—namely, life satisfaction—was measured using Cantril’s self-anchoring ladder (1965), and ranged from 0 (worst life you can imagine for yourself) to 10 (best life you can imagine for yourself). Positive and negative feelings reflected more immediate experiences (feeling emotions such as sadness or enjoyment much of yesterday). Equality was analysed using the Gini coefficient, which is a statistic frequently used by economists. A Gini coefficient of 0 indicates complete equality within a nation and a Gini of 1.0 means that a single individual possesses all of that resource and all other people are at zero. We computed Gini coefficients for annual household income and for life satisfaction. © 2015 International Union of Psychological Science

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TABLE 1 Nation-level welfare: descriptive statistics

Nation characteristics

N

Economic and material quality of life Annual household income 163 (GWP: International Dollars) GDP Per Capita (World Bank: 157 US Dollars) Does your home have access to 163 the Internet? (1 = Yes; 0 = No)

Mean

Lowest nation

15,672

1,080 Burundi 196 Burundi 0.00 Burundi, Burkina Faso 0.02 Burundi

13,040 0.33

Does your home have Television? (1 = Yes; 0 = No)

163

0.80

Does your home have Electricity? (1 = Yes; 0 = No) Does your home have a Computer? (1 = Yes; 0 = No)

146

0.83

149

0.36

Have there been times in the past 12 months when you or your family have gone hungry? (1 = Yes; 0 = No) Have there been times in the past twelve months when you did not have enough money to buy food that you or your family needed? (1 = Yes; 0 = No) Have there been times in the past 12 months when you did not have enough money to provide adequate shelter or housing for you and your family? (1 = Yes; 0 = No) Physical health Do you have any health problems that prevent you from doing any of the things people your age normally can do? (1 = Yes; 0 = No) Life expectancy at birth (years)

135

Healthy environment In your country, are you satisfied or dissatisfied with efforts to preserve the environment? (1 = Satisfied; 0 = Dissatisfied) In the city or area where you live, are you satisfied or dissatisfied with the quality of air? (1 = Satisfied; 0 = Dissatisfied) In the city or area where you live, are you satisfied or dissatisfied with the quality of water? (1 = Satisfied; 0 = Dissatisfied) Social quality of life If you were in trouble, do you have relatives or friends you can count on to help you whenever you need them, or not? (1 = Yes; 0 = No)

Highest nation 60,928 Luxembourg 100,953 Luxembourg 0.94 Iceland

Average nation change per year

Percent average nation change per year

World average improving or declining

126.8*

0.8%

↑

574.7*

4.4%

↑

.028*

8.3%

↑

.004*

0.5%

↑

.007*

0.8%

↑

.023*

6.4%

↑

−.0003

−0.1%

↑

0.03 Burundi 0.00 Burundi

1.00 Japan, Singapore, Puerto Rico, Hong Kong 1.00 51 nations 0.95 Iceland

0.19

0.80 Liberia

0.00 Austria

162

0.32

0.82 Central African Republic

0.03 Singapore

.003*

0.9%

↓

162

0.22

0.64 Azerbaijan

0.02 Singapore

.004*

1.9%

↓

162

0.24

0.40 Georgia

0.10 Singapore

−.002*

−0.8%

↑

46.2 Sierra Leone

82.9 Hong Kong

.273*

0.38%

↑

161

69.8

162

0.51

0.14 Ukraine

0.95 Bhutan

.008*

1.5%

↑

163

0.75

0.28 Hong Kong

0.94 Ireland

.007*

0.9%

↑

163

0.68

0.25 Congo (Kinshasa)

0.98 Iceland

.005*

0.7%

↑

162

0.81

0.34 Togo

0.98 Iceland

−.003*

−0.3%

↓

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DIENER AND TAY TABLE 1 Continued World average improving or declining

Lowest nation

0.71

0.28 Cuba

0.95 Norway

.002

0.3%

↑

163

0.68

0.20 Haiti

0.98 United Arab Emirates

.006*

0.8%

↑

162

0.65

0.21 Malaysia

0.92 New Zealand

.001

0.2%

↑

157

0.51

0.1%

↑

0.76

0.94 Qatar 0.05 Singapore

.0003

156

0.14 Chad 0.97 Lithuania

.002

0.2%

↓

163

5.40

2.98 Togo

7.78 Denmark

.008

0.1%

↑

162

0.70

−0.2%

↓

0.20

0.90 Denmark 0.07

−.0016

163

0.41 Sierra Leone 0.49

−.002

−0.8%

↑

Sad much of yesterday (1 = Yes; 0 = No)

163

0.21

Iraq 0.42 Iran

−.0003

−0.1%

↑

Stress much of yesterday

162

0.29

0.66 Philippines

Finland 0.08 Taiwan, Thailand, China 0.08 Uzbekistan

.008

2.7%

↓

163

43.64

.0001

0.0%

↓

163

20.26

74.54 Rwanda 35.03 Dominican Republic

.002*

0.0%

↓

Nation characteristics

N

Mean

In your country, are you satisfied or dissatisfied with your freedom to choose what you do with your life? (1 = Satisfied; 0 = Dissatisfied) Do you believe that children in your country are treated with respect and dignity, or not? (1 = Yes; 0 = No) Is the city or area where you live a good place or not a good place to live for immigrants from other countries? (1 = Yes; 0 = No) Honesty of elections (1 = Yes; 0 = No) Is corruption widespread throughout the government, or not? (1 = Yes; 0 = No) Subjective well-being Life satisfaction ladder (0 = “Worst Possible” to 10 = “Best Possible”) Enjoyed much of yesterday (1 = Yes; 0 = No) Angry much of yesterday (1 = Yes; 0 = No)

163

Equality Income GINI (GWP) Life satisfaction GINI

Average nation change per year

Percent average nation change per year

Highest nation

27.11 Israel 8.20 Netherlands

Note: Mean levels were computed using an average of nation averages (first averaged across years). * p < .05.

FINDINGS Overall quality of life Table 1 presents the average world levels of well-being across our measures of quality of life, as well as the best and worst nation for each indicator. The averages are based on nation scores, not weighted by national population size. The table also reveals whether the overall trend across nations has been improving or declining for each indicator and at what rate (based on the proportion of the average change across nations over the average level). A quick summary of the results would be that Northern

European nations are at the top of many well-being indicators, although certainly not all and many African nations continue to reside near the bottom. In terms of material life, approximately 80% of the households in the world now have electricity and television. Access to the internet is spreading very rapidly. An encouraging trend is that longevity is increasing on average across the globe, and in almost all nations, and health problems are declining. Despite improvements in many areas, there are still troubling numbers of individuals with low levels of quality of life. For instance, 19% say they have nobody they can count on, 49% say elections are dishonest, and 29% do not feel freedom in how © 2015 International Union of Psychological Science

HAPPINESS AND HUMAN WELFARE

they live their lives. Nineteen percent said that they have gone hungry at some time during the last year. In examining the worst versus best nation for each indicator, the differences are dramatic. On some indicators a few nations have reached the upper limits—in them all people have electricity, virtually nobody has gone hungry, the quality of water and air is high, and there is relative equality between individuals. Despite recent economic setbacks, a nation such as Iceland seems to have achieved a high quality of life for most citizens. In contrast, in some nations such as Burundi virtually nobody has electricity and life satisfaction is extremely low. In some Eastern European nations corruption is ubiquitous, and 80% of people in Liberia went hungry at some point last year. Not only do these figures show the huge differences between nations, but they also reveal the optimistic promise that it is possible for a country to achieve a very high quality of life on specific dimensions for virtually all of its citizens. In terms of quality of life the globe is one of stark contrasts, and yet the success of many nations shows that it is possible to improve. The Gini coefficients for income and life satisfaction are informative. Recall that low scores mean more equality, with zero being complete equality. Income equality is high in nations such as Sweden, and inequality prevails in other nations such as Rwanda. Nations also differ in equality of life satisfaction, but equality within nations is much higher here. A few nations such as the Netherlands are close to complete equality when it comes to life satisfaction. It seems as though there might be equalising factors for life satisfaction that to some degree overcome the disparities in income, making people more equal on life satisfaction than they are on income.

Figure 1. Declining well-being over time in three nations.

© 2015 International Union of Psychological Science

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Trends: Changes from 2006 to 2013 Table 1 also presents the amount of change on the variables across time. During the period we analysed the world has improved on most measures and significantly declined on only a few. Despite the world economic downturn in 2009, notable advances were made in income and material resources. People perceived the quality of the natural environment to be improving, and there were very large increases in access to computers and the internet. There was a small but significant downward trend in social support. Although there was a small downward trend in enjoying life and an increase in stress, none of the SWB variables changed significantly during the 7-year period. Annual increases in internet use were dramatic. The global economic downturn hurt economic growth, but household income nevertheless increased over this period. We are in a period where long-term economic growth is occurring in the world. Despite economic growth, people reported that affordable food and housing became more difficult. One possible explanation is that the poor were hurt more by the downturn than were the affluent, and they benefited less from the long-term economic growth. Figure 1 presents the trends in income, feelings of freedom, going hungry and several forms of SWB for a few selected nations that experienced substantial difficulties over the period we examined. We selected these three nations because they have received much world attention recently, due to political and economic upheavals. The figure reveals that although Greece declined in income after 2008, two of the nations increased in income. Furthermore, Greece at the end of 2013 was approximately

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DIENER AND TAY TABLE 2 Cross-sectional correlations of SWB and facets of quality of life of nations Subjective well-being LS

Economic and material quality of life Annual income .75** GDP .72** Have Internet .72** Have television .61** Have electricity .62** Have computer .78** Hungry −.58** No food −.72** No shelter −.63** Health problems −.43** Life expectancy .71** Healthy environment Environment preserved .26** Good air quality .23** Good water quality .66** Social quality of life Count on others .68** Corruption −.43** Freedom .53** Children respected .20** Immigrants treated well .34** Honest elections .39** Equality LS GINI −.71** Annual income GINI −.44**

Enjoy

Angry

Sad

Stress

(.10) (.20) (.43) (.45) (.27) (−.33) (−.39) (−.39) (−.25) (.42)

.35** .34** .23** .16** .29** .33** −.22** −.30** −.35** −.26** .28**

(.06) (−.15) (.00) (.15) (−.15) (−.13) (−.07) (−.19) (−.14) (.08)

−.16** −.16** −.06 .09** .00 −.03 .20** .08* .16** .08** .01

(−.03) (.14) (.18) (.02) (.23) (.21) (−.02) (.10) (.04) (.14)

−.21** −.18** −.12** .07* −.06 −.18** .29** .23** .25** .20** .01

(.07) (.16) (.19) (.05) (.25) (.25) (.12) (.16) (.13) (.20)

.24** .25** .31** .27** .22** .39** .11 −.16** −.17** −.27** .36**

(.03) (.19) (.19) (.09) (.31) (.32) (.02) (−.04) (−.18) (.27)

(.07) (.17) (.40)

.37** .44** .53**

(.30) (.42) (.41)

−.18** −.34** −.27**

(−.13) (−.31) (−.22)

−.21** −.24** −.21**

(−.15) (−.21) (−.10)

.08* −.12** .11**

(.01) (−.16) (−.04)

(.49) (.03) (.29) (−.13) (.03) (.07)

.46** −.28** .53** .14** .25** .27**

(.33) (−.07) (.44) (.01) (.11) (.12)

−.29** .16** −.37** −.10** −.29** −.19**

(−.26) (.03) (−.35) (−.04) (−.26) (−.11)

−.23** .24** −.26** −.34** −.16** −.23**

(−.15) (.13) (−.18) (−.28) (−.07) (−.14)

.09** −.08* .07* −.05 −.03 .10**

(−.05) (.07) (−.05) (−.15) (−.15) (.00)

(−.51) (−.21)

−.45** −.07*

(−.33) (.10)

.33** −.09**

(.30) (−.18)

.45** .02

(.42) (−.08)

.11** −.11**

(.32) (−.01)

Note: Zero-order cross-sectional analysis was based on all years. To obtain stable correlations for each year, correlations were computed only when there were more than 10 nations. Numbers in parenthesis represent partial correlations (controlling for annual household income). * p < .05. ** p < .01.

where it was in 2006. Despite these positive income trends, there were dramatic decreases in other facets of quality of life. Thus, economic or social turbulence can decrease SWB and quality of life even if income rises. More people could not afford food, perhaps because of the distribution of income or the availability of food. Sadness and stress increased substantially and life satisfaction declined dramatically. Feelings of personal freedom also declined markedly. These nation trends show that economic indicators alone do not provide a complete account of the quality of life and well-being in nations—and at times they may even be misleading. Predictors of SWB Table 2 shows the cross-sectional correlations at the nation-level between societal characteristics and various forms of SWB. Table 3 shows the same correlations between variables based on changes over years. Thus, the first table is based on static associations and the second table shows to what degree variables change together. In Table 2 life satisfaction is associated with income and meeting basic needs such as for food and shelter, as well as material comforts such as having electricity and a

television. Having social support is also correlated with life satisfaction. Partial correlations are also shown in Table 2, which reveal the degree to which the measures of SWB are affected by quality of life variables even after household income was statistically controlled. These partial correlations indicate that life satisfaction is associated with other dimensions of quality of life beyond the effects of economic development per se. This is important because if economic development were to completely account for societal levels of SWB we would not need the latter measures. However, as can be seen, many sizable partial correlations between SWB and the other dimensions of quality of life besides income reveal that SWB does reflect quality of life beyond material development. In Table 3 we show the average of year-to-year correlations of the changes between the variables. Several of the cross-sectional correlations are replicated in the change data in Table 3, and also replicate across different time periods. In the table we highlight those instances where the average correlation was significant and also each of the correlations between adjacent years was largely in the same direction. The highlighted correlations are those that were relatively consistent across time. All of the © 2015 International Union of Psychological Science

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TABLE 3 Temporal relations: correlation of changes over all nation-waves (2006–2013) Subjective well-being LS Economic and material quality of life .11** Annual income [.00, .42] GDP .08* [−.22, .22] Have Internet .11** [−.10, .29] Have television .13** [−.09, .34] .27** Have electricity [.14, .30] Have computer .12 [.00, .22] Hungry −.30** [−.44, .22] −.30** No food [−.45, −.13] −.22** No shelter [−.35, .02] Physical health Health problems −.10** [−.24, .07] Life expectancy .02 [−.02, .08] Healthy environment .07* Environment preserved [−.04, .18] Good air quality .05 [−.08, .21] .10** Good water quality [.05, .21] Social quality of life .20** Count on others [.06, .41] −.08* Corruption [−.20, .02] Freedom .13** [−.07, .27] .12** Children respected [−.03, .29] Immigrants treated well .04 [−.05, .15] Honest elections .03 [−.15, .11] Equality −.62** LS GINI [−.73,−.46] −.10** Annual income GINI [−.17, .00]

Enjoy

Angry

Sad

Stress

.04 [−.03, .39] −.02 [−.08, .10] .06 [−.18, .20] .03 [−.10, .17] −.07 [−.06, .14] −.04 [−.18, .14] .01 [−.13, .25] −.05 [−.17, .14] −.10** [−.17, .14]

.02 [−.20, .12] −.06 [−.10, .02] −.01 [−.34, .17] .02 [−.15, .16] .04 [−.09, .20] −.07 [−.26, .09] .24** [−.11, .64] .09** [−.07, .26] .13** [−.06, .24]

−.05 [−.39, .09] −.10* [−.17, .08] −.07 [−.15, .03] −.02 [−.19, .09] −.02 [−.20, .05] .00 [−.09, .40] .21** [−.24, .63] .11** [−.08, .38] .16** [−.06, .28]

−.02 [−.12, .20] −.11* [−.36,−.07] .04 [−.10, .19] .04 [−.17, .18] .05 [−.06, .23] .23* [.11, .33] .25** [−.11, .47] .07 [−.10, .24] .10** [−.03, .42]

−.02 [−.26, .23] .01 [−.13, .09]

.11** [−.03, .24] −.02 [−.20, .07]

.10** [.08, .12] −.08* [−.14, .08]

.08* [−.18, .19] −.08* [−.44, .24]

.15** [−.01, .32] .18** [.01, .32] .13** [.03, .22]

−.03 [−.20, .10] −.16** [−.26, .00] −.08* [−.15, .13]

−.06 [−.28, .11] −.15** [−.40,−.03] −.16** [−.26,−.04]

.08* [−.05, .31] −.10* [−.22, .11] −.08* [−.17, .10]

.08* [−.06, .25] −.08* [−.22, .14] .13** [−.02, .33] .15** [−.04, .26] .08* [−.11, .34] .08* [−.04, .21]

−.16** [−.31,−.03] −.03 [−.17, .15] −.05 [−.19, .06] −.08* [−.21, .10] −.09* [−.26, .02] −.04 [−.18, .12]

−.19** [−.28,−.13] −.01 [−.13, .19] −.05 [−.31, .07] −.17** [−.32, .03] −.03 [−.22, .11] −.04 [−.22, .19]

−.15** [−.30, .05] −.04 [−.43, .07] −.01 [−.16, .29] −.05 [−.18, .16] .05 [−.45, .17] .03 [−.18, .23]

−.09* [−.24, .08] −.06 [−.15, .11]

.20** [.04, .34] .05 [−.11, .26]

.35** [.12, .44] .16** [−.18, .29]

.18** [−.01, .58] .06 [−.04, .23]

Note: The GWP has ongoing survey waves collected at times over two calendar years—but for the purpose of correspondence to external economic variables, we used the year of interview for temporal demarcation; because there were small samples for the year 2005, we focused only on temporal change from 2006 to 2013. As a measure of consistency across years, brackets represent the range (lowest, highest) of first-order difference (Timen − Timen−1 ) correlations across years: 2007, 2008, 2009, 2010, 2011, 2012 and 2013. To obtain stable correlations for each year, correlations were computed only when there were more than 10 nations. Highlighted effects show significant correlations across all nation-waves (p < .05) and relatively consistent effects (inverse correlation ≤ .05). * p < .05. ** p < .01.

© 2015 International Union of Psychological Science

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Figure 2. Cross-section association of national mean life satisfaction by annual household income. Note: Size of the circles represents the population of each nation. Although there is a declining marginal utility, with more money being required the higher the current income to make the same different to life satisfaction, the pattern here is linear because of the logarithmic scaling of income on the x axis.

highlighted correlations were also statistically significant in the cross-sectional analyses. Changes in the quality of life in terms of the social, natural environment and income equality of citizens all predict changes in life satisfaction over time. There is a clear association between life satisfaction and material progress, as well as social support in both Tables 2 and 3. Enjoying life is associated with good air quality in nations, feelings of freedom in living one’s life, and with social support, and these correlations tend to be replicated in the change correlations. Health problems, not being able to count on others, and poor air quality are associated with some forms of negative emotions, both in the cross-sectional and change analyses. Although the change correlations might appear small, it should be recalled that many factors can influence short-term change in average SWB from year-to-year, and also that the degree of stability in most of the variables is substantial, and thus changes in one year tend to be small. Figure 2 shows the association between income (on a log-scale) and average life satisfaction in nations; the correlation between raw income and life satisfaction was .73. Clearly, this shows that life satisfaction is in part a function of national income. There are no wealthy nations that are extremely low on life satisfaction, and no very poor nations that are very high on it. Despite the high correlation there are large differences in life satisfaction between countries with similar incomes. For example, Costa Rica and Syria have similar incomes, and yet one is towards the bottom and one towards the top of the distribution of life satisfaction. At the wealthy end Denmark is substantially higher than Hong Kong on life

satisfaction; at the low end of wealth Togo is substantially lower than Burundi on life satisfaction. Thus, although income is important to life satisfaction, other factors such as conflict also substantially influence quality of life and are captured by measures of life satisfaction. SWB as a global indicator of quality of life Table 4 presents the correlations between the quality of life dimension mean scores averaged across years. A regression analysis revealed that although log GDP itself is a strong predictor of the composite SWB score (β = .48, p < .001; R2 = .70), other facets of well-being significantly predict SWB beyond income: Health β = .18, p < .01; Environment β = .20, p < .001; and Equality β = .20, p < .001. The incremental R2 was .09, meaning that about an additional 9% of the variance in SWB could be accounted for by other quality of life dimensions. Thus, we again see that SWB scores capture more facets of quality of life than just economic development. Table 5 presents a regression in which change scores across the years are used to predict changes in SWB. Specifically, we focused on key indicators that were found to predict life evaluations over time. As can be seen, these predictions of changes in SWB confirm the conclusions of the cross-sectional regression analysis reported above. Social support, freedom, water quality and income inequality all predict changes in SWB beyond the effects of changes in income. These variables incrementally accounted for 9% of the changes in SWB beyond changes in income. What the regression analyses clearly © 2015 International Union of Psychological Science

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TABLE 4 Correlations between six dimensions of quality of life Six dimensions of quality of life Composite material

Composite health

Composite en vironment

Composite social

Composite SWB

Composite equality

1.00 .86** .42** .64** .34** .77**

1.00 .41** .53** .26** .68**

1.00 .73** .51** .32**

1.00 .50** .48**

1.00 .33**

1.00

Composite material Composite health Composite environment Composite social Composite SWB Composite equality Note: * p < .05. ** p < .01.

TABLE 5 Predicting life satisfaction changes using changes in key variables Dimensions of well-being predictive over log-household income

Variables Intercept Log-household income Water quality (1 = Good; 0 = Poor) Social support Freedom Income inequality Pseudo-R2 Δ R2 beyond material progress

Material progress

Healthy environment

Social quality of life

Equality

Combined

−0.006 0.469*** — — — — 0.023 —

−0.007 0.418** 0.55* — — — 0.053 0.026

0.000 0.395** — 1.209*** 0.486* — 0.083 0.060

−0.008 0.554*** — — — −0.843** 0.033 0.010

−0.003 0.444** 0.394† 1.130*** 0.433* −0.603* 0.111 0.088

Note: Results were based on crossed-nested modelling accounting for nation and temporal nesting. Pseudo-R2 was calculated using proportion of residual variance accounted for beyond the null model. † p < .10. * p < .05. ** p < .01. *** p < .001.

demonstrate is that SWB captures facets of quality of life beyond economic development. Individual nations Table 6 presents the individual nations and their scores, listed from highest to lowest in overall quality of life, with the scores all being calibrated to a 0–100 metric. For the Gallup survey items the transformation to a 100-point scale required a straightforward multiplication of the scales. For household income, we used zero income to be zero on our scale, and the highest income of $60,928 (Luxembourg) to equal 100. We did not include GDP per capita to avoid double counting income. It is important to note that the scores for each nation are not standardised against other nations. All nations could receive a high or low score because the values are not relative to the set of nations. The average scores shown in the rightmost column are based on an average of the six quality of life composite scores. As can be seen, for the dimensions of well-being no nation scores at 100, and none are close to zero. Thus, despite excellent conditions in some nations and terrible conditions in others, no nation is either as bad or as good as it might be. There is room for improvement even in the best nations. The table reveals that Scandinavian nations © 2015 International Union of Psychological Science

tend to score quite highly whereas a number of African nations tend to have lower scores. ON WEALTH AND POVERTY IN NATIONS Around the world there is now widespread concern about poverty and inequality. However, both of these are usually computed based on income, although there are exceptions such as the United Nations Development Program’s (UNDP) Human Development Index, which takes into account education and health in addition to income. However, the other UNDP factors that are considered correlate very highly with income, and therefore add only marginal amounts in assessing nation differences in quality of life. We propose a broader definition of quality of life, in which the six facets of quality of life we enumerated are all considered. A full discussion of quality of life must include, for instance, whether individuals have social support, clean water to drink, freedom and life satisfaction, as well as sufficient income to meet basic needs. If we examine the nations in Table 6 we can see that some nations such as in Northern Europe are high on all aspects of quality of life. In contrast, some nations have quality of life resources in certain categories that are greater than their quality of life resources in other dimensions. For instance, the UAE is stronger in social

10

DIENER AND TAY TABLE 6 Composite scores for dimensions of well-being for each nation

Nation Iceland Norway Switzerland Denmark Luxembourg Sweden Singapore Netherlands Australia New Zealand Austria Finland United Arab Emirates Canada Ireland United Kingdom Qatar Belgium Germany United States France Kuwait Japan Czech Republic Slovenia Bhutan Spain Taiwan Hong Kong Malaysia Thailand Bahrain Costa Rica Malta Saudi Arabia Uzbekistan Uruguay Israel Italy Mauritius Slovakia China Portugal Poland South Korea Laos Cyprus Venezuela Panama Estonia Vietnam Suriname Croatia Indonesia Jordan Hungary Belarus Latvia Mexico Libya

Material/economics

Physical health

Healthy environment

Social

SWB

Equality

Average

94.7 94.8 90.5 92.9 94.8 93.0 89.9 90.9 91.7 88.1 86.8 86.2 87.4 90.5 85.2 87.8 81.9 83.6 86.6 89.8 82.4 89.9 85.5 77.6 82.2 54.2 77.8 85.9 87.9 65.3 62.3 75.7 61.2 82.1 74.7 52.6 63.8 80.4 75.0 62.0 73.7 63.2 74.4 72.3 84.1 49.8 75.2 59.0 56.4 69.5 57.5 55.3 72.0 51.2 63.3 67.1 61.3 66.8 56.7 62.2

90.2 86.3 89.7 84.5 88.3 87.8 93.9 86.5 89.5 89.6 88.7 86.4 89.3 88.8 91.3 88.8 91.3 85.5 85.8 86.3 90.2 85.7 91.1 84.3 84.0 83.5 90.1 90.8 90.9 82.5 83.2 85.1 86.8 88.8 84.5 74.3 85.1 88.9 91.5 79.4 82.2 86.2 84.7 80.2 87.4 80.5 87.5 84.8 87.2 80.4 83.9 81.4 83.1 82.4 89.3 80.6 75.8 79.4 85.9 83.3

84.3 82.1 84.3 84.2 84.3 82.5 90.6 81.1 81.2 85.8 82.8 82.8 86.7 76.6 82.1 82.9 88.6 74.4 83.2 76.0 72.0 64.7 67.8 73.0 75.3 89.3 66.1 58.5 49.5 76.2 80.9 74.0 79.8 60.1 64.4 81.0 82.0 56.7 60.6 85.6 67.7 75.7 75.7 68.0 64.0 82.0 63.7 67.0 69.0 69.1 70.4 77.9 67.6 72.0 60.3 65.4 63.5 67.9 65.6 63.8

90.1 93.3 93.0 91.3 93.2 88.8 88.9 89.7 92.3 89.0 88.9 91.8 92.5 91.5 91.3 85.5 92.2 90.0 79.7 83.5 87.0 86.8 79.3 85.8 84.2 89.3 88.0 78.4 89.4 87.8 84.3 90.7 81.7 89.3 80.5 92.3 75.6 75.4 79.9 82.2 81.1 86.3 78.9 81.2 66.7 85.4 77.4 78.7 75.2 71.3 85.0 72.2 68.4 79.7 79.0 76.7 81.1 69.4 69.1 73.5

82.5 81.0 79.1 84.0 74.4 81.4 73.4 82.6 77.8 77.9 79.4 79.6 74.1 77.3 77.6 78.0 69.4 76.6 76.9 74.3 72.5 75.7 75.2 73.9 71.6 74.7 69.4 78.5 70.5 77.1 79.9 60.6 77.7 64.6 72.8 80.3 75.9 69.3 68.9 69.8 69.8 75.3 67.7 73.1 72.5 76.1 67.9 79.2 79.6 75.0 69.5 74.1 69.4 77.7 66.1 68.2 72.3 71.4 76.7 66.4

77.8 78.5 77.6 77.0 77.9 78.8 74.2 78.0 73.8 73.7 76.3 76.0 71.7 74.2 71.3 70.4 67.7 76.9 73.5 72.5 76.6 74.7 74.3 76.1 71.7 75.4 74.3 73.4 72.7 70.9 68.6 72.2 70.4 68.3 75.0 71.4 69.1 79.9 74.5 70.9 75.0 61.8 67.0 72.3 71.1 68.5 70.1 71.6 69.7 70.3 69.0 74.1 73.2 69.9 72.2 71.3 75.1 72.1 70.0 74.4

86.6 86.0 85.7 85.7 85.5 85.4 85.2 84.8 84.4 84.0 83.8 83.8 83.6 83.1 83.1 82.2 81.8 81.2 80.9 80.4 80.1 79.6 78.9 78.5 78.1 77.7 77.6 77.6 76.8 76.6 76.5 76.4 76.3 75.6 75.3 75.3 75.2 75.1 75.1 75.0 74.9 74.7 74.7 74.5 74.3 73.7 73.7 73.4 72.9 72.6 72.6 72.5 72.3 72.2 71.7 71.5 71.5 71.2 70.6 70.6

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TABLE 6 Continued Nation Argentina Sri Lanka Trinidad & Tobago Belize Brazil Myanmar Kazakhstan Montenegro Chile Lithuania Tunisia Paraguay Jamaica Algeria Greece Puerto Rico Kosovo Guyana Colombia Kyrgyzstan Macedonia Tajikistan Djibouti Bangladesh Ecuador Cambodia Nicaragua Morocco Guatemala Bulgaria Nepal Philippines El Salvador India Bolivia Mongolia Ethiopia South Africa Azerbaijan Dominican Republic Botswana Honduras Iran Bosnia and Herzegovina Albania Rwanda Romania Russia Serbia Turkey Ghana Senegal Moldova Swaziland Peru Mauritania Georgia Syria Lebanon Kenya

Material/economics

Physical health

Healthy environment

Social

SWB

Equality

Average

64.7 43.7 59.4 60.5 62.9 39.9 57.0 67.2 63.5 65.3 61.4 55.0 57.4 63.6 69.3 64.0 64.8 58.4 56.3 48.7 65.6 47.7 48.4 43.7 52.8 32.5 47.0 57.9 51.2 63.4 46.6 36.2 49.2 47.2 50.2 51.2 33.5 47.6 42.5 48.3 39.0 43.3 59.5 64.9 58.2 28.3 59.8 62.6 64.9 58.3 37.5 41.2 54.1 46.6 49.2 40.9 45.5 56.1 67.0 31.4

84.9 76.8 81.0 84.9 83.2 77.2 76.8 82.6 84.9 80.5 82.5 83.2 83.7 83.3 89.1 82.5 82.1 76.9 84.6 76.2 83.5 75.7 73.9 76.8 84.0 72.5 82.4 81.8 83.3 79.6 76.2 76.5 84.0 77.2 76.7 75.9 76.5 70.3 78.7 83.3 64.9 82.9 82.9 81.1 84.2 74.3 79.2 74.4 80.3 83.2 70.9 75.7 75.9 61.7 82.1 73.9 74.7 87.2 87.0 75.5

60.8 80.6 64.8 59.1 65.7 84.4 52.7 61.2 61.8 58.3 54.9 68.4 67.9 59.5 54.5 51.8 52.6 57.7 66.1 64.5 57.2 67.0 62.5 79.0 62.0 83.6 72.1 64.0 65.1 51.8 75.3 81.9 63.2 69.3 68.7 47.8 74.5 65.1 56.8 64.8 70.6 66.7 64.9 55.9 46.2 80.0 55.0 39.4 47.1 56.9 65.7 51.6 49.1 65.2 55.7 51.2 62.7 52.4 38.3 62.4

62.5 82.7 72.5 69.7 62.5 77.3 79.7 69.6 66.1 63.8 76.1 60.0 68.7 69.1 61.6 72.3 66.4 71.9 61.2 71.3 67.9 75.5 77.2 66.8 64.3 86.7 67.5 67.7 60.7 69.6 59.9 81.7 60.1 67.1 63.2 72.8 71.4 75.8 72.2 69.5 85.6 63.4 68.0 54.7 67.9 81.6 61.3 61.2 59.9 53.3 74.3 68.5 60.6 73.4 54.9 65.8 65.5 69.7 56.2 70.4

76.8 67.0 77.5 71.2 75.7 74.6 77.2 65.1 73.1 70.9 64.6 80.3 74.1 66.3 64.5 75.9 74.1 66.9 72.4 76.0 63.4 70.1 74.4 70.3 71.9 65.7 71.4 67.5 74.1 68.2 73.5 59.2 72.2 68.0 66.2 75.8 72.2 73.7 69.0 68.1 71.6 72.9 53.5 65.2 65.6 71.3 65.6 75.7 62.9 57.1 69.9 73.0 70.4 71.1 67.2 74.9 65.9 50.9 59.2 73.2

72.5 70.4 65.9 75.2 68.3 63.4 72.7 69.9 66.1 72.7 71.7 64.3 59.5 69.3 72.1 62.8 67.0 74.7 65.5 69.1 67.9 69.2 68.0 67.6 68.5 62.1 62.1 61.6 65.8 66.7 66.9 61.7 67.9 67.1 69.3 69.9 65.2 58.8 71.4 56.4 57.7 60.0 60.2 66.7 65.5 51.6 65.4 71.3 68.9 71.5 61.2 69.3 69.1 60.7 67.3 69.7 62.0 59.8 68.1 62.3

70.4 70.2 70.2 70.1 69.7 69.5 69.4 69.3 69.2 68.6 68.5 68.5 68.5 68.5 68.5 68.2 67.8 67.8 67.7 67.7 67.6 67.5 67.4 67.4 67.3 67.2 67.1 66.7 66.7 66.6 66.4 66.2 66.1 66.0 65.7 65.6 65.5 65.2 65.1 65.1 64.9 64.9 64.8 64.7 64.6 64.5 64.4 64.1 64.0 63.4 63.2 63.2 63.2 63.1 62.7 62.7 62.7 62.7 62.6 62.5

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DIENER AND TAY TABLE 6 Continued

Nation Niger Egypt Mali Mozambique Sudan Armenia Zimbabwe Malawi Pakistan Ukraine Ivory Coast Zambia Palestinian Territories Burkina Faso Nigeria Cameroon Afghanistan Yemen Uganda Comoros Gabon Madagascar Tanzania Benin Angola Iraq Congo Brazzaville Lesotho Guinea Congo (Kinshasa) Central African Republic Burundi Liberia Sierra Leone Togo Chad Haiti Cuba Oman Namibia Northern Cyprus Somaliland region Nagorno-Karabakh Republic

Material/economics

Physical health

Healthy environment

Social

SWB

Equality

Average

22.5 50.6 34.8 40.3 43.7 52.0 36.2 25.6 45.5 56.2 36.8 31.8 56.1 28.0 38.5 33.0 34.2 40.8 27.6 33.0 38.5 28.1 29.3 25.8 35.1 55.7 32.4 28.8 22.0 26.1 14.7 18.7 17.4 22.7 25.1 23.2 31.6 — 77.5 42.8 64.6 36.8 61.9

71.4 80.5 70.0 69.1 73.6 76.6 69.6 64.9 72.5 73.2 69.7 68.6 82.9 70.2 72.0 67.2 70.7 75.8 67.7 70.8 70.5 77.0 72.0 71.3 69.0 77.5 70.1 63.8 69.4 72.0 65.6 66.1 70.5 61.3 67.8 63.8 71.5 84.0 — 76.9 — — —

68.1 53.1 56.4 64.6 54.5 53.0 62.5 74.9 56.3 34.0 54.4 60.1 47.1 59.9 50.2 59.0 62.2 50.4 61.5 57.2 53.3 60.9 52.0 58.7 49.8 35.3 53.8 42.6 52.5 44.7 63.0 62.7 46.9 48.9 47.9 43.3 40.0 59.6 — 72.8 50.4 67.9 76.8

72.0 62.2 68.9 64.6 67.7 63.1 69.4 72.3 58.9 55.6 66.9 67.9 49.6 66.1 63.4 66.6 54.6 58.0 73.4 51.2 65.9 52.3 66.0 61.6 57.7 49.7 58.5 71.4 57.1 49.2 53.4 43.6 60.5 59.9 48.3 49.5 37.2 79.5 — 78.5 70.3 80.5 78.9

74.8 58.7 77.7 69.3 66.2 59.3 70.8 72.0 65.4 73.0 71.1 72.1 57.2 69.0 68.8 68.1 66.9 63.0 65.3 72.9 65.7 68.0 69.5 68.5 65.7 50.0 66.0 75.6 68.9 69.8 68.7 70.6 62.3 56.5 59.5 66.9 61.5 70.0 — — 54.8 78.2 60.1

66.0 66.4 63.3 62.7 64.2 65.3 59.2 55.6 66.1 70.6 61.9 59.4 66.8 63.8 63.9 62.8 66.9 65.7 58.0 68.1 58.8 66.2 62.4 62.8 67.2 72.8 57.9 52.6 62.7 66.5 61.0 62.3 59.0 59.3 58.8 58.7 62.3 72.3 69.3 66.2 70.1 63.0 72.4

62.4 61.9 61.9 61.8 61.7 61.5 61.3 60.9 60.8 60.4 60.1 60.0 60.0 59.5 59.5 59.4 59.3 59.0 58.9 58.9 58.8 58.8 58.6 58.1 57.4 56.8 56.5 55.8 55.4 54.7 54.4 54.0 52.8 51.4 51.2 50.9 50.7 — — — — — —

Note: Category scores for each well-being component were based on indicators that were administered to more than 160 nations. All negatively worded items were reversed-scored (R). “Economics/Material”: Annual household income, Internet, Television, Shelter (R), Food (R); “Physical Health”: Health Problems (R), Life Expectancy; “Environment”: Environment preserved, Quality water, Quality air; “Social”: Support, Freedom, Children Respected, Good place for Immigrants; “SWB”: Life satisfaction, Enjoy, Anger (R), Sad (R), Stress (R); “Equality”: Income GINI, LS GINI.

relationships than it is in other categories. Bhutan scores highly in several categories compared to its material development score. Taiwan and Hong Kong show a different pattern, being strong in economic development and social relationships, but low in a healthy environment. Bahrain scores high in social relationships but relatively low in SWB. When we turn to nations that tend to be low in overall quality of life, we can also see differences in patterns. There are some nations such as Haiti, Togo and

Sierra Leone that score relatively low in all categories. But other nations such as Iraq score relatively high in a dimensions such as equality, but extremely low in others such as SWB and a healthy environment. Certain nations stand out for their low SWB scores (Iraq, Syria, Sierra Leone and the Palestinian Territories), and these tend to be nations that are in conflict. The Dominican Republic scores lowest on our equality index, the Ukraine lowest on a healthy environment, and Haiti lowest on social relationships. Thus, the facets help us pinpoint © 2015 International Union of Psychological Science

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quality of life that goes beyond economic development alone. Some might question whether equality is a necessary facet of quality of life. It can be argued that only equality of opportunity, or fairness, is a widespread value, and it does not require equality of outcomes. A thorough discussion of the philosophical, political and economic issues related to equality is beyond the scope of this paper. However, several considerations are worth noting. The Stiglitz et al. (2009) commission states that in assessing the quality of life in societies, an integral part of the assessment must be to examine not just mean levels but inequalities as well. Income inequality appears to be growing in economically developed nations, and there are concerns expressed about it. It is noteworthy that in our study equality, both of income and life satisfaction, is associated with higher average SWB. This is true both in the cross-sectional analyses and in the change-over-time analyses. These findings suggest that more equal societies tend to be happier societies (for a range of findings, see Diener, Diener, & Diener, 1995; Alesina, Di Tella, & MacCulloch, 2004; Oishi, Kesebir, & Diener, 2011). THE BENEFICIAL EFFECTS OF SOCIETAL SWB There are a number of reasons to monitor the SWB of nations. As described above, the measures of SWB mirror a number of facets of quality of life in addition to economic development, and therefore present information that complements the economic indicators. In addition, it is becoming increasingly clear that SWB should be monitored because it not only reflects quality of life, but increases several beneficial aspects of quality of life such as physical health. There is now a substantial amount of supportive evidence for the conclusion that high SWB is generally beneficial—to health and longevity, productivity and citizenship and supportive social relationships. There are now a number of reviews available—based on experimental, longitudinal and other types of research that indicates that SWB helps to improve aspects of life such as relationships and health (DeNeve, Diener, Tay, & Xuereb, 2013; Diener, Kanazawa, Suh, & Oishi, in press; Lyubomirsky, King, & Diener, 2005). Diener and Chan (2011) reviewed studies showing that happier individuals are both healthier and live longer on average. Although the majority of data are at the individual level, some data indicate that the beneficial findings generalise to the SWB of groups. For example, Lawless and Lucas (2011) found that places with higher SWB also have lower rates of mortality from heart disease, homicide, liver disease, diabetes and cancer. High SWB seems to have benefits for outcomes as diverse as fertility, stable and rewarding marriages, altruistic behaviour and immune function (Diener et al., in press). There are © 2015 International Union of Psychological Science

13

not mere associations in that the evidence is growing that SWB has a beneficial causal role for many desirable outcomes. Thus, an important reason to monitor the SWB of societies is that it influences and causes other good outcomes that people everywhere value. NATIONAL ACCOUNTS OF WELL-BEING In terms of assessing quality of life in the world an important development about which readers should be aware is national accounts of SWB. In 2000 Diener proposed that societies create accounts of SWB to parallel economic accounts and other social indicators. The proposal was based on the idea that nations that were monitoring well-being could craft better policies because the accounts would reveal aspects of quality of life in societies that influence people’s SWB, but which the economic accounts do not fully reflect. SWB measures have been found to be valid and reliable (Diener, Inglehart, & Tay, 2013a). They reflect important societal conditions such as economic factors (Diener, Tay, & Oishi, 2013b), corruption levels (Tay, Herian, & Diener, 2014), freedom (Inglehart, Foa, Peterson, & Welzel, 2008) and pollution (Welsch & Kuhling, 2009). As described above, SWB tends to increase the prevalence of health and longevity, social quality of life, citizenship and productivity at work. Thus, not only does SWB reflect facets of quality of life, but it tends to increase some of them. Since Diener’s (2000) proposal much progress has been made, with over 40 nations conducting some measurement of SWB. The Organization of Economic Cooperation and Development, which helps nations coordinate their statistical collection, has issued guidelines for societal measures of SWB. The National Academy of Sciences of the USA issued a report on measures of SWB related to time use, which was largely favourable. David Cameron, the Prime Minister of the United Kingdom, announced in 2010 that his nation would monitor SWB as input to policy. As noted earlier, the Stiglitz et al. commission, comprised primarily of economists, called for broad indicators of quality of life, including subjective ones, going beyond traditional economic indicators. Thus, there is now some momentum for adoption of societal measures of SWB. Because the accounts of SWB can reveal the beneficial effects of programs and policies that psychologists often advocate, they should be used as a tool to examine and advocate for certain policy alternatives. Our analyses reveal that SWB scores do capture information about quality of life that is not contained in economic measures. If the policies advanced by psychologists enhance quality of life in societies this ought to be captured by the SWB measures. Thus, psychologists can analyse SWB data to help demonstrate the effectiveness of the programs they advocate.

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DIENER AND TAY

CONCLUSIONS AND THE FUTURE Several conclusions emerge from our findings: (1) In most areas the human world has improved over recent years. Economies have grown despite the world recession, and people have greater access to electricity, computers and the internet. Longevity has risen and people perceive that their natural environments are improving. Even most of the poorest nations in the world have improved in terms of economic development. (2) Despite these positive trends, in some areas the world has declined. For example, people feel slightly less that they can count on others, and corruption has increased slightly. Thus, despite positive economic trends certain social indicators turned slightly downward. (3) Economic success appears to be relevant to life satisfaction in nations, but other variables are important to SWB as well. Nations in which people can count on others and feel respected, as well as those that are relatively low in conflict, are happier. Several nations that have seen notable conflict within the past decade have declined markedly in SWB. (4) National accounts of well-being are spreading, with increasing numbers of nations adopting measures of SWB. This provides an opportunity that thus far has been overlooked by most psychologists. The accounts of well-being can help reveal the benefits of programs and policies that are often advocated by psychologists, such as broader treatment for mental illness, and programs to counter discrimination and bullying. To the extent that the programs advocated by psychologists improve people’s lives this ought to be revealed in the accounts of well-being. For example, Richard Layard (Layard & Clark, 2014), an economist in the United Kingdom and a member of the House of Lords there, published a book arguing that expansion of mental health programs can substantially raise the SWB of societies, perhaps more than any other program. Psychologists ought more frequently to use the accounts of SWB to confirm the beneficial outcomes of the programs they propose. Thus far economists are the social science that has dominated policy discussions, and they are the most frequent users of SWB measures in analysing policy issues. It is time for psychologists to step forward and provide greater input to policy deliberations. Another reason to advocate for national accounts of SWB is that it is beneficial to the health, productivity and social relationships of societies. SWB should be monitored for this reason alone. One challenge for nations is to have economic growth without endangering the environment, and also without

lowering enjoyment of life and social cohesion. Because stress seems to be high in economically developed nations (Ng, Diener, Aurora, & Harter, 2009), a challenge is to create economic growth without extremely high levels of stress. Along these lines, it will be important to distinguish the different types of stress that individuals experience: “eustress” to meet challenges or “distress” that impairs functioning. Progress includes more than economic growth and national accounts of SWB are a useful way to assess citizen’s evaluations of overall progress in the quality of life in their societies. The Stiglitz et al. (2009) commission recommended that multiple measures of quality of life be used. In this paper we took this recommendation to heart and presented levels of well-being in nations using six composite indicators. Thus, we presented an integrated overview of well-being in the world that includes both subjective indicators of well-being and dimensions of quality of life such as economic development, a healthy natural environment and supportive social relationships. By measuring the various facets of quality of life we will be better able to craft policies to improve them. Manuscript received September 2014 Revised manuscript accepted December 2014

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