Social Environments for World Happiness

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Introduction only raises life evaluations directly but also. indirectly by providing the greatest gains for,This is the eighth World Happiness Report Its. those most in misery To do this we consider,central purpose remains as it was for the first. two main aspects of the social environment,Report to review the science of measuring and. The first is represented by the general climate,understanding subjective well being and to use. of interpersonal trust and the extent and quality,survey measures of life satisfaction to track the.
of personal contacts The second is covered by,quality of lives as they are being lived in more. a variety of measures of how much people trust,than 150 countries In addition to presenting. the quality of public institutions that set the,updated rankings and analysis of life evaluations. stage on which personal and community level,throughout the world each World Happiness. interactions take place,Report has a variety of topic chapters often 14.
dealing with an underlying theme for the report We find that individuals with higher levels of. as a whole Our special focus for World Happiness interpersonal and institutional trust fare signifi 15. Report 2020 is environments for happiness cantly better than others in several negative. This chapter focuses more specifically on situations including ill health unemployment. social environments for happiness as reflected low incomes discrimination family breakdown. by the quality of personal social connections and fears about the safety of the streets Living. and social institutions in a trusting social environment helps not only. to support all individual lives directly but also,Before presenting fresh evidence on the links. reduces the well being costs of adversity This,between social environments and how people. provides the greatest gains to those in the most, evaluate their lives we first present our analysis. difficult circumstances and thereby reduces,and rankings of national average life evaluations. well being inequality As our new evidence shows,based on data from 2017 2019.
to reduce well being inequality also improves, Our rankings of national average life evaluations average life evaluations We estimate the possible. are accompanied by our latest attempts to show size of these effects later in the chapter. how six key variables contribute to explaining,the full sample of national annual averages from. 2005 2019 Note that we do not construct our Measuring and Explaining National. happiness measure in each country using these Differences in Life Evaluations. six factors the scores are instead based on,In this section we present our usual rankings for. individuals own assessments of their subjective,national life evaluations this year covering the. well being as indicated by their survey responses,2017 2019 period accompanied by our latest.
in the Gallup World Poll Rather we use the six,attempts to show how six key variables contribute. variables to help us to understand the sources,to explaining the full sample of national annual. of variations in happiness among countries and,average scores over the whole period 2005 2019. over time We also show how measures of,These variables are GDP per capita social support. experienced well being especially positive,healthy life expectancy freedom generosity and.
emotions supplement life circumstances and,absence of corruption As already noted our. the social environments in supporting high life,happiness rankings are not based on any index. evaluations We will then consider a range of,of these six factors the scores are instead. data showing how life evaluations and emotions,based on individuals own assessments of their. have changed over the years covered by the,lives as revealed by their answers to the Cantril.
Gallup World Poll 1,ladder question that invites survey participants. We next turn to consider social environments for to imagine their current position on a ladder with. happiness in two stages We first update and steps numbered from 0 to 10 where the top. extend our previous work showing how national represents the best possible and the bottom the. average life evaluations are affected by inequality worst possible life for themselves We use the six. and especially the inequality of well being Then variables to explain the variation of happiness. we turn to an expanded analysis of the social across countries and also to show how measures. context of well being showing for the first time of experienced well being especially positive. how a more supportive social environment not,World Happiness Report 2020. affect are themselves affected by the six factors In the fourth column we re estimate the life. and in turn contribute to the explanation of evaluation equation from column 1 adding both. higher life evaluations positive and negative affect to partially implement. the Aristotelian presumption that sustained,In Table 2 1 we present our latest modeling of. positive emotions are important supports for a,national average life evaluations and measures of. good life 5 The most striking feature is the extent to. positive and negative affect emotion by country, which the results buttress a finding in psychology.
and year 2 For ease of comparison the table has,that the existence of positive emotions matters. the same basic structure as Table 2 1 in several,much more than the absence of negative ones. previous editions of the World Happiness Report, when predicting either longevity6 or resistance to. We can now include 2019 data for many countries,the common cold 7 Consistent with this evidence. The addition of these new data slightly improves, we find that positive affect has a large and highly.
the fit of the equation while leaving the coefficients. significant impact in the final equation of Table,largely unchanged 3 There are four equations in. 2 1 while negative affect has none, Table 2 1 The first equation provides the basis for. constructing the sub bars shown in Figure 2 1 As for the coefficients on the other variables in. the fourth column the changes are substantial, The results in the first column of Table 2 1 explain. only on those variables especially freedom and,national average life evaluations in terms of six. generosity that have the largest impacts on,key variables GDP per capita social support.
positive affect Thus we infer that positive,healthy life expectancy freedom to make life. emotions play a strong role in support of life,choices generosity and freedom from corruption 4. evaluations and that much of the impact of,Taken together these six variables explain. freedom and generosity on life evaluations is, three quarters of the variation in national annual. channeled through their influence on positive,average ladder scores among countries using.
emotions That is freedom and generosity have,data from the years 2005 to 2019 The model s. large impacts on positive affect which in turn,predictive power is little changed if the year. has a major impact on life evaluations The Gallup,fixed effects in the model are removed falling. World Poll does not have a widely available,from 0 751 to 0 745 in terms of the adjusted. measure of life purpose to test whether it too,would play a strong role in support of high life.
The second and third columns of Table 2 1 use evaluations. the same six variables to estimate equations for,Our country rankings in Figure 2 1 show life. national averages of positive and negative affect,evaluations answers to the Cantril ladder. where both are based on answers about yesterday s,question for each country averaged over the. emotional experiences see Technical Box 1 for,years 2017 2019 Not every country has surveys. how the affect measures are constructed In,in every year the total sample sizes are reported.
general emotional measures and especially,in Statistical Appendix 1 and are reflected in. negative ones are differently and much less fully,Figure 2 1 by the horizontal lines showing the 95. explained by the six variables than are life evalua. confidence intervals The confidence intervals are, tions Per capita income and healthy life expectancy. tighter for countries with larger samples,have significant effects on life evaluations but. not in these national average data on either The overall length of each country bar represents. positive or negative affect The situation changes the average ladder score which is also shown in. when we consider social variables Bearing in mind numerals The rankings in Figure 2 1 depend only. that positive and negative affect are measured on on the average Cantril ladder scores reported by. a 0 to 1 scale while life evaluations are on a 0 to the respondents and not on the values of the six. 10 scale social support can be seen to have variables that we use to help account for the. similar proportionate effects on positive and large differences we find. negative emotions as on life evaluations Freedom,Each of these bars is divided into seven.
and generosity have even larger influences on,segments showing our research efforts to find. positive affect than on the Cantril ladder Negative. possible sources for the ladder levels The first,affect is significantly reduced by social support. six sub bars show how much each of the six key,freedom and absence of corruption. variables is calculated to contribute to that, Table 2 1 Regressions to Explain Average Happiness across Countries Pooled OLS. Dependent Variable, Cantril Ladder Positive Affect Negative Affect Cantril Ladder.
Independent Variable 0 10 0 1 0 1 0 10,Log GDP per capita 0 31 009 0 008 0 324. 0 066 0 01 0 008 0 065,Social support 2 362 0 247 336 2 011. 0 363 0 048 0 052 0 389, Healthy life expectancy at birth 0 036 0 001 0 002 0 033 16. 0 01 0 001 0 001 0 009, Freedom to make life choices 1 199 0 367 084 0 522. 0 298 0 041 0 04 0 287,Generosity 0 661 0 135 0 024 0 39.
0 275 0 03 0 028 0 273,Perceptions of corruption 646 0 02 0 097 720. 0 297 0 027 0 024 0 294,Positive affect 1 944,Negative affect 0 379. Year fixed effects Included Included Included Included. Number of countries 156 156 156 156,Number of obs 1627 1624 1626 1623. Adjusted R squared 0 751 0 475 0 3 0 768, Notes This is a pooled OLS regression for a tattered panel explaining annual national average Cantril ladder. responses from all available surveys from 2005 to 2019 See Technical Box 1 for detailed information about each. of the predictors Coefficients are reported with robust standard errors clustered by country in parentheses. and indicate significance at the 1 5 and 10 percent levels respectively. country s ladder score relative to that in a column of Table 2 1 These residuals are as likely. hypothetical country called Dystopia so to be negative as positive 8. named because it has values equal to the world s,How do we calculate each factor s contribution.
lowest national averages for 2017 2019 for each,to average life evaluations Taking the example. of the six key variables used in Table 2 1 We use,of healthy life expectancy the sub bar in the. Dystopia as a benchmark against which to,case of Tanzania is equal to the number of years. compare contributions from each of the six,by which healthy life expectancy in Tanzania. factors The choice of Dystopia as a benchmark,exceeds the world s lowest value multiplied.
permits every real country to have a positive,by the Table 2 1 coefficient for the influence. or at least zero contribution from each of the,of healthy life expectancy on life evaluations. six factors We calculate based on the estimates,The width of each sub bar then shows country. in the first column of Table 2 1 that Dystopia had. by country how much each of the six variables,a 2017 2019 ladder score equal to 1 97 on the. contributes to the international ladder differences. 0 to 10 scale The final sub bar is the sum of two,These calculations are illustrative rather than.
components the calculated average 2017 2019, conclusive for several reasons First the selection. life evaluation in Dystopia 1 97 and each,of candidate variables is restricted by what is. country s own prediction error which measures,available for all these countries Traditional. the extent to which life evaluations are higher or. variables like GDP per capita and healthy life,lower than predicted by our equation in the first. World Happiness Report 2020, Technical Box 1 Detailed information about each of the predictors in Table 2 1.
1 GDP per capita is in terms of Purchasing 4 Freedom to make life choices is the. Power Parity PPP adjusted to constant national average of binary responses. 2011 international dollars taken from to the GWP question Are you satisfied. the World Development Indicators or dissatisfied with your freedom to. WDI released by the World Bank on choose what you do with your life. November 28 2019 See Statistical,5 Generosity is the residual of regressing. Appendix 1 for more details GDP data,the national average of GWP responses. for 2019 are not yet available so we,to the question Have you donated. extend the GDP time series from 2018,money to a charity in the past month. 14 15 Introduction This is the eighth World Happiness Report Its central purpose remains as it was for the first Report to review the science of measuring and understanding subjective well being and to use survey measures of life satisfaction to track the

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