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Did average happiness in nations change over time, or did it remain stable as implied in trait theory and some variants of comparison theory? We assessed changes in average happiness in nations over the last decade. Happiness was conceptualized as the subjective enjoyment of one’s life-as-a-whole, which can be measured using self-reports. We took stock of responses to questions on happiness in representative surveys of the general population in nations, drawing on findings gathered in the World Database of Happiness. We limited to time series that cover at least 20 years and 10 data-points, which yields 200 time series in 50 nations over the years 1946–2021. Comparison between the first and last observation in 80 timeseries showed 50 cases of a rise and 30 cases of a decline. The average rise was 7%, the average decline 6%. Regression analysis over all 200 time-series showed an average yearly change to the better or worse of 1.6% and a yearly increase of 0.007%. Inspection of the COVID years 2020–2021 revealed declines in average happiness from 5 to 10%. These findings go against theories that imply that average happiness in nations will hardly change over time but fit well with livability theory.
Erasmus Happiness Economics Research Organization EHERO, Erasmus University Rotterdam, Netherlands
Optentia Research Program, North-West University, South Africa
Silke Kegel
Psychology, University of Konstanz, Germany
*Address all correspondence to: veenhoven@ese.eur.nl
1. Introduction
1.1 The issue
One of the ideological foundations of the modern welfare states is the belief that people can be made happier by providing them with better living conditions. This belief is challenged by two theories of happiness: ‘comparison theory’ and ‘trait theory’. Both these theories predict that average happiness will remain unchanged over time despite changes in living conditions such as economic growth or decline. They contradict common sense ‘liveability theory’, which holds that improvement of living conditions in a society will make life more enjoyable, and reversely, that deterioration of living conditions will reduce average happiness.
1.2 Comparison theory
This theory sees happiness as the result of cognitive comparison with standards of the good life. One variant of this theory focuses on comparison with other people; the ‘reference group’ and holds that we are happier the more we think to be better off. In that view, a general improvement in living conditions in the country will not make us any happier, because the reference groups get also better. A proponent of this theory is Richard Easterlin [1] who maintains that economic growth does not improve happiness as ‘the rising tide lifts all boats’. Another variant of comparison theory focuses on comparison with aspirations which tend to rise when income rises, leaving us equally happy as before [2, 3]. Several of these variants are combined in Michalos’s [4] theory that happiness results from ‘multiple discrepancies’.
1.3 Trait theory
This theory sees happiness as a stable personality trait, rather than a variable state. This character happiness is seen to root in genetic endowment and early experience and to result in a ‘set-point’ level around which happiness can vary a bit across ups and downs. The macro-level variant of this theory holds that average happiness in nations is a matter of national character, which roots in culture and history. In this view, average happiness in nations will change only in the very long-term.
A variant of this theory holds that the set point is typically around 7.5 on a scale of 0–10, which level is homeostatically defended, like our body temperature [5]. In that view, average happiness will typically vary around that level and will be lowered only if homeostatic defense fails, like when we are unable to keep warm.
1.4 Liveability theory
This theory holds that happiness depends on the degree to which our living environment fits our needs and capacities. In this theory, ‘needs’ are seen as innate requirements for survival and distinguished from ‘wants’ in cognitive theories of happiness. Gratification of needs is seen to reflect in affective experience, which on its turn determines how much we like the life we live [6]. This theory predicts that happiness will change when living conditions improve or decline or when our capability to deal with these conditions gets better or worse.
These views are discussed in more detail in Veenhoven [6, 7, 8, 9].
1.5 Research questions
This chapter addresses the following questions:
Has average happiness in nations changed over time?
Did the COVID epidemic affect average happiness in nations?
We limit these questions to whether average happiness has changed or not, and do not enter questions about possible determinants of change and stability of happiness in nations.
1.6 Structure of this chapter
We will first delineate the concept of happiness in more detail and identify valid measures of that concept in Section 2. We describe the source of our data on happiness in nations (the World Database of Happiness) in section 3. We explain how we use links to that online finding archive in Section 4. On that basis, we answer our research questions one by one in Section 5. We discuss these results in Section 6 and conclude in Section 7.
We define happiness as the subjective enjoyment of one’s life-as-a-whole. This notion is explained in more detail in Veenhoven [10].
2.2 Components of happiness
Within this notion of overall happiness, we distinguish two components of happiness, the affective component, how well one feels most of the time, and the cognitive component, to what extent one perceives to acquire from life what one wants. Research has shown that the affective component dominates in the overall evaluation of life [11].
2.3 Measurement
Since happiness is defined as something in our mind, it can be measured using questioning. A great variety of questions has been used, direct and indirect questions, single and multiple questions and questions on happiness in the past, present and future. In this chapter, we limit to single direct questions on current happiness [12].
2.4 Selection of valid questions on happiness
Not all questions ever used fit the above definition of happiness equally well. The questions used in this study have passed a check for face validity, which involved a close reading of the text. This kind of substantive validity testing differs from the usual practice of assessing validity using correlations, such as the correspondence between different questions in a scale (construct validity) and correlation with related phenomena (predictive validity). These correlational methods are suited for ill-defined ‘sensitizing’ concepts such as ‘neuroticism’ in psychology and ‘alienation’ in sociology. The correlations tell us that a series of questions measure something, though not precisely what.
In this case of happiness, we deal with a well-defined ‘distinct’ concept and can assess the correspondence between concept and measurement by comparing the text of a question with the definition of the concept; that is using logic. Several commonly used questions and questionnaires fail that test, as shown in Veenhoven [13, 14].
2.5 Some valid survey questions on happiness
Two examples of questions on overall happiness are:
Taking all things together, how satisfied or dissatisfied are you with your life-as-a-whole these days? Please indicate in a number between 1 and 10, where 1 means very satisfied and 10 for very satisfied
How happy would you say you are, very happy, pretty happy or not too happy?
An example of a question on the affective component of happiness is:
With which of the following statements can you identify best?
I have not been cheerful for a long time,
I am rarely cheerful,
I am cheerful sometimes,
I am cheerful not every day, but frequently,
I am cheerful almost every day.
A much-used question on the cognitive component of happiness reads1:
Here is a picture of a ladder with steps numbered from 0 at the bottom to 10 at the top. Suppose that we say that the top of the ladder represents the best possible life for you and the bottom represents the worst possible life for you. On which step of the ladder would you personally feel to stand at the present time?
2.6 Classification of equivalent questions on happiness
As illustrated in the above examples, questions differ in several ways, next to variation in conceptual focus, there is technical difference such as in lead phrase, time frame, number and wording of response options.
Ideally, comparison restricts to identical questions, which involves severe restriction to the number of cases. Therefore, we do with near-identical equivalent questions. Single survey questions are sorted by a combination of lead items, kind of response scale (verbal or numerical) and number of response options. The list of equivalent measure types is available at the end of the chapter, in the “Additional information” sections (Link 1). If you click on a type, you get an overview of all responses to that kind of question, sorted by nation and year.
2.7 Transformation of responses to a common 0–10 numerical scale
Comparison across equivalent questions further required that the observed degree of happiness is quantified on the same scale. This is done using techniques described in Kalmijn [15].
In this chapter, we draw on the World Database of Happiness [16]. This is an online finding archive that consists of some 30.000 electronic findings pages, on which empirical research findings are described in standard format and terminology. Each page has a unique internet address. The structure of this finding archive is presented visually in Figure 1, and an example of a finding page is given in Figure 2. The technique is described in more detail by Veenhoven [17].
Figure 1.
Structure of the World database of happiness.
Figure 2.
Example of a finding page in the World Database of Happiness.
In this finding archive, one can search for distributional findings on happiness in a nation and year using a particular question. In this chapter, we can draw on pre-selections of distributional findings in the general population of nations, brought together in ‘reports’. We use the Report on Average Happiness in Nations, which sorts all such findings first by type of happiness question used and further by nation and within the nation by year [18]. To date, the report covers 13.126 findings. Links in that lengthy list bring the user to full detail on electronic finding pages.
Analysis of these data is facilitated by entering them in a spreadsheet, the file ‘TrendsInNations’. The latest version of that data set is available in Excel and can be downloaded from the World Database of Happiness website (available as Link 2 in the “Additional information” section) [19]. The file can be uploaded to statistical programs such as R and SPSS.
Using the datafile Trends In Nations version 2022, we restricted to time series that cover at least 20 years and involve at least 10 data points. This is to keep the eye on long-term change for the better or worse and reduce the influence of incidental outliers. This left us with 200 time series in 70 nations over ranges of 71 to 20 years in the period 1945–2021.
4.1 Sorting by decade
The longer the time series, the fewer cases we have; only one nation in the longest series since 1945 (United States) and 44 nations for the shortest time series since 2000. To allow for analysis of change in happiness over longer and shorter periods, we sorted the findings by decade; since 1950s, since 1960s, …, until since 2000. With a few exceptions, these series go up to and including the year 2019.
4.2 Separate presentation of 2020–2021 COVID years
For a limited number of nations, we also have findings on average happiness in the years 2020–2021 in which the COVID pandemic developed. As we will see in Section 5.4, this incidental disaster has lowered average happiness in all nations and with recovery data not yet available it would distort the view of the general trend. As 2020–2021 data are available only for a few nations, comparison across nations would also be marred if we took all the available years together.
Trends can be analyzed in various ways, with applicability depending on the research questions at hand. For our research questions, we did with two easily interpretable methods.
5.1 First-last comparison
We started with a comparison between the first and last observation in each time series and assessed whether and to what extent the difference denoted a decline (−) or gain (+) in happiness. An evident limitation of this method is that it takes only a fraction of the information into account and misses possible ups and down in happiness in between. The method is also vulnerable to outliers in the first and last years. We report this analysis in Table 1.
Change average happiness expressed in points on scale 0–10. Difference between first and last assessment.
Technical details:
The years 2020 and 2021 are left out in this comparison because of the COVID-19 pandemic, which lowered average happiness substantially in most nations (up to one point). Since score for these years are not available for all countries, comparison would flaw
ls4 question on life-satisfaction answer rated on 4-step verbal response scale
ls5 question on life-satisfaction answer rated on 5-step verbal response scale
ls10 question on life-satisfaction answer rated on 10-step numeral response scale
ls11 question on life-satisfaction answer rated on 11-step numeral response scale
ls10+11 question on life-satisfaction answer rated on 10 and 11-step numeral response scale
Scores on questions using verbal response options on range 5 or less were transformed to numerical scales on range 0-10 using linear transformation. This procedure is explained in chapter 6 (Link 6) of the introductory text to the collection of happiness measures section 6.1.1.
Within series of responses to equivalent questions not all questions are fully identical, variations in wording being indicated with a, b, c … at the end of the measure code. See chapter 5 (Link 7) of the introductory text to the collection of happiness measures, scheme 5. When assessing the difference between the first and last score of questions using verbal response scales, we limited to identical questions, since differences in wording can bias the trend. In the case of responses to 10 and 11-step numerical rating scales we accepted equivalent questions, assuming that respondents will have focused on scale numbers, rather than on the verbal labels of scale extremes.
Data were rounded up to three decimal places.
5.2 Linear regression
Using all available data points, we next estimated the best-fitting regression line, applying ordinary least square analysis. This analysis is presented in Figure 3. The resulting unstandardized regression coefficient denotes the angle of deviation from the horizontal line of no change. Since we deal with a 0–10 range, a regression coefficient of +0.01 denotes a yearly increase in happiness of 1%, giving a rise of a full point in 10 years. We report this analysis in Table 2.
Figure 3.
Example of trend analysis using ordinary least squares regression.
ls4 question on life-satisfaction answer rated on 4-step verbal response scale
ls5 question on life-satisfaction answer rated on 5-step verbal response scale
ls10 question on life-satisfaction answer rated on 10-step numeral response scale
ls11 question on life-satisfaction answer rated on 11-step numeral response scale
ls10+11 question on life-satisfaction answer rated on 10 and 11-step numeral response scale
The original scores on these questions were transformed to a comparable 0-10 scale. See section /3.3.3 of the introductory text to this collection of distributional findings on happiness in nations, chapter 7 (Link 8) how the data were homogenized.
Mean scores were taken from the country tables in this collection of distributional findings on happiness in nations (Link 9). In the nation reports look into: ‘Methodological notes’, ‘All distributional findings on happiness by measure and year in …’ (right bottom of the screen).
When happiness was assessed more than once in a year in a country, the average of the mean scores is used.
The average annual change is expressed in a regression coefficient that stands for the size of the slope of the linear regression line through the dots (averages) in the time charts. A positive coefficient denotes an average increase in average happiness, and a negative coefficient a decline. A regression coefficient of +.01 means 0.01-point increase on this 0-10 happiness scale per year, which implies that a one-point rise of happiness would take one hundred years at this pace of change.
The observed regression coefficient is based on a sample of assessments of happiness during this era and the coefficient in this sample may differ from the ‘true’ coefficient. The confidence interval gives an estimated range in which this true coefficient is likely to be included with 95% probability.
This report restricts to time series of at least 20 years involving 10 or more comparable data points.
Coefficients were rounded up to three decimal points.
More than one measure of happiness has been used in some nations and in some of these cases the trends are not identical, such as in the USA, where life-satisfaction declined but responses to the question on best-worst possible life rose.
i The lowest average happiness over the years 2010-2-19 was 3,8 In Tanzania, the highest 8,2 in Denmark. (Veenhoven 2022c).
5.3 Significance of change in separate time-series
In this analysis, we also considered the statistical significance of observed rise or decline in happiness, which will depend on both the number of observations and the size of deviations from the average trend. We do that using confidence intervals on which the reader can see whether or not the difference falls with a 95% interval above or below zero, but also how big that interval is.
This test for statistical significance involves the debatable assumption that the available data points provide an a-select sample of all years in the period in a particular nation. The test is also quite severe for the time series close to the minimum of 10 data points. A change on only 10 observations with a standard deviation of 0.1 must be at least 0.07 to reach statistical significance.
5.4 Significance of change over all time-series
In Table 2, we also reported the average yearly change of average happiness in all nations in a period and at the bottom of the table, we did that for all periods together. We did that in two ways, (1) we presented the total change taking the average of the change coefficient irrespective of the sign. This tells us how much average happiness has changed. In addition, we assess the net change, using the difference between change to the positive and change to the negative. This tells whether average happiness has risen more than declined.
In this case, we also assessed statistical significance, while acknowledging that this test is even more debatable now, since the countries at hand cannot be considered to provide a random sample of all nations at that time. In this test, we meet again with the problem of small numbers, now the number of time series in a period. With only three time series over the years 1946–2019, the average change must be at least 0.15 to reach the 5% level of significance. Given these limitations, the reader can also opt to ignore the statistical significance and take the average change scores as they are.
We can now answer the research questions raised in Section 1.4.
6.1 Has average happiness in nations changed over time?
In Table 1, we noticed the presence of a difference between the first and last observed average and found a difference in all nations, ranging from a 1.8-point rise in Poland after the fall of communism to a 1.2-point decline in Egypt. The average rise was 0.65 points and the average decline was 0.58 points, so a change of about 6% in both directions.
In Table 2, we considered all the data points and report the coefficient of linear change through these points. In this case, we could assess statistical significance. Of the 200 trends up to 2019, 81 were significant at the 5% level, while 119 were not. So, there was less change than stability in happiness over the years and countries considered here. Still, the 40% cases of significant change are not to be neglected. The inclusion of the COVID years 2020–2021 rises the value to 47%.
6.2 Was there more rise than decline?
At the bottom of Table 1, we see that there were 50 cases of rise and 30 cases of decline in average happiness in nations over the years. The average size of the rise was +0.65 points and the average size of the decline was −.58. So clearly more rise than decline.
At the bottom of Table 2, we see that average happiness changed significantly only in 37 nations, of which 26 changed to greater happiness and 11 to less, the average size of the chances being similar. So again, more rise than decline. Remember that this test for significance is quite severe given the many time series around the minimum of 10 data points (cf. Section 5.2), even in this contestable test.
At the bottom of Table 2, we can also see that the average net change in the level of happiness over all the years and nations was positive, with a significant mean of +0.007. We report in more detail on this finding in another paper [20].
6.3 What was the size of these changes?
At the bottom of Table 1, we see that the average size of the rise was +0.65 points and the average size of the decline was −0.58 points. When expressed as a percentage on the possible 0 to 10 range, this denotes about a 6% change to better or worse. When expressed on the actual range of 4.4 between 8.2 in Denmark and 3.8 in Tanzania [19], the changes are respectively 15% to the better and 13% to the worse.
The size of the changes reflects better in the change coefficients in Table 2. Considerable changes to the positive appear again for the post-communist East-European countries after the year 2000, while considerable negative changes appear in the South-European countries that went through an economic crisis in these years. Remember that a coefficient of 0.01 denotes a yearly change of 1%, which will result in a change of a full point on a scale of 0–10 in 10 years. Note that most of the change coefficients are below that level, some just being zero (e.g., hl4 in Norway 1981–2018).
At the bottom of Table 2, we presented the average total change over all periods and nations, which is +0.016. This mean is based on 200 time series and is statistically significant. This corresponds to a yearly change of 0.16% which denotes a one-point change in average happiness in a nation in 63 years. The net change of +0.007 corresponds to an average yearly rise in the happiness of 0.07%. At this rate, a one-point increase in happiness (10%) will take 143 years. This is a factor 10 less than the spectacular rise in longevity in the period considered here2 but also signifies a change for the better.
6.4 Did the COVID epidemic leave average happiness unaffected?
To date (December 2022), we have trend data on average happiness that include the years 2020–2021 for 117 time series in 46 nations. The change scores at the bottom of Table 2 show that the inclusion of these years reduces the average rise by 0,003 points and increases the average decline by 0.01 points. An illustrative case is the United Kingdom, where average happiness declined from 7.4 in 2019 to 7.1 in 2020 as can be seen https://worlddatabaseofhappiness.eur.nl/nations/united-kingdom-16/.
7.1 Why the difference between theories that hold happiness immutable?
These data clearly contradict theories that imply that average happiness in nations will hardly change over time. Though there is considerable stability, there is undeniable change.
These theories have been advanced for some reason. One reason seems to be that they were proposed around 1980, when the available data showed little change in happiness over time, neither in individual follow-up studies nor in trends of average happiness in nations.
The first sizable time series at the nation level was from the United States and Japan, in which average happiness did not change until today. In retrospect, these are exceptions to the rule that average happiness does change over time and that this change is related to economic growth [22].
Another reason, specific to the Easterlin paradox, is what might be called the ‘cognitive fallacy’, seeing happiness as mere contentment while ignoring its affective component (cf. Section 2.1). The current distinction between life satisfaction (overall happiness) and life evaluation (cognitive component) was not made at that time. Mere contentment is indeed likely to depend on social comparison.
Trait theory was inspired by the stability of individual happiness observed in the first follow-up studies in developed nations. Change over the life time became visible only when longer time series became available [23].
The variant of trait theory proposed by Cummins [5] does acknowledge the affective component of happiness, but its assumption of homeostatic defense of a set-point mood level around 7.5 does not fit data that became available later, such as the dip of happiness during the COVID-19 pandemic that hit not only the least happy, prone to homeostatic failure, but also the happiest people (cf. Section 5.4).
7.2 How does liveability theory account for stability and change in happiness?
The initially observed stability of happiness can also be explained by the liveability theory. Need gratification will remain at the same level when positive and negative changes in living conditions balance out or when deteriorations in external living conditions are compensated by improved life-ability. From this perspective, it is explicable that after the fall of communism in 1990, average happiness in Eastern Europe followed a V-pattern; in the first 10 years a decline and since 2000 a sharp increase [24]. The regime change involved a temporary deterioration of external living conditions, for example, a catastrophic decline in the material standard of living which hit pensioners in particular, and lasted for several years [25]. Required abilities for dealing with the new market economy had not been developed under communism and their acquirement also took time.
7.3 Why more change for the better?
Average happiness in nations did not only change considerably during the last decade (total change) but it changed also more for the better (net change). This rise in happiness went together with an unprecedented rise in longevity. All nations were subject to the ongoing process of societal modernization in the period considered, and average happiness was already much higher in the most modern nations of our time [26]. All this supports the theory that human nature, as developed in the conditions of hunter-gatherer existence, fits better with modern industrial society than with traditional agrarian society [27].
7.4 Robustness
The above conclusions draw on 200 time series on average happiness in 50 nations. Though this is more than ever reported before, we cannot exclude the possibility that a different pattern could have been found if all nations of the world had been considered. Likewise, the conclusions could be specific to the questions on happiness used and the periods for which data were available. Though possible, we do not deem that probable, among other things because average happiness appeared to be equally changeable in all kinds of nations, in all kinds of time series and in all periods. Moreover, we do not need more evidence to show that average happiness in nations can change over time.
Average happiness in nations has changed considerably during the last decade. This fits the liveability theory of happiness There was more change to the better than to the worse. That is likely to be the fruit of the societal modernization that pervaded all nations considered in this period.
Due to their size and complexity, complete Tables 1 and 2 are available in digital format for download and ease of use: https://bit.ly/3TBkT7i
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Notes
This question is known as the ‘Cantril ladder’ and is seen to measure ‘life-evaluation’ while the above first example of a question on overall happiness is seen to tap ‘life-satisfaction’.
Longevity increased by some 10 years since 1950 and denotes a yearly change of about 0.08% [21].
Written By
Ruut Veenhoven and Silke Kegel
Submitted: 24 November 2022Reviewed: 23 January 2023Published: 09 February 2024
Open access peer-reviewed chapter - ONLINE FIRST
