Valuation:

Methods and principles for valuing life satisfaction

With a well-established correlation between wellbeing and life satisfaction and life satisfaction and income, we have the elements needed to estimate the monetary value of social parameters such as depression, stress and loneliness.

Specifically, this is done in two steps:

1. Estimating the correlation between the social parameter of interest and subjectively assessed wellbeing (measured as life satisfaction). This is done in a regression where relevant control variables are ^included1.
2. Monetization of the correlation between the social parameter and subjective wellbeing. This is done by using the willingness to pay per WELLBY.

In OSVB, you can find a number of social values that are valued from the above steps, based on English experiences and data. In the next update of OSVB, the values will gradually be based on Danish data.

Value of wellbeing change = [effect on life satisfaction] x [WELLBY]

The value of the social effect is given as the ratio between the importance of income and the social effect on life satisfaction

Valuing 1 point of life satisfaction per person per year (WELLBY)

Monetization of life satisfaction - willingness to pay as key

We define the value of changes in life satisfaction (measured on a scale of 0-10) by the unit WELLBY. A one-point change corresponds to one WELLBY, per person per year. We monetize the value of a WELLBY by establishing individuals' willingness to pay for a change in life satisfaction. Willingness to pay can be established in different ways. In OSVB, we basically follow the approach used in the UK Treasury - Wellbeing Guidance for Appraisal: Supplementary Green Book ^Guidance1. In future versions of OSVB, we will work on establishing willingness to pay using specific Danish data and different methods, including discrete choice experiments and quasi-experimental approaches using existing survey and register data.

The relationship between QALY, VOLY and WELLBY

The method OSVB is based on uses the well-established measure QALY (quality adjusted life years) and examines what it equates to in terms of WELLBYs - i.e. how many WELLBYs correspond to one year of life. The UK Treasury shows that a QALY is associated with a 7 point change in life satisfaction (going from 8 to 1). In Denmark, we do not have a monetary value for a QALY. However, the Danish Ministry of Finance has valued the "Value of a life year" - a VOLY, which is based on the value of a statistical ^life2. The UK Treasury has chosen to value a ^QALY3 and a VOLY the same, so one VOLY equals one QALY. Based on this, it is assumed that the Danish VOLY value can be used to value our WELLBY. In 2021, the Danish Ministry of Finance valued the value of one year of life, one VOLY, at DKK 1.3 million per ^year4.

The value of one point of life satisfaction (the value of a WELLBY)

Based on the above assumptions, we can derive a Danish value for one point of life satisfaction.

Willingness to pay for a WELLBY = VOLY/(8-1) = DKK 1,300,000/(8-1) = DKK 185,714 (2021 prices)

A change of one point on the life satisfaction scale thus has a value of DKK 186,000 per person per year (2021 prices)

OSVB contribution:

OSVB contribution to socio-economic analysis and limitations of OSVB

Economic assessments are an essential part of society's decision-making and prioritization processes.

In the areas of traffic, environment and climate, both socio-economic and budgetary economic analyses of how new initiatives affect citizens are already included.

Investments in social welfare are often based only on budgetary values and overlook the social benefits the investment creates.

The total value of social investments may be underestimated, and that the potential for measuring wellbeing expressed through life satisfaction and valuing social change is significant.

There is a need for a common approach to include social value creation in decision-making and prioritization processes.

Open Social Value Bank puts the value of social change on the societal agenda and makes it possible to:

• Express the pros and cons of social interventions in comparable monetary values
• Include social cost-benefit analysis in welfare assessments like other areas
• Provide decision makers with a common language to evaluate impact

Limitations: Note that a distinction is made between capitalization and monetization. OSVB does not put a value on the capitalizable budgetary changes, as these values are already in existing calculation models, e.g. the SØM model.

Terminology

Method description (DK)

1. introduction

1.1 The basic idea behind Open Social Value Bank

1.2 Open Social Value Bank today and tomorrow

Method description (DK)

2. The literature on social valuation

2.1 The literature on social valuation

Social valuation is a relatively new approach that falls under the umbrella of wellbeing economics. Wellbeing economics is a field that has been evolving over a number of decades, particularly with a basis in positive psychology. Researchers such as Diener and Seligman (2004) have argued for an economics of wellbeing that takes into account factors beyond financial wealth. In particular, they have emphasized the need to include subjective measures of wellbeing and non-financial aspects in economic analyses. Around the same time, Kahneman et al. (2004) argued that national well-being indicators should be developed as a complement to economic indicators and that this was essential to assess a society's progress. Researchers have long argued for monitoring wellbeing across countries and over time, and that wellbeing should be considered rather than GDP as the sole measure (Jones and Klenow, 2016; Dalziel et al. 2018). More recently, Frijters and Krekel (2021) published a handbook presenting a methodology for working with wellbeing economics in practice. These works have contributed to the development of wellbeing economics by highlighting the importance of incorporating wellbeing measures into economic analysis, policies and strategies. The increased focus on wellbeing economics has led to wellbeing being prioritized politically in a number of national and international settings.

Bhutan was the first country in the world to implement a policy framework based on Gross National Happiness, which includes nine key areas such as wellbeing, community and environmental conservation. Later on, New Zealand was one of the first countries to take significant steps towards implementing a wellbeing economy through the introduction of wellbeing budgeting. This budget placed wellbeing at the center of government budget decisions and included a wider range of indicators beyond GDP. Scotland has also made progress in wellbeing economics through the release of a framework for delivering national outcomes. This framework aims to improve the wellbeing of the population in Scotland. Recently, the UK followed suit with the release of guidance for using wellbeing in economic assessments. This supplementary guidance provides a framework for considering the implications for wellbeing in policy assessments and decision-making processes. In the European Union (EU), there has also been more focus on the field with the release of Council conclusions on wellbeing economics. These conclusions emphasize the importance of prioritizing wellbeing in policies and decision-making processes at the EU level. Similarly, the OECD has issued publications advocating the use of social valuation in economic evaluations and cost-benefit analysis. Finland, in particular, has taken steps to integrate the economics of wellbeing into decision-making processes and sustainability assessments. The country has drawn up an action plan to ensure that well-being considerations are integrated into policy decisions and sustainability assessments.

Thus, there has been a rapid development of implementation policies with a focus on well-being in several different countries and internationally, but this development is lacking in Denmark. OSVB wants to address this gap. Overall, wellbeing economics is a new and growing field that seeks to understand the economic value of promoting wellbeing and inform policy decisions and interventions to achieve this goal. Well-being economics is, among other things, about examining the economic aspects of well-being and establishing methods to estimate economic (social) values for improving well-being or quality of life across the population or in specific population groups.

2.2 The starting point - no social valuation

Social benefits have so far not been valued. There's a good reason for this. It's not easy to put a value on social goods that are not bought and sold on the market. Social goods play a fundamental role in life, but they are not produced in a factory and cannot be imported or exported. Rather, they are products of human conditions, relationships and interactions. Nevertheless, there is both supply and demand for social goods, and in general, a society cannot function without social goods. However, as there are no established market values for social goods, this means that they have so far been valued qualitatively - without monetary linkage. The lack of monetary linkage can, among other things lead to 1) social initiatives, efforts and interventions being underprioritized or underfunded, 2) investments being made in social initiatives, efforts and interventions without knowing the value of the well-being they generate, and decisions being based on a feeling or gut feeling, rather than an informed basis, 3) that you don't know the cost-benefit ratio for a given social initiative or intervention, which can lead to waste, and 4) that you can't compare social initiatives, efforts and interventions, and therefore can't assess where you get the most benefit in relation to the investment. Social valuation is all about placing values on social goods that do not normally have a market value. Social valuation is therefore needed to address these problems.

2.3 From valued to valued

As mentioned, many goods and services that we value and that create wellbeing in society do not have a market price. For example, the beauty of nature, time spent with friends or family, or a sense of purpose in life. Ironically, it's often the things we value the most that don't have values, such as the value of feeling like you can contribute to the society around you.

Social valuation provides us with a way to identify the things we value that don't normally have an economic value. In other words: Open Social Value Bank seeks to value what we value.

In traditional cost-benefit analyses, usually only the budget-related costs and savings are taken into account, but the value of well-being is set to 0. This is a huge limitation, as we know from decades of research that people with better wellbeing have a wide range of health benefits, and also cost society and workplaces far less in annual sickness costs and production losses. This means that traditional cost-benefit analyses that don't take wellbeing value into account can result in underestimating the true socio-economic outcome. This is a serious challenge, as it means that social interventions and policies that lead to social improvements will not be prioritized, as the "true" or rather "full" value is not known.

In practical terms, social valuation can help to make better economic calculations of the value of social improvements. Social valuation can therefore help inform policy decisions and help ensure that the things that create wellbeing are also taken into account economically. It also has implications for how to allocate resources and create new policies. For example, if we know that a certain policy will have negative effects on people's wellbeing, we can weigh these costs against the benefits and make a more informed decision. Overall, social valuation allows us to take a more holistic approach to decision-making, one that considers not only economic factors but also the wellbeing of people and society as a whole.

2.4 Measuring wellbeing under social valuation

It is increasingly recognized that macroeconomic measures, such as Gross Domestic Product (GDP), are inadequate as a measure of societal progress. Indicators such as GDP, for example, can rise despite falling wellbeing. This is because GDP is mainly influenced by labor and productivity, but not necessarily by factors that create wellbeing. The approach behind OSVB is adapted from the UK Green Book Wellbeing Valuation Approach. The premise of this approach is that societal progress should also be measured by overall improvements in wellbeing, rather than relying solely on standard macroeconomic indicators. More specifically and practically, progress can be measured in terms of increasing wellbeing across the population or among different sub-populations. In healthcare and especially in the pharmaceutical industry, QALYs (Quality Adjusted Life Years) have often been used as a measure of wellbeing or quality of life. However, there are some problems with QALYs as a measure of wellbeing, partly because QALYs are not well suited for measuring quality of life, but are based primarily on poor physical health (and a single item for anxiety/depression). There are also some issues with the scoring range, which means that there appear to be conditions on the QALY scale that are worse than death. For these reasons, there was a desire to find a more appropriate measure of wellbeing, one that could act as an overarching indicator with one item and potentially be influenced by most of the things people value in their lives.

The unit used instead as a measure of wellbeing in mental health economics is called WELLBY, which refers to one unit of life satisfaction for one person for one year. In the context of WELLBY, life satisfaction is a standard single-item measurement that is widely used internationally. It is a single question that asks about overall wellbeing:

'Overall, how satisfied are you with your life at the moment?

• With response options from 0 (not at all satisfied) to 10 (fully satisfied).

It is particularly important that the question is about life as a whole, that the timing is non-specific (currently), that there is a clearly ranked range of answer options (0-lowest, 10-highest), and that a recognizable term is used that makes it clear that a subjective assessment is being sought (how satisfied are you?). When it comes to subjectivity, it is essential that the question is completely subjective. The quality of our lives is subjective and what we as individuals value is subjective. Social valuation is a method of establishing values for subjective concepts.
‍
Specific variants of the life satisfaction measure can be used and transferred directly, such as the Cantril ladder question. Other life satisfaction scales also exist (e.g. SWLS) and can be converted to single-item life satisfaction using standard formulas (1). Scales that measure overall well-being but do not measure exactly the same underlying psychological construct (e.g. WHO-5, SWEMWBS) can be converted to single-item life satisfaction using conversion rates.

2.5. Valuation of one WELLBY device

In the UK, WELLBY units have previously been valued via regression analysis of observational data, or using quasi-experimental approaches such as using lottery winners as instrument variables. However, there are a number of limitations associated with these approaches, including that regression analysis cannot establish a clear direction of causality or that there are problems with selection bias, while the instrument-variable approach has some limitations in terms of external validity.

Currently, two main approaches are used to value a WELLBY unit in England. One approach is based on the value already used in the National Health Service (NHS) for one QALY unit (£60,000), which is then converted to WELLBY (≈£10,000). The second approach is based on the value of one WELLBY (≈£16,000) being set via Discrete Choice Experiments and an analysis of the relationship between income and life satisfaction. Choice experiments have been used for years to value goods and services that do not normally have a market value. The novelty of choice experiments in social valuation is that they use life satisfaction as the primary outcome and can identify the relationship with income and different life situations and conditions. One of the strengths of choice action experiments is that the experiment can be randomized and the values identified are therefore considered causal. The UK Treasury Green Book uses the middle value of the results for the two methods, i.e. £13,000 (£10,000; £16,000). The methodological starting point for the Open Social Value Bank will be the same.

2.6 Valuing social improvements

In addition to the valuation of one WELLBY unit, OSVB is also set up to establish values for social change and improvement. These values are identified using two different methods: a) choice action experiments and b) regression analysis of observational data. In choice action experiments, different social situations or life conditions (e.g. loneliness, employment) can be directly related to life satisfaction, allowing social values to be calculated. In regression analyses, the social values are obtained by analyzing the relationship between the social parameters and life satisfaction.

OSVB will use both of these methods, among other things to achieve as robust a data basis as possible. Overall, both methods involve two steps: 1) quantifying the well-being gain associated with a given social intervention, i.e. the effect of the social intervention on life satisfaction, and 2) identifying what change in income would be necessary to achieve the same well-being gain.

2.7 Applying OSVB's social values

OSVB social values can be used to calculate the wellbeing value of social improvements or effects. This type of calculation is also called a social cost-benefit analysis or a wellbeing extended cost-benefit analysis. Here, the normal budget-related costs or savings are taken into account, as well as the value of wellbeing improvement. This is then compared to the costs associated with the action or intervention. The calculations can be made prior to the intervention based on an expected effect (ex-ante) or after the intervention has been carried out based on a real effect (ex-post). The direct wellbeing value can be calculated if the intervention's improvements are based on life satisfaction or a similar wellbeing outcome (e.g. WHO-5, SWEMWBS). Alternatively, the wellbeing value can be calculated if the intervention's improvements are based on social parameters (e.g. reduction of loneliness, unemployment, bullying).

Method description (DK)

3. Methodology and data

The purpose of the Open Social Value Bank is to estimate monetary values of various social parameters that can be used to include the value of social effects of initiatives in socio-economic calculations. There are several possible methods for this. We choose to use choice experiments. There are several reasons for this, which we will discuss in this section. Before we get that far, in the first subsection we present the basic framework for calculating social values. Then, in the second subsection, we describe the choice action experiment as a data collection method to establish optimal conditions for causal inference. Finally, in the third subsection, we present the analytical process by which we estimate the parameters in the framework and thereby calculate the social valuations.

3.1 Framework

When an individual has to choose between two goods to consume, let's call the two goods good A and good B, the individual will choose the good that provides the greater utility. If good A provides greater utility than good B, the individual will choose good A. As the individual consumes good A, the utility of the good will often decrease. This is known in economics as diminishing marginal utility, as the utility of the last good consumed is often lower than the marginal utility of the first. At some point, the utility of good A becomes sufficiently low that the individual will prefer good B, as the marginal utility of B exceeds the marginal utility of A. The exchange ratio between good A and B, i.e. the number of good Bs the individual will give up for one good A, is called the marginal rate of substitution (MRS):

If MRS=2, the individual's marginal utility of A will be twice as high as that of B. In other words, the individual will be indifferent between having 2 good Bs or 1 good A.

We use the exchange ratio approach to value social parameters. If we can calculate the marginal utility of a social parameter and compare it to the marginal utility of income, we can identify how much income individuals would be willing to give up to improve a social parameter. In other words, how much of an increase in income it would take for an individual to be indifferent between an increase in income and an increase in the social parameter.

In other words, we can basically calculate social values with MRS if we:

1. Know the importance of income for life satisfaction (let's call it _MUInd)
2. Know the importance of a social parameter for life satisfaction (let's call it_MUSP)

Here it is essential that we have good and reliable estimates of the marginal utility values of income and the social parameters whose value we want to calculate. It is therefore crucial that these estimates can be interpreted causally.

3.2 Regression analysis of observational data

Traditionally, there are several ways in which attempts have been made to estimate causal estimates of marginal utility values. One way this has been attempted is by using cross-sectional data from, for example, surveys. Here, respondents are indirectly asked about their utility of income and social parameters by assessing their life satisfaction. The reason for this is that the concept of utility is arbitrary for respondents, and life satisfaction is therefore used as the overall parameter that individuals want to optimize.

Thus, life satisfaction is compared between individuals with different incomes and this variation is used to calculate the marginal effects. The limitation of this approach is that respondents' income and social parameters may be correlated with other factors that also affect respondents' life satisfaction. For example, individuals with high income will often also be more educated and employed, which can also have an impact on life satisfaction. These correlations can potentially skew the estimated effects. Even with a rich set of control variables, causality can be challenging to achieve with this approach. Therefore, several studies have used random variation from, for example, lottery winnings to model the impact of income, which overcomes the aforementioned challenge. However, the transferability of the results from these studies may be limited.

3.3 Electoral action experiment

To overcome these methodological barriers, we use a choice action experiment, described in more detail with an example below. The basic idea is that respondents from our desired population answer a questionnaire in which they are presented with a series of choices to select which of the life situations of two hypothetical people, Person A and Person B, they perceive to be associated with the highest quality of life. Respondents are asked about the income of the two people and a number of social parameters, such as their health or whether they are lonely, which we want to calculate the social value of. In addition to the social parameters, the two people are identical in terms of age and gender, for example.

Each respondent is presented with a number of choices between the two hypothetical people's life situations and asked to rate the two people's quality of life on a scale from 0 to 10. The social parameter values of the two hypothetical people are randomly generated for each choice. This means that the characteristics of Person A and Person B are completely independent of all other factors. This is essential and what then allows us to hold all other factors that can influence the assessment of quality of life constant. Since all other factors do not vary, we can estimate causal estimates of the perceived importance of each of the characteristics for QoL.

In the questionnaire, respondents are also asked to provide their age and gender, which allows us to later calculate the social values heterogeneously, i.e. across relevant subgroups. This allows us, for example, to estimate the value of social parameters for men and women separately.

3.3 Analysis

Respondenter præsenteres hver for en række valg om hypotetiske personernes livssituation, som de skal vurdere livskvaliteten L for. Hver hypotetisk livssituation generes tilfældigt. Lad os kalde de hypotetiske personers livssituation i∈{A,B} og valget v∈{1,2,…}.

Vi antager, at respondenterne vurdering af livskvalitet er en funktion af indkomst og de sociale parametre brugt til at beskrive de hypotetiske livssituationer som:

Method description (DK)

4. Social values in Denmark: An electoral experiment

4.1 Sampling

To illustrate the calculation of monetary values of socially important social parameters, we piloted an electoral action experiment in Denmark. The experiment was implemented via a questionnaire sent to a sample of 1,047 Danes in May 2023. The respondents were recruited from the research institute Norstat's online panel and were selected to reflect the Danish population in terms of age, gender, education, region and income.

Respondents received an email invitation to participate in the survey. Those who accepted were directed to one of two versions of the questionnaire. It was random which version they received. The two versions were structured identically. First, respondents were asked to answer a series of background questions about their gender, age, place of residence (region), education level, employment status and monthly income (before tax). They were then taken to the voting experiment itself. As we describe below, the choice experiment in the two versions of the questionnaire was structured identically; the only difference was which social parameters were included in the experiment^.4

4.2 The ballot experiment

In the experiment, respondents were presented with two fictional people, called Person A and Person B, and asked to rate the "life satisfaction" of these people. After a brief introduction to the task, respondents were presented with a screen showing the two people (see Figures 4.1 and 4.2 for examples). The figures contained a table where respondents could read about the characteristics of the two people related to different social parameters. Next, respondents had to answer two questions. First, they were asked to rate: "Which of the two people do you think is more satisfied with their life?". Then they could choose either Person A or Person B. The second question was: "On a scale from 0 to 10, where 0 is 'not at all satisfied with life' and 10 is 'completely satisfied with life', where would you place Person A and Person B?". Here they were asked to rank both Person A and Person B on this 11-point scale. The final assessment of people's life satisfaction constitutes the study's primary dependent variable. However, it is reassuring to know that when we use the second outcome measure, the results lead to substantially the same conclusions.

Each respondent was asked to consider a total of ten comparisons between Person A and Person B. Each comparison was presented on a new page. For each comparison, we randomly varied the values of five social parameters of the two people. In one version of the choice experiment, the five parameters were: Monthly income,loneliness, employment, neighborhood, and overall health. In the other version of the experiment, the parameters were: Monthly income,experience stress, trust in friends and family, weight , and education. The monthly income parameter was repeated in both versions, as it is necessary to calculate the monetary value of the other parameters. The remaining parameters were chosen because they are factors that are usually considered important for people's quality of life. They are often (indirectly) influenced by societal and political measures, but are notoriously difficult to value.

Each parameter could take on different values, which were indicated in brackets below each parameter in the leftmost column. For example, the loneliness parameter could take the values "Never", "Almost never", "Occasionally", "Often", and "Always". The values for each parameter were generated randomly between the two people in a given comparison and within the same person across the ten comparisons. Therefore, the values for each of the two people were completely independent of each other. The values for monthly income were drawn in 1000-kroner intervals from an approximate normal distribution that reflected the actual monthly income among Danes over the age of 18 in 2023. The order in which the parameters were presented in the tables was randomly determined once for each respondent and then remained the same throughout all subsequent comparisons.

Figure 4.1: Example of an electoral action experiment, version 1

Figure 4.2: Example of election action experiment, version 2

Our design has a number of advantages over cross-sectional studies of the monetary value of social parameters. Since the values that the parameters can take on vary randomly and independently of each other, our design allows us to estimate the causal effect of each parameter on respondents' perceptions of life satisfaction. This is difficult to achieve in observational studies, where the values of the different parameters typically correlate with each other. For example, one could imagine that a person who often experiences stress also has weight problems, and it would therefore be difficult to isolate the effect of one factor on life satisfaction over the other. Furthermore, because we estimate the effects of the parameters on the same outcome scale, we can compare their relative importance. More importantly, this allows us to conduct the social valuation on the same monetary scale by comparing the effect of the respective parameters with the estimate of the causal effect of monthly income on life satisfaction.

4.3 Results

Our analysis follows the approach presented in Section 3. For both versions of the choice action experiment, we first use linear regression models to estimate the causal effects that the different social parameters have on respondents' assessment of the life satisfaction of the two individuals. This rating is measured on an 11-point scale from 0 to 10. Since each of the 1,047 respondents rate two people in ten comparisons, we have a total of 20,940 observations. Since individual respondents' ratings are not independent from one comparison to another, we use cluster-robust standard errors at the respondent level to adjust for this.

So what is the causal effect of the social parameters on respondents' ratings of the two people's life satisfaction? The results from the regression analyses for versions 1 and 2 of the choice experiment are presented in Tables 4.1 and 4.2 respectively. For all parameters except monthly income, the coefficients represent our estimated causal effect of each value relative to the reference category for that factor (the reference category is indicated in brackets next to the variable names). The coefficient for monthly income represents the estimated effect on life satisfaction of earning DKK 10,000 more per month (before tax). Brackets next to the estimates indicate 95% confidence intervals and the asterisks represent significance level (see table notes for further details).

We first turn our attention to the regression results from version 1 of the experiment in Table 4.1. Here we see that all five parameters affect respondents' assessment of their life satisfaction. Respondents seem to rate life satisfaction as higher for people who are employed, live in a safe neighborhood, rarely feel lonely, and have good health. For example, we find that people with "excellent" health rather than "poor" health are rated 1.47 scale points (95% CI = 1.35 - 1.60) more satisfied with life. Similarly, people living in a "safe neighborhood" are estimated to be 0.5 scale points (95% CI: 0.42 -- 0.58) more satisfied than people living in an "unsafe neighborhood". Given that our outcome variable ranges from 0 to 10, effects of this magnitude appear to be not only statistically but also practically significant. Finally, we also see that a higher monthly income is associated with a more positive assessment of life satisfaction. For every additional DKK 10,000 a person earns per month, the assessment of life satisfaction increases by 0.15 scale points (95% CI: 0.13 - 0.17).

Now let's switch focus to the results from version 2 of the experiment, presented in Table 4.2. Here we see a similar, but slightly less clear-cut, pattern. It is noteworthy that the level of education has no significant impact on the respondents' assessment of life satisfaction. The differences are neither statistically significant nor of major importance. For example, people with a tertiary education are estimated to be only marginally more satisfied with life (0.004 scale points more) compared to people who have only completed primary school. The uncertainty around this estimate is large and includes both negative and positive values (95% CI: -0.13 - 0.14).

The picture is different when we look at respondents' assessment of how stress levels, weight and trust in friends and family affect people's quality of life. We see positive effects of lower stress, normal weight and strong trust in one's network. For example, when a person goes from being "very often" to "never" stressed, life satisfaction ratings increase by 1.21 scale points (95% CI: 1.07 - 1.35). And again, income also plays a role: an increase in income of DKK 10,000 per month is associated with an increase of 0.12 scale points (95% CI: 0.09 - 0.14) in life satisfaction ratings, which is very close to the effect we observed in the first version of the experiment.

Method description (DK)

5. references

Diener, E., & Seligman, M. E. P. (2004). Beyond Money: Toward an Economy of Well-Being. Psychological Science in the Public Interest, 5(1), 1-31. https://doi.org/10.1111/j.0963-7214.2004.00501001.x

Kahneman, Daniel, et al. "Toward National Well-Being Accounts." The American Economic Review, vol. 94, no. 2, 2004, pp. 429-34. JSTOR, http://www.jstor.org/stable/3592923.

Jones, Charles I., and Peter J. Klenow. 2016. "Beyond GDP? Welfare across Countries and Time." American Economic Review, 106 (9): 2426-57.

Dalziel, P., Saunders, C., Saunders, J. (2018). From Economic Growth to Wellbeing Economics. In: Wellbeing Economics. Wellbeing in Politics and Policy. Palgrave Macmillan, Cham. https://doi.org/10.1007/978-3-319-93194-4_1

Frijters, P. and C. Krekel (2021). A handbook for wellbeing policy-making: History, theory, measurement, implementation, and examples, Oxford University Press

Burns, G.W. (2011). Gross National Happiness: A Gift from Bhutan to the World. In: Biswas-Diener, R. (eds) Positive Psychology as Social Change. Springer, Dordrecht. https://doi.org/10.1007/978-90-481-9938-9_5

EU (2019). "The Economy of Wellbeing - Draft Council Conclusions." from https://data.consilium.europa.eu/doc/document/ST-13171-2019-INIT/en/pdf.

OECD (2018), Cost-Benefit Analysis and the Environment: Further Developments and Policy Use, OECD Publishing, Paris, https://doi.org/10.1787/9789264085169-en.

Treasury (2019). The wellbeing budget 2019. Wellington, New Zealand.

Action Plan to integrate the economy of wellbeing into decision-making and sustainability assessment. Ministry of Social Affairs and Health, Finland. https://stm.fi/en/-/action-plan-to-integrate-the-economy-of-wellbeing-into-decision-making-and-sustainability-assessment

NPFT (2019). Scotland's Wellbeing - Delivering the National Outcomes. Edinburgh, The National Performance Framework Team.

TextHM_Treasury (2021). "Wellbeing guidance for appraisal: supplementary green book guidance." HM Treasury, London.

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