Methodology description

Open Social Value Bank uses the "subjective wellbeing valuation" method, where 1 life satisfaction point for 1 person per year (1 WELLBY) is valued with an economic value. This makes it possible to estimate the monetary value of social change.

Behind the method

The Open Social Value Bank uses the subjective wellbeing valuation method, where 1 life satisfaction point for 1 person per year (1 WELLBY) is assigned an economic value. Once this value is determined, the economic wellbeing value of social change can be estimated. The method is based on choice action experiments and regression analysis of observational or intervention data. The method involves two steps:
Step 1
To quantify the well-being gains associated with a given social intervention, i.e. the impact of social change on life satisfaction.
Step 2
To estimate what change in income is theoretically needed to compensate for a given wellbeing gain or loss.
Background note
Methodology and data (new)
Literature
Methodology and data
References
Method description (DK)

1. background note

1.1 Introduction

There is a growing movement towards the idea that societal development cannot be measured solely by economic growth such as GDP, but should also be about wellbeing. Socio-economic calculations are crucial for prioritization and decision-making, but rarely include measurable values for the social consequences of investments, including the impact on subjective wellbeing. This is despite an increasing focus over the years that societal development should move towards giving dimensions such as subjective wellbeing a significant place.

In 2013, the OECD published guidelines for measuring subjective wellbeing1. The publication was a response to the recommendations of the Commission on the Measurement of Economic Performance and Social Progress (CMEPSP), a commission led by Joseph Stiglitz (2009)2. The Commission's report clearly argued that we should move beyond GDP when measuring societal progress and particularly emphasized the importance of measuring the economic, environmental and social dimensions of well-being. However, despite the fact that subjective well-being had long been a topic of academic literature in 2013, at that time there was no guideline on how national statistical institutions and other relevant actors should work with subjective well-being. The OECD report from 2013 was thus the starting point for creating more accepted and uniform guidelines for measuring and collecting knowledge about well-being, particularly subjective well-being. In this connection, the OECD presented a multidimensional well-being framework in which subjective well-being was a key dimension in its own right3.

Since 2013, many countries have moved towards including subjective well-being as part of the key national well-being and prioritization indicators. The OECD report "Subjective well-being measurement: Current practice and new frontiers" (2023)4 highlights that more than 70% (27 out of 38) of OECD member countries have developed national initiatives on multidimensional well-being, and among these, almost 90% have included subjective well-being indicators in their approach. The most common is a life evaluation indicator, typically in the form of a life satisfaction (LS) question.

There is thus a significant development of implementation policies focusing on wellbeing in several different countries and international organizations, but this development is lacking in Denmark. 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 investigating 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.

With the Open Social Value Bank, we want to move this forward in a Danish context. We want to initiate a Danish movement towards getting well-being, including subjective well-being, even higher on the political agenda. Part of this is about being able to supplement the traditional approaches to economic analysis of societal investments by including the direct human consequences of our societal investments. If we are to become better at prioritizing the factors that we actually value, we need to be able to value them. We believe that this movement is necessary if we are to support the many major societal investments and priorities we face to be sustainable, both economically, environmentally and socially.

1.2. What is Open Social Value Bank?

Open Social Value Bank (OSVB) is an association that wants to focus on social values, including subjective well-being, when decision-makers make decisions. The association is supported by a strong board of directors and a diverse advisory board. The project is initially implemented by Economists Without Borders, UCPH, Impactly and Rambøll Management Consulting, but there is a broad invitation for research collaboration and practice involvement.

The purpose of OSVB is to support the inclusion of the subjective well-being dimension in the decision-making basis for societal investments and priorities. This requires that we put social values on the societal agenda and that we establish common standards for how we quantify and monetize subjective well-being and other social value parameters.

The ambition and goal of OSVB is to put social valuation on the agenda by establishing accepted and uniform approaches to clarify and include the social values created by investments in sustainable societal development. Our goal is to contribute to the development of new standards for measuring the value of social sustainability, both when testing new social initiatives, when testing social investments, but also when investing in major societal changes. We want to contribute with knowledge and practical tools that support decision-making processes across sectors for the benefit of people and society.

Humility is a key word in the work with OSVB. Our goal is not to revolutionize, but to push the development of a Danish adaptation of already recognized international methods and approaches, where Social Value Bank UK is a good example. We believe that based on the strong Danish data culture and the considerable experience Denmark already has in formulating indicators for non-directly measurable parameters, we have a solid foundation for developing a strong paradigm in this area. Despite the solid experience we have in Denmark, we want to approach the task with humility, as quantifying and valuing wellbeing and other social parameters, which are subjective by nature, is a complex task. Changing the mindset and practices around societal investments and priorities requires great humility. It doesn't happen by itself and certainly doesn't happen overnight. With this humble approach, we invite all interested researchers, practitioners and other actors in the field to join our work, as we want to be challenged on the methodology, interpretation and application scenarios of OSVB.

1.3 What is Open Social Value Bank not?

OSVB is not a tool that helps calculate the social impact of the initiatives or investments that are initiated. OSVB "simply" offers a uniform metric to compare and put a quantitative value on the social parameters, which are typically subjective in nature, in order to strengthen the potential for prioritizing according to these parameters. OSVB can thus help put value on the elements we value.

OSVB is also not a tool that can clarify where capitalizable budget value can be established, because even if we quantify and monetize the value of the social changes, it does not mean that a capitalizable value is created in dollars and cents. Thus, OSVB cannot replace budget economic calculation models such as SØM, but can be seen as a supplement that supports a more holistic basis for decision-making.

Figure 3: Open Social Value Bank's contribution to socio-economic analysis

1.4 The methodological starting point - How do we work with subjective wellbeing measurement and social valuation?

Subjective wellbeing valuation is a relatively new methodological approach. It differs from other methods that can be used to value non-traded market goods, as the values are based on how these goods affect self-reported measures of wellbeing, such as life satisfaction. In the Open Social Value Bank, we use the Subjective Wellbeing Valuation approach to value wellbeing. We lean on the UK Treasury's Green Book5, as well as Frijters & Krekels (2021)6. A fundamental assumption of this approach is that measures of life satisfaction (and other subjective wellbeing measures used) serve as good approximations of individuals' underlying utility.

1.4.1 Well-being expressed in life satisfaction

According to the OECD7, measuring wellbeing falls under "Subjective Wellbeing Measurement and Indicators". There are different ways of measuring wellbeing, including 'evaluative wellbeing', i.e. self-assessed wellbeing. One of the measures or indicators used for evaluative wellbeing is life satisfaction, which is used by the OECD8. While many other wellbeing measures are designed to capture specific types of wellbeing (e.g. mental wellbeing, emotional wellbeing), life satisfaction is designed to capture a form of overall human wellbeing.

Life satisfaction is measured with a single question:

"Overall, how satisfied are you with your life at the moment?". Scale: 0 (not at all satisfied) - 10 (fully satisfied)

There are several reasons why the life satisfaction question is appealing to use. The life satisfaction question is easy to collect, easy to answer and easy to interpret. It is also one of the most widely used wellbeing measures in the world, having been collected for millions of respondents in almost every country in the world, starting more than fifty years ago9.

The question has been used in major international data collections such as the World Happiness Report, Gallup World Poll, Global Flourishing Study, OECD, European Social Survey (ESS), European Values Survey (EVS), Survey of Health, Ageing, and Retirement in Europe, as well as many surveys in Denmark.

The life satisfaction question successfully measures many important aspects of life. The question is broadly predictive of many things that we would intuitively think would be associated with well-being, such as marital stability10, longevity11 and work productivity12.

The question is positively associated with a number of desirable states, such as close relationships13, social relationships14, physical and mental health15, employment16 and social status17. It is thus, in this specific context, the best existing single question that can capture a broad spectrum of the dimensions that affect human well-being. When applied in practice in the context of social change (initiatives and interventions), the question should generally be asked before and after a change in a person's life situation and will require follow-up measurements to document duration.

1.4.2 Two steps to social valuation

The starting point for Open's Social Value Bank is thus in line with the OECD's focus on subjective well-being and a well-established research literature that points to a strong correlation between social parameters and well-being expressed as life satisfaction. When we focus on social valuation from this starting point, we basically work with two steps.

Step 1 is about ensuring a robust (and causal) link between specific social parameters and subjective well-being (here captured by life satisfaction).

Step 2 is about monetizing subjective well-being (again captured by life satisfaction), and involves translating the identified well-being effects into something monetary (captured by income).

Figure 4: From Social Change to Wellbeing and from Wellbeing to Monetary Value

1.4.3 Step 1: Correlation between social parameter and subjective well-being

The first step is to establish the correlation between social parameters and life satisfaction. This correlation is inherently complex to estimate, as it is difficult to unambiguously conclude how the specific social parameter associated with wellbeing directly affects self-reported and subjective feeling. However, this causality challenge is well known across social science disciplines and is not unique to wellbeing economics.

Following Fujiwara & Campbell (2011)18 we can express the subjective well-being function as follows:

𝑆𝑊𝐵(𝑆𝑃,𝐼,𝑋) [1]

where SP is the social parameter we are interested in (the non-traded market good), I is income and X represents a vector of other factors that affect an individual's subjective well-being.

We can empirically estimate the function as follows:
𝑆𝑊𝐵i = 𝛼 + 𝛽SPSPi + 𝛽I Ii + 𝛽XXi + 𝜀i [2]
where i represents the individuals in our dataset, 𝛼 is a constant, 𝛽SP, 𝛽I and 𝛽X are the coefficients for each input and 𝜀i is the error term.

This estimation can be carried out using various econometric approaches - the key factor is data availability (e.g. cross-sectional data, longitudinal data, experimental data). Estimation techniques that have been attempted include fixed effects analysis, natural experiments (two otherwise similar groups are exposed to different situations in an approximately random manner), real experiments (such as randomized controlled trials, RCT). However, the latter can be challenging to implement in practice, as the situations we are typically interested in can be difficult to randomize.

In the existing literature, cross-sectional data is typically used to establish the correlation, as it will often be this type of data that is available when we need the above inputs in the same dataset. However, this can be challenging in terms of establishing a real causal relationship, and in such cases there will be a need for a strong theoretical argumentation or previous evidence to back up the relationship.

In the Open Social Value Bank, we will experiment with different approaches to establish this relationship, including drawing on the many good experiences from research in a Danish context and the opportunities offered by the strong Danish register data. We will thus test estimation strategies based on existing data sources from both panel surveys and cross-sectional data, but we will also experiment with data collection through choice experiments.

Regardless of the approach, there will be a consistent focus on whether the established correlation can be considered causal, as this will carry over to the next step and affect monetization. Specifically, the UK Treasury - Wellbeing Guidance for Appraisal19 recommends that only evidence with a sufficiently convincing causal wellbeing effect should be considered for monetization.

The result of the estimation will be a quantification of the change in wellbeing resulting from a change in a social parameter. When we work with life satisfaction as a measure or indicator of subjective or assessed wellbeing, as described above, we operate with the concept of a WELLBY (wellbeing-years). A WELLBY represents a one-point change in life satisfaction for one person in one year (on the 0-10 life satisfaction scale).

1.4.4 Step 2: Monetizing the link

The next step is to monetize the subjective well-being effect. As described in the previous sections, in the Open Social Value Bank we follow the dominant part of the literature, which primarily focuses on quantifying and monetizing subjective well-being through life satisfaction. Basically, this step is about establishing a willingness to pay for well-being or life satisfaction. Thus, we need to be able to estimate how large an amount of money (typically captured in income) can create the same change in subjective well-being as a change in a specific social parameter.

The fundamental challenge when we want to monetize is that income is very likely to be endogenous. For example, previous literature has shown that individuals who feel happier or more satisfied later have higher wages20. Research has attempted to address this challenge by exploiting various exogenous changes in income (lottery winners, large sudden income shifts), and the results show relatively large differences in the resulting income coefficients. In the Green Book, the primary sources of this variation in income coefficients are considered to be endogeneity in the statistical model, how aware individuals are of income changes, whether the effect is short- or long-term, and whether gains or losses in income are taken into account21.

This challenge and complexity is unavoidable and can give rise to many discussions and uncertainties. To meet this challenge, we at OSVB will work exploratively with monetization by testing different approaches.

In doing so, we believe that this is the best way to build consensus around the Danish valuation. Specifically, we are testing three approaches, each with advantages and disadvantages.
  • Alignment with existing valuations
  • Regression analysis of observational data
  • Electoral experiment
Adapting to existing valuations: The first approach we are testing is largely about drawing on the experience that already exists around valuation in other contexts. The basic idea is to use the well-established measure QALY (quality adjusted life years) and examine what it corresponds to in terms of WELLBYs - i.e. how many WELLBYs correspond to one year of life. The monetized value of a QALY can then be applied to an appropriate number of WELLBYs. The approach is proposed by Frijters & Krekel (2021)22.

UK Treasury shows that a QALY is associated with a 7 point change in life satisfaction (goes from 8 to 1)23. The Danish Ministry of Finance has valued the "Value of a life year" - a VOLY, which is based on the value of a statistical life24. The UK Treasury has chosen to value a QALY and a VOLY equally, so one VOLY equals one QALY25. 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 year26.

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

The value of a WELLBY = 𝑉𝑂𝐿𝑌/(8 - 1) = 1,300,000 𝑘𝑟./(8 - 1) = 185,714 𝑘𝑟. (2021 𝑝𝑟𝑖𝑠𝑒𝑟)

A change of one point on the life satisfaction scale is thus assigned a value of DKK 186,000 per person per year (2021 prices) if this approach is used.

Regression analysis: With this approach, we start from the above estimation equation [2]. The basic idea of this approach is to establish a trade-off between income and wellbeing. That is, for a given wellbeing effect, how large an increase/decrease in income must an individual experience in order to create a corresponding change in wellbeing. Or to put it another way, how large an increase in income would be needed for an individual to be indifferent between an increase in income and an increase in the social parameter.

Here we draw on core concepts in the economic toolbox when we try to calculate the marginal rate of substitution (MRS) between the non-traded market good (the social parameter) and income, while keeping subjective wellbeing constant. We can express the marginal rate of substitution in a simple form as:

|𝑀𝑅𝑆| =𝛽SP / 𝛽I
which represents the ratio of the estimated effects - i.e. the coefficients from a robust regression analysis. The overriding assumption here is that we can establish a causal link between the social parameter and subjective well-being, and between income and subjective well-being (measured as life satisfaction). It is therefore essential that we have good and reliable estimates, which ties in with the discussion raised earlier in the chapter.

Choice action experiment: The third and final approach we wish to test is a choice action experiment, which can potentially alleviate some of the methodological barriers associated with regression-based approaches. The basic idea of this approach is that respondents from our desired population answer a questionnaire where they are presented with a series of choices to decide which of two hypothetical people's life situations, Person A and Person B, they perceive to be associated with the highest quality of life. Respondents are given the income of the two people and a number of social parameters that we want to calculate the social value of. This could be, for example, whether they feel lonely or how safe the neighborhood they live in is. In addition to the social parameters, the two people are completely similar 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 life satisfaction of the two people 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 allows us to keep all other factors that can influence the assessment of life satisfaction constant. Since all other factors do not vary, we can estimate causal estimates of the perceived importance of each of the characteristics for life satisfaction.

In the questionnaire, respondents are also asked to provide their age and gender, which means that we can 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.

1.4.5 Results in three dimensions

Across the approaches we can use to work with subjective wellbeing and social valuing, it results in three dimensions
  1. We establish a WELLBY in a Danish context. The thinking here is wellbeing as a common currency - WELLBY represents a one-point change in life satisfaction for one person for one year (on a 0-10 scale).
  2. We establish a unit value for one WELLBY. Next, we want to establish a monetary unit value for 1 WELLBY. This unit value will be particularly relevant when working with larger socio-economic calculations where we want to clarify the potential well-being consequences.
  3. Finally, we establish monetary social values on concrete social parameters. The last part here is about putting monetary value on specific social changes. This could be changes in loneliness, stress, life mastery, social network, etc. For example, the value of moving from feeling lonely "often" to feeling lonely "sometimes". This dimension is particularly relevant when evaluating specific social initiatives.

1.4.6 Advantages and limitations of subjective wellbeing valuation

The work of valuing non-traded market goods is inherently complex. As mentioned in the introduction, subjective wellbeing valuation is a relatively new methodological approach within this discipline that offers many possibilities. However, it is also important to be aware of the methodological challenges, limitations and potential biases that apply when using this approach. In 201827, the OECD described a number of these limitations, but also highlighted the benefits. Since then, some of the limitations have been addressed by, among other things, preparing approaches to model the relationship between income and life satisfaction with instrumental variables and by using choice experiments.

The OSVB uses monetization of well-being for the following reasons:
  1. Transparency - we can see what works on wellbeing, which in some areas is patchy in Denmark today
  2. A common yardstick is necessary to be able to compare across initiatives, but there is also a need for the yardstick to be made practically applicable in an economic context, for example by enabling social cost-benefit analyses.
  3. Benchmark - we can benchmark how we create the most "wellbeing for the money", which is relevant for prioritization and decision-making. In practice, it can be difficult to interpret, understand and compare effect sizes on different metrics, therefore the use of WELLBYs and social value in monetary terms can enable easier and more intuitive comparison and transparency, see the example below.

Figure 5: Example of comparison of 3 initiatives with and without WELLBYs and social value

OSVB's approach is that social values will not be fully applicable if wellbeing is only expressed in WELLBYs. Without monetization, it is difficult to compare across the social field what creates the most well-being, for example, if you want to compare efforts against loneliness, anxiety or stress. Without monetization, it is also not possible to perform social cost-benefit analyses or use the method for economic calculations. This is precisely the purpose of OSVB. For example, there are many interventions that specifically aim to increase wellbeing in a certain population group. Without monetization, you wouldn't be able to say whether the intervention in question is serving its purpose. You will be able to assess the effect on WELLBYs, but you will not be able to calculate whether an intervention is worth the money without 1) establishing the value of a WELLBY and 2) establishing a threshold for how much we should pay to generate a WELLBY. The whole idea of OSVB is to put a value on wellbeing so that it is possible to calculate what the generated wellbeing is worth. Nevertheless, all calculations should always include the social changes/effects expressed in WELLBYs, so that you can always assess the effect in life satisfaction in addition to the monetization. The WELLBY unit is the common yardstick that is one of the cornerstones of the OSVB method. It allows a decision-maker to choose to focus on the change in WELLBYs (in addition to monetization), which says something about the wellbeing effect itself. This makes it possible to compare effects across interventions. But it is necessary to monetize, both because there is a need for social values to be used for economic calculations, and also because wellbeing should have an economic value that corresponds to its cultural value.

1.4.7 Why doesn't OSVB just use QALYs?

QALYs (Quality Adjusted Life Years) is a measure that is widely used in the healthcare sector, and specifically in medical research and the pharmaceutical industry. QALY is a health-related measure and is therefore appropriate in that context. QALYs are not an appropriate measure of overall human wellbeing. For example, QALYs are often measured through EQ-5D-5L (health-related quality of life) specifically in relation to pain, mobility, disability and personal care (4/5 items), as well as a single item (1/5) related to anxiety and depression. QALY therefore has a narrow focus on wellbeing and will not capture the many other factors that determine people's wellbeing in everyday life, including their employment, education, housing, family constellations, leisure activities, values, etc. The same goes for measures of mental wellbeing, such as the WHO-5 and12/35 SWEMWBS. Overall human wellbeing is more than physical health and mental wellbeing. For this reason, life satisfaction is the best bet for a measure that best captures everything that affects how people feel.

Figure 6: QALY vs WHO-5 / SWEMWBS vs WELLBYs in measuring wellbeing

1.5 Organization

The board is a diverse and diverse group of 10 competent experts in key areas of the social sector. It serves as a forum for presenting research from both internal and external projects. Based on the research and recommendations from the steering group, the board makes decisions on which consensus values to adopt and how these values can be disseminated. This process is well-founded and represents a professionally supported approach to social valuation that is also application-oriented.

Figure 7: Organization of OSVB

The board of OSVB focuses on the fact that openness and transparency is a critical prerequisite for the development of social values and that these are trusted by societal actors. OSVB therefore facilitates a broad collaboration between stakeholders across sectors so that social valuation becomes part of the common societal agenda.

The Advisory Board, like the Board of Directors, consists of a diverse group of 28 people with expertise in their respective areas of responsibility. The purpose of the Advisory Board is to present and discuss the OSVB's recommendations for estimating social value. Through these discussions, nuances, challenges and opportunities are uncovered, which are then communicated to the steering group and the board. The advisory board is also tasked with increasing awareness and understanding of social valuation and the OSVB.

1.6 What does "open" mean in OSVB?

The fact that the OSVB is 'open' means that there is a transparent, open, broad and collaborative dialog involving both public and private actors interested and engaged in this agenda. It strives for dialog, collaboration and involvement of stakeholders and researchers who want to collaborate and contribute to this growing field. In this way, the overall goal of making social valuation a recognized and accepted element is pursued. Openness also serves as a guideline for the collaboration strategy that OSVB builds on and further develops.

1.7 How do we collaborate?

OSVB wants to partner with all serious players who share the mission of developing, spreading and increasing the use of social values. OSVB provides an open and transparent platform for social values, which can be strengthened through partnerships and cross-sector collaboration.

Openness and transparency are essential for the development of social values and to gain the trust of societal stakeholders. The OSVB therefore seeks to facilitate broad collaboration between stakeholders across sectors, so that the use of WELLBYs and social valuation can become an integral part of the common societal agenda.

For example, the OSVB steering group is involved in and conducts research on social values, but also encourages and invites research collaboration, e.g. by openly sharing data sets.e.g. by open exchange of datasets and research in different application areas.

To concretely facilitate open and transparent collaboration and partnerships, work is ongoing to further develop the collaboration strategy and establish a "collaboration area" on the OSVB website. The purpose is to clarify how to collaborate, engage in dialog and contribute data, as well as what requirements there may be for data. It should also be clear how to handle demand or sharing of new values, including the methodological and quality requirements that OSVB sets. The intention is also to credit external contributors on the website.

As part of this work, OSVB can issue a "call" where everyone with an interest in social valuation and working in this area is invited to participate. There is therefore also an ongoing dialogue with Trivselsbanken and Østifterne, and a goal of a formalized collaboration in the new year. These actors also participate in OSVB's advisory board. OSVB generally seeks a dialog with all relevant actors in order to create visibility, dissemination and interest from the outside world.

1.8 Do we anchor collaborations?

OSVB seeks to be anchored broadly among public, private and civil society actors, with a particular focus on the municipalities' use of the value bank. To ensure a broad, open and transparent framework for the anchoring, the OSVB association has been founded as a non-profit association with the purpose of developing, operating and disseminating the social value bank.

With its non-profit purpose, the association enables private, public and civil society actors to be represented, support and contribute to the association's work. At the same time, the association facilitates the possibility of receiving financial contributions from both private, public and non-profit foundations as well as other civil society actors.

In addition, OSVB's articles of association make it possible that if, for example, KL, the National Board of Health and Welfare, the Ministry of Finance or the like at some point want to further develop or operate the value bank, the ownership of OSVB can be transferred to them.

In line with OSVB's development, the association structure and project model makes it possible for municipalities, state actors, NGOs, civil society actors and the business community to participate in the development processes and build both knowledge and ownership through participation in both the association OSVB or in the project organization, including the board, advisory board, steering committee or working group.

Figure 8: Organization of the OSVB development work

1.9. OSVB Phase I?

The goal of phase 1 was to establish a methodological foundation for valuing social change, based on English experiences, data and values.

The first phase of the project has resulted in significant methodological progress:
  • The English experience is adapted to a Danish context
  • The first values are established, based directly on the English approach
  • A first version of a catalog of social values is available online
  • First experiences with establishing pure Danish values have been made
  • A pilot test of a choice action experiment with survey responses among 1,047 Danes has been conducted to establish social values using the DCE method
  • A first estimate for a Danish unit value for life satisfaction (WELLBY) has been established based on the Danish value for statistical life years (VSL28), the Danish Ministry of Finance's Key Figures Catalog29, research and reports from the Danish Economic Council (DØRS), based on the methodology in the UK socio-economic guide UK Green Book.30
In phase 1, OSVB has relied on existing research on the valuation of social change. The current social values in the OSVB are based on UK data and values based on solid research.

The UK social values are generated by the correlation method: i.e. the impact of a social change on life satisfaction is described by the correlation coefficient between the given social change and life satisfaction. The correlation coefficients are derived from regressions between a given social change and life satisfaction as outcomes, adjusted for relevant demographic variables and confounders. The degree of certainty/precision of the social values depends on factors such as available data and its representativeness, as well as, for example, adjustments made in the respective analyses. The degree of certainty is described for each social parameter on the website.

The monetary value of social change is found by multiplying the correlation coefficient, which describes the impact of social change on life satisfaction, by the Danish WELLBY value.

International research in the field is constantly growing and developing. The social values are continuously adapted to reflect the most accurate data in the field. During Phase 1, adjustments were made, reviewed and assessed by Danish and UK experts, and then implemented in the value bank. This approach will continue to be used in the future, where social values based on Danish data, like the UK values, will be continuously updated as research and experience develops.

In phase 1, the focus has been on investigating and testing different methods for establishing willingness to pay based on Danish values. Choice action experiments (DCE) and extensive methodological considerations around testing quasi-experimental approaches using existing survey and register data have been carried out. In phase 2, OSVB begins generating Danish social values on Danish data based on the correlation method, which is further described below.

1.10. OSVB Phase II

Beta version of OSVB with Danish data (Dec 2023-Dec 2024)

In the second phase of the project, work will continue to develop Danish values and continuously replace the English data and values with the Danish ones. In addition, the focus is on strengthening the robustness of the value of life satisfaction (WELLBY), as well as preparing case examples with Danish data and values.

Concrete activities:
  • Further development of the experimental setup
  • Creation of research project at and preparation of data submission to Statistics Denmark
  • Raw data processing, merging different data sources and statistical analysis
  • Calculation of values and unit value
  • Update of method description, including calibration and validation with experts, including Simetrica and other experts
  • Presentation of results
  • Organizing conferences, workshops, webinars and seminars
  • Creation of case examples
  • Creation of user guides
It focuses on three pillars:

1) Strengthening the basis for recognition methods and valuation of WELLBYs

OSVB is a development project that works pragmatically to test other methods that can be used to derive life satisfaction coefficients associated with different social situations (outcomes) and to triangulate the value of 1 life satisfaction point (a WELLBY) to achieve broad consensus. Based on the FM, VSL and VOLY values, OSVB wants to follow international research and test different methods that can clarify the relationship between social outcomes, life satisfaction and willingness to pay. This is key to strengthening the core of a Danish WELLBY value and expanding the understanding of social values. OSVB will take advantage of the fact that in a Danish context we have a rich selection of register-based data and survey data that gives us a unique and rich knowledge of life satisfaction, income and social conditions. With this data, we can use regressions to strengthen the basis for estimating willingness to pay for life satisfaction and social values. Secondarily, we will continue testing other approaches, including choice action experiments as an alternative approach to establishing social values.

2) Further development of platform, expanding social values and psychometrics

In phase 2, the value bank is expanded with more social values and target groups. The value and methodological development will be supported by new sections on the website on collaboration, methodology and psychometrics, which will be communicated through articles, guides and video material. This places demands on IT support in terms of user-friendliness, which is why optimization of the website will continue to be in focus. With international interest, a translation function into English will also be implemented in phase 2. Furthermore, the value bank will be expanded with a simple statistics function to give users increased insight into Danish data on life satisfaction, which can be used to put in relation to the bank's social values, including specifically when applying the value bank's values in practice. The statistics function and future needs also require focus on optimizing the database so that the foundation for phase 3 is incorporated into the IT architecture.

3) Dissemination, recognition and consensus

In this track, the continued focus on disseminating knowledge and application of social values is intensified. In particular, we will communicate the complex message that the value of life satisfaction in OSVB is rooted in and directly linked to the Ministry of Finance's guidance on socio-economic analysis. In addition, special attention will be paid to communicating consensus by explaining how this is worked with internationally and the significance for OSVB's work in a Danish context. This work requires the involvement of the steering group, board and advisory board, and the activities in this phase will also include organizing conferences, workshops and seminars. In this phase, we will also develop case examples and user guides aimed at different target groups for OSVB.

1. OECD (2013), OECD Guidelines on Measuring Subjective Well-being, OECD Publishing, Paris

2. Stiglitz, Joseph E., Amartya Sen, and Jean-Paul Fitoussi. "Report by the commission on the measurement of economic performance and social progress." (2009)

3. Other key dimensions are: Income and Wealth, Work and Job Quality, Housing, Health, Knowledge and Skills, Environmental Quality, Safety, Work-Life Balance. Social Connections, Civic Engagement.

4. Mahoney, J. (2023), "Subjective well-being measurement: Current practice and new frontiers", OECD Papers on Well-being and Inequalities, No. 17, OECD Publishing, Paris

5. M_Treasury (2021). "Wellbeing guidance for appraisal: supplementary green book guidance"

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

7. OECD (2013), OECD Guidelines on Measuring Subjective Well-being, OECD Publishing, Paris

8. OECD (2013), OECD Guidelines on Measuring Subjective Well-being, OECD Publishing, Paris

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

10. see Carr, D., Freedman, V. A., Cornman, J. C., and Schwarz, N. (2014). "Happy Marriage, Happy Life? Marital Quality and Subjective Well-being in Later Life". Journal of Marriage and Family 76(5): 930-48 and Margelisch, K., Schneewind, K. A., Violette, J., and Perrig-Chiello, P. (2017)."Marital Stability, Satisfaction and Well-being in Old Age: Variability and Continuity in Long-term Continuously Married Older Persons". Aging and Mental Health 21(4): 389-98

11. see Koivumaa-Honkanen, H., Honkanen, R., Viinamäki, H., Heikkilä, K., Kaprio, J., and Koskenvuo, M. (2000). "Self-reported Life Satisfaction and 20-year Mortality in Healthy Finnish Adults". American Journal of Epidemiology 152(10): 983-91,Chida, Y., and Steptoe, A. (2008). "Positive Psychological Well-being and Mortality: A Quantitative Review of Prospective Observational Studies". Psychosomatic Medicine 70(7): 741-56, Diener, E., and Chan, M. Y. (2011). "Happy People Live Longer: Subjective Well-being Contributes to Health and Longevity". Applied Psychology: Health and Well-Being 3 (1): 1-43. and Steptoe, A., and Wardle, J. (2011). "Positive Affect Measured Using Ecological Momentary Assessment and Survival in Older Men and Women". Proceedings of the National Academy of Sciences 108(45): 18244-8

12. see De Neve, J. E., and Oswald, A. J. (2012). "Estimating the Influence of Life Satisfaction and Positive Affect on Later Income Using Sibling Fixed Effects". Proceedings of the National Academy of Sciences 109(49): 19953-8. and Oswald, A. J., Proto, E., and Sgroi, D. (2015). "Happiness and Productivity". Journal of Labor Economics 33(4): 789-822

13. see Jakobsson, U., Hallberg, I. R., and Westergren, A. (2004). "Overall and Health-related Quality of Life among the Oldest Old in Pain". Quality of Life Research 13(1): 125-36.and Kesebir, P., and Diener, E. (2009). "In Pursuit of Happiness: Empirical Answers to Philosophical Questions". In The Science of Well-being: The Collected Works of Ed Diener. Dordrecht: Springer, pp. 59-74. and Gustavson, K., Røysamb, E., Borren, I., Torvik, F. A., and Karevold, E. (2016). "Life Satisfaction in Close Relationships: Findings from a Longitudinal Study". Journal of Happiness Studies 17(3): 1293-311

14. see Powdthavee, N. (2008). "Putting a Price Tag on Friends, Relatives, and Neighbours: Using Surveys of Life Satisfaction to Value Social Relationships". Journal of Socio- Economics 37(4): 1459-80

15. see Layard, R., Chisholm, D., Patel, V., and Saxena, S. (2013). "Mental Illness and Unhappiness". In J. F. Helliwell, R. Layard, and J. D. Sachs (eds), World Happiness Report 2013. New York: Sustainable Development Solutions Network, pp. 38-53 and Layard, R. (2018). "Mental Illness Destroys Happiness and Is Costless to Treat". Global Happiness Policy Report. Global Happiness Council, pp. 26-51

16. see Clark, A. E., and Oswald, A. J. (1994). "Unhappiness and Unemployment". Economic Journal 104(424): 648-59 and Blanchflower, D. G., and Oswald, A. J. (2004). "Well-being over Time in Britain and the USA". Journal of Public Economics 88(7-8): 1359-86

17. see Alpizar, F., Carlsson, F., and Johansson-Stenman, O. (2005). "How Much Do We Care about Absolute versus Relative Income and Consumption?" Journal of Economic Behavior and Organization 56(3): 405-21 and Anderson, C., Kraus, M. W., Galinsky, A. D., and Keltner, D. (2012). "The Local-ladder Effect: Social Status and Subjective Well-being". Psychological Science 23(7): 764-71

18 Fujiwara, D. and D. Campbell, (2011), Valuation Techniques for Cost Benefit Analysis: Stated Preference, Revealed Preference and Subjective Well-Being Approaches, HM Treasury, London

19. m_Treasury (2021). "Wellbeing guidance for appraisal: supplementary green book guidance"

20. See for example: Graham, C., Eggers, A. and Sukhtankar, S. (2004), "Does Happiness Pay? An Exploration based on Panel Data fromRussia", Journal of Economic Behaviour and Organization, 55, 319-342 ; De Neve, J.-E., & Oswald, A. J. (2012). Estimating the influence of life satisfaction and positive affect on later income using sibling fixed effects. PNAS Proceedings of the National Academy of Sciences of the United States of America, 109(49), 19953-19958. https://doi.org/10.1073/pnas.1211437109; Elsas, Susanne. Causality in the link between income and satisfaction: IV estimation with internal instruments. No. 1143. SOEPpapers on Multidisciplinary Panel Data Research, 2021.

21 M_Treasury (2021). "Wellbeing guidance for appraisal: supplementary green book guidance"

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

23 M_Treasury (2021). "Wellbeing discussion paper: monetization of life satisfaction effect sizes"

24. the Ministry of Finance's documentation note on the value of static life and statistical life year (2019)

25 A scoping study on the valuation of risks to life and health: the monetary value of a life year (VOLY)

26. Ministry of Finance's key figures catalog (2021)

27 OECD (2018), Cost-Benefit Analysis and the Environment: Further Developments and Policy Use, OECD Publishing, Paris

28. the Ministry of Finance's documentation note on the value of static life and statistical life year (2019)

29. Ministry of Finance's key figures catalog (2021)

30. M_Treasury (2021). "Wellbeing guidance for appraisal: supplementary green book guidance", pp 55

Using Subjective Wellbeing data and valuation

2. International application of well-being measures and social valuation for policy development, decision support and evaluation

2.1 International use of well-being measures and social valuation for policy development, decision support and evaluation

2.1.1. OECD

Measuring people's quality of life is essential to assessing the progress of a society. It is now widely recognized that measuring subjective well-being is a fundamental part of measuring quality of life, along with other social and economic dimensions. As part of the groundbreaking Better Life Initiative31 project launched in 2011, which aims to measure societal progress across eleven domains of well-being32, the OECD has developed methodological recommendations for the collection and use of measures of subjective well-being. Similarly, the UN uses subjective well-being, measured by life satisfaction, as an indicator in SDG goal 3 on Good health and well-being.

Denmark is sometimes referred to as a "welfare paradise" or "the fairy tale country", with an extensive network of coherent social, health and welfare services. But perhaps there is trouble in paradise. The Danish Health Authority's National Health Profile 2017 showed that 25 percent of Danes experienced high levels of stress.33 Compared to previous national health surveys from 2010, the 2017 survey indicates that Danes' mental health had deteriorated by 3.2 percent since 201034. Critics argue that Denmark is entering a mental health crisis and that the welfare system is not effectively addressing these challenges, resulting in high human and societal costs. A key problem and research gap may be a lack of knowledge about the impact of various public services, initiatives and interventions in the social area, the costs associated with these, as well as insight into opportunity costs and other alternative ways of creating quality of life.

The figure below shows that the vast majority of OECD countries that we usually compare ourselves with in Denmark have introduced national wellbeing indicators, etc. However, Denmark is not among the group of countries that have adopted this type of initiative, and at the time of writing, no official plans have been published. This is despite the fact that the other Nordic countries are already in the process, with Finland leading the way. From a societal perspective, this can make it difficult to monitor, analyze and optimize the benefits of the projects that create value for citizens and society, and it can also be considered paradoxical, given how much talk there is about well-being in our society and the amount of investments that are articulated to improve well-being, for example for vulnerable young people.

Figure 9: 85% of OECD countries with a wellbeing measurement framework use subjective wellbeing indicators based on the life satisfaction measure

A wide range of states, governments, municipalities, organizations and companies currently collect and use data on subjective well-being indicators, particularly the life satisfaction (LS) measure, to inform decision-making, policy development, public budget allocation and investment evaluations, as well as to monitor societal progress and trends.

At an overall state level, subjective well-being data and social valuation are used to

  1. Highlighting trends, societal friction and discontent and taking the societal pulse in a way that other societal indicators don't always capture,
  2. Predict behavioral changes in society empirically and provide explanations and understanding of developments and trends in addition to or beyond other objective data sets,
  3. Support policy development, strategic planning, decision-making, implementation and evaluation processes, as well as budget processes and resource allocation.

OECD methodological work on shadow pricing (social valuation)

The OECD describes the valuation of non-market goods and services as shadow pricing. The OECD works with different methods for estimating shadow prices, including revealed and stated preference and subjective shadow pricing based on life satisfaction data and the income equivalent approach - the same approach used in the OSVB.36 It is recommended to use subjective shadow pricing as inputs, along with traditional market goods, in the development of and investment in large welfare initiatives.

2.1.2. New EU sustainability initiative: ESG, CSRD and ESRS

The EU Directive on CSRD, including the social ESRS standards, obliges large companies, listed SMEs covered by the Danish Financial Statements Act and certain financial institutions to report and disclose their sustainability performance according to mandatory standards set by the EU.37

Figure 10: 85% Overview of upcoming EU ESRS reporting standards38

31. OECD "How's Life? 2020: Measuring Well-being", section 8

32. OECD (2023) "Measuring Well-being and Progress: Well-being Research"

33. Ministry of Health (2017), "The National Health Profile", pp. 16-26

34. Danish Health Agency, (2017), "The Health of The Danes - The National Health Profile", Danish Ministry of Health. P. 16-26

35. OECD (2023), Subjective Well-being Measurement: Current Practice and New Frontiers, p. 20

36. OECD (2023), Subjective Well-being Measurement: Current Practice and New Frontiers, p. 19-20

37. Danish Business Authority (2022), CSRD and European sustainability standards

38. Deloitte & Impactly ESG impact roundtable (2023)

39. Regeringskanseliet (2012), Sweden, nya-matt-pa-valfard-and-quality-of-life-in-society (regjeringen.se)

40. Statistics Sweden, "Indicators of sustainable development and quality of life for budget work", Statistics Sweden

41. Regeringskanseliet, Sweden, "Sustainable Economy Roadmap - Coordinator - Agenda 2030 (agenda2030samordnaren.se)"

42. Regeringskanseliet, Sweden, (2015), "Are we getting better? About measures of quality of life"

43. Eurostat, EU-SILC (2023), Average rating of satisfaction by domain, income quintile, household type and degree of urbanization

44. General Secretariat of the Council (2019): The Economy of Wellbeing Council Conclusions

45. McKinsey & Company (2020): "An experiment to inform universal basic income"

46. Leveling up the UK (2022)

47. "Subjective Well-being Measurement: Current Practice and New Frontiers",p. 30D (OECD, 2023)

48. https://www.gov.uk/government/publications/the-magenta-book

49. https://www.gov.uk/government/publications/the-green-book-appraisal-and-evaluation-in-central-government/the-green-book-2020

50. https://www.gov.uk/government/publications/green-book-supplementary-guidance-wellbeing

51. Public Services (Social Value) Act 2012

52. Procurement Policy Note 06/20

53. HACT, UK Social Value Bank

54. Simmetrica Jacobs & Which? (2021), "Scams and subjective wellbeing Evidence from the Crime Survey for England and Wales"

55. Statistics Netherlands, CBS (2021), "Monitorof Well-being& the SustainableDevelopment Goals"

56. Statistics Netherlands, CBS (2021), "Monitorof Well-being& the SustainableDevelopment Goals: Trends in well-being"

57. Statistics Netherlands, CBS (2021), "Monitorof Well-being& the SustainableDevelopment Goals: Trends in well-being"

58. OECD (2023), "Subjective Well-being Measurement: Current Practice and New Frontiers", p. 29-30.

59. OECD (2023), "Subjective Well-being Measurement: Current Practice and New Frontiers", p. 29-30.

60. OECD (2023), "Subjective Well-being Measurement: Current Practice and New Frontiers", pp. 19-20.

61. OECD (2023), "Subjective Well-being Measurement: Current Practice and New Frontiers", p. 30-31.

62. Wellbeing Economy Alliance, "For an economy in service of life"

63. Wellbeing Economy Alliance, "Wellbeing Economy Governments (WEGO)"

64. The 6th OECD World Forum (2018): "The Future of Well-being", Incheon, Korea

65. Scottish Government, Wellbeing Economy Goverments (WeGo)

66. The New Zealand Treasury, 2022/41

67. Australian government, "Australia's welfare 2021 data insights"

68. Australian Government (2023)"Measuring What Matters - Australia's First Wellbeing Framework"

69. OECD (2023), "Subjective Well-being Measurement: Current Practice and New Frontiers",p. 29-30

70. AUE Government "National Program for Happiness and Wellbeing"

71. Statistics Canada, "About the Quality of Life Framework for Canada"

72. OECD (2023), "Subjective Well-being Measurement: Current Practice and New Frontiers", pp. 18-20.

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 itMUSP)

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:

where L is the assessed quality of life for the hypothetical life situations i i choice v. IND is income, while SP is a vector of values of social parameters, and µi,v is a stochastic error term that we assume is normally distributed.

The beta coefficients represent the marginal utilities of income and the social parameters, respectively. We estimate the model (2) with an OLS regression model and then use them in (1) to value the social parameters.2

If MRSSP1,IND=10(the trade-off between social parameter 1, let's say loneliness and income in thousands), it means that individuals must be compensated with DKK 10,000 annually to maintain the same quality of life if loneliness increases by 1 on the loneliness scale. In other words, a loneliness point is valued at DKK 10,000.

To describe the uncertainty associated with the social valuation, we calculate a 95% confidence interval around the estimates. Here we follow a simulation-based approach.2 The approach consists of a number of steps:

  1. Estimate the desired OLS regression model and save the point estimates for the beta coefficients and the variance-covariance matrix for the coefficients.
  2. Subtract a value from a multivariate normal distribution where the mean is the vector of point estimates for the beta coefficients and the variance comes from the variance-covariance matrix.
  3. Use the extracted values to calculate the social value based on the formula for MRS in equation (3) above.
  4. Repeat the previous two steps 10,000 times and save the estimates for the 10,000 MRSs in a vector.
  5. Rank the estimates from lowest to highest and the confidence interval is as follows:

Furthermore, the value of loneliness can differ across gender, age, etc. Therefore, we heterogeneously value the social parameters across the descriptive characteristics provided by the respondents. This makes it possible to apply as locally accurate social values as possible.

Finally, to validate the results, we compare the valuation of the social parameters using this method with valuations found in other studies using a different methodological approach. This should indicate whether valuations with this method are generally higher, lower or on par with other valuation methods.

2. The estimates in (2) are causal, but they do not in themselves show the effect that income and the social parameters have on quality of life, but rather the effect that respondents believe income and the social parameters have on quality of life. In other words, the causal estimates are scaled. By using MRS to value the social parameters, where we divide the coefficient for a social parameter by the coefficient for income, we overcome this challenge under the assumption that the scaling factor is constant across the parameters of the model.

3. For a detailed review of the methodology, see: Gary King, Michael Tomz, and Jason Wittenberg. 2000. "Making the Most of Statistical Analyses: Improving Interpretation and Presentation." American Journal of Political Science, 44, pp. 341-355

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.

4 We chose to send out the choice experiment in two versions so that respondents didn't have to deal with too many social parameters at once.

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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Examples

Open Social Value Bank wants to create visibility and understanding of the methodology behind calculating the economic value of wellbeing. Wellbeing is measured as changes in a person's life satisfaction as a result of social change.

Below you will find examples related to the methodology and selected cases:
Loneliness
Desire to work
Loneliness:

Case: Efforts against loneliness (fictitious case)

A number of social and health issues can be prevented or alleviated with targeted loneliness initiatives that increase the wellbeing of the citizen and reduce social and health care costs. In Denmark, there are an estimated 600,000 lonely citizens, which has a large economic burden. The cost of health and care, extra early retirement pensions and lost production due to sick leave alone is estimated to cost society DKK 7.4 billion annually, while the well-being cost for the 600,000 lonely citizens is estimated to be DKK 13.5 billion.

Internet-based Cognitive Behavioral Therapy for Loneliness (Fictitious case)

The initiative aims to treat lonely adults through internet-based cognitive behavioral therapy (psychological treatment). The initiative lasts 8 weeks, costs a total of DKK 400,000 and has a total of 73 participants. It is estimated that the target group can achieve an effect size of 4.65 measured on the UCLA-20 scale.

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Open Social Value Bank Partner
Desire to work:

It pays to increase job satisfaction

The Job Satisfaction Knowledge Center collects representative data on Danes' job satisfaction through their GAI survey. Job satisfaction is measured on a scale from 0-100, as an average of three questions that shed light on the individual's job satisfaction. In a series of reports, in collaboration with Kraka Advisory, they present calculations on the value of increasing job satisfaction among employees in Danish companies. Consequences of low job satisfaction include higher sick leave, higher likelihood of job change, earlier retirement and lower life satisfaction.

Fictitious case: Estimates of gains from increasing job satisfaction

The report shows a fictitious example of how the value of life satisfaction can be used in a socio-economic analysis of the value of an initiative. The calculations are based on a fictitious company's efforts to increase job satisfaction among their employees. The estimates are calculated on the basis of socio-economic values from the Job Satisfaction Knowledge Center and Kraka Advisory's reports and OSVB's value for changes in life satisfaction. To accommodate uncertainties, the potential benefit of increased job satisfaction for employee wellbeing is presented in a range of +/- 15% of the OSVB's value for life satisfaction.

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Open Social Value Bank Partner
Example

6. references

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