Metodebeskrivelse

Open Social Value Bank anvender “subjective wellbeing valuation” metoden, hvor effekten af sociale indsatser og interventioner kan udtrykkes i WELLBYs (1 livstilfredshedspoint for 1 person pr. år). WELLBYs kan bruges som en fælles målestok, og kan endvidere værdisættes med en økonomisk værdi. Dette gør det muligt at estimere den monetære værdi af sociale forandringer.

Bag om metoden

Trivsel udtrykt som ændringer i livstilfredshed

Der findes forskellige måder at måle trivsel på, herunder ‘evaluative wellbeing’. Et af de anvendte mål eller indikatorer for vurderet trivsel er livstilfredshed, der bl.a. anvendes af OECD. Mens mange andre trivselsmål indfanger specifikke former for trivsel (f.eks. mental trivsel, emotionel trivsel), så indfanger livstilfredshed overordnet menneskelig trivsel.
Èt spørgsmål: "Alt i alt, hvor tilfreds er du med dit liv for tiden?"
Livstilfredshedsspørgsmålet som bliver brugt i OSVB måles med et enkelt spørgsmål: "Alt i alt, hvor tilfreds er du med dit liv for tiden?" der besvares på en skala fra 0 (slet ikke tilfreds) til 10 (fuldt ud tilfreds). Det er nemt at indsamle, nemt at besvare, og nemt at fortolke. Det et af de mest udbredte trivselsmål i verden, og er blevet indsamlet for millioner af respondenter i næsten alle lande i verden, begyndende for mere end halvtreds år siden.
WELLBY og monetarisering: To trin til social værdisætning
Trin 1 handler om at sikre en robust (og kausal) sammenhæng mellem konkrete sociale parametre og subjektiv trivsel (her indfanget ved livstilfredshed). Trin 2 handler om monetariseringen af den subjektive trivsel (igen indfanget ved livstilfredshed), og indbefatter at vi kan oversætte de identificerede trivsels effekter til noget monetært (indfanget ved indkomst).
1. Overview
2. Estimations
3. References
Metodebeskrivelse (UK)

1. Overview of Wellbeing Valuation

To estimate monetary values for the twenty shortlisted outcomes, the Wellbeing Valuation (WV) approach was used. This methodology represents the latest developments in the valuation of outcomes that are not openly traded on the market and therefore do not have an explicit value. It is fully endorsed in the UK’s HM Treasury Green Book and the OECD’s guidance on wellbeing. This approach comprises of two steps:

Step 1 – estimating the association between the outcome and subjective wellbeing

The first step uses regression analysis to empirically estimate the associated impact of the outcome in question on individuals’ subjective wellbeing:
  • SWBi is some measure of individuals’ subjective wellbeing. For our analysis, we follow the convention and use life satisfaction since it is an evaluative measure (i.e. it captures a broad assessment of an individual’s wellbeing and is less impacted by day-to-day changes in mood than other measures, such as happiness) and has a large body of evidence supporting its validity and rigour3.
  • Xi is the outcome that is being valued.
  • Wi is a vector of control variables. We control for the main determinants of life satisfaction as given in a 2011 research paper by the UK’s Department for Work and Pensions4.
  • εi is an error term.
  • β1 is an estimate of the association between the outcome of interest Xi and life satisfaction.
If longitudinal data is available (data that surveys the sample people over time), we also control for time-invariant factors. Called a fixed-effects regression, this allows us to further isolate the relationship between the outcome of interest and life satisfaction, increasing the likelihood of an unbiased estimate.

Step 2 – monetising the association between the outcome and subjective wellbeing

Once β1 has been estimated, it is monetised. This allows it to be summed with financial impacts and means it can be included in cost-benefit analysis calculations.

To do this, we use the WELLBY approach. A WELLBY is the monetised value of a one-point change in life satisfaction for one year. The UK uses a WELLBY value of £13,000. This is the average value of a lower-bound and an upper-bound value; these are based on the relationship between health and life satisfaction and income and life satisfaction, respectively. As far as we are aware, there is no research into an equivalent figure in Denmark. We therefore make use of the UK’s WELLBY value as a first approximation.

Two steps are taken in order to translate the UK WELLBY value into a Danish context.
  1. First, we uprate the UK WELLBY value into present day British sterling. We do this suing the latest data from the Office for National Statistics.
  2. We then convert this figure to Danish krone using the World Bank’s purchasing power parity (PPP) exchange rates. This accounts for individuals’ purchasing power when converting, meaning individuals in Denmark would be able to purchase the same basket of goods in Denmark that £13,000 would be able to purchase in the UK.
Once the Danish WELLBY was calculated, it was multiplied with the estimate of 1 to give the monetised value of each outcome.

1. HM Treasury (2022).

2. OECD (2018).

3. Waldron (2010).

4. Fujiwara & Campbell (2011).

Metodebeskrivelse (UK)

2. Outcome-specific estimations

This section gives more detail about the twenty shortlisted outcomes. In particular, it gives a general description, the survey question uses to elicit the value (and to attribute the value), as well as the data set used to derive it. Throughout, one asterisk (*) id used to define the negative answer category and two asterisks (**) are used to define the positive answer category. The value should apply to all individuals moving from * to **.

2.1. Part-time employment

This outcome captures the value of moving from unemployment to part-time employment, where part-time employment is defined as working less than 28 hours per week.

The outcome was estimated using two questions from Understanding Society, one of which asks respondents to describe their current employment situation and another which asks respondents how many hours they work each week. For simplicity, we have combined these survey questions into the following:

Which of these best describes your current employment situation?

  • Self-employed
  • Part-time employed (<28 hours per week)**
  • Full-time employed (≥28 hours per week)
  • Unemployed*
  • Retired
  • On maternity leave
  • Family care or home
  • Full-time student
  • Long-term sick or disabled
  • Government training scheme
  • Unpaid, family business
  • On apprenticeship
  • Doing something else

A fixed-effects regression was used to elicit this value. It is statistically significant at the 1% confidence level.

It should be noted that the value is based on responses from individuals aged 16 and over.

2.2. Healthy relationships

This outcome captures the value of moving from having a relatively poor relationship with your partner (≤7 on a 0-10 scale) to having a good relationship with your partner (8+ on a 0-10 scale).

The key variable of interest uses a survey question from HILDA, where respondents must answer the following question:

How satisfied are you with your relationship with your partner?

  • 0 – Completely dissatisfied*
  • 1*
  • 2*
  • 3*
  • 4*
  • 5*
  • 6*
  • 7*
  • 8**
  • 9**
  • 10 – Completely satisfied**

An OLS regression was used to elicit this value. It is statistically significant at the 1% confidence level.

2.3. Diabetes

This outcome captures the value of moving from being advised to take medication for diabetes to not having to take medication for diabetes.

The key variable of interest uses a survey question from Understanding Society, where respondents must answer the following question:

Has a doctor or other health professional ever told you that you suffer from diabetes?

  • Yes*
  • No**

An OLS regression was used to elicit this value. It is statistically significant at the 1% confidence level.

Note that respondents who answer ‘Yes’ to this question cannot switch to ‘No’. Because of this, we recommend the use of the following question to attribute the wellbeing value of diabetes to individuals:

Does your doctor currently advise that you take medication for diabetes?

  • Yes*
  • No**

2.4. Transport

This outcome captures the value of moving from not walking/cycling short journeys to walking/cycling short journeys, where a short journey is defined as less that 2 or 3 miles.

The key variable of interest uses a survey question from Understanding Society, where respondents must answer the following question:

How often do you personally walk or cycle for short journeys less than 2 or 3 miles?

  • Always**
  • Very often**
  • Quite often**
  • Not very often*
  • Never*

Never*A fixed-effects regression was used to elicit this value. It is statistically significant at the 10% confidence level.

2.5. Addiction

This outcome captures the value of moving from having used illegal drugs in the past year to not having taken illegal drugs in the past year.

The key variable of interest uses a survey question from Understanding Society, where respondents must answer the following question:

In the past year, how many times have you used or taken any illegal drugs?

  • Never**
  • Once or twice
  • Three or four times*
  • Five to ten times*
  • More than ten times*

A fixed-effects regression was used to elicit this value. It is statistically significant at the 1% confidence level.

2.6. Homelessness

This outcome captures the value of moving from homelessness (defined as sleeping rough, sleeping in a vehicle or squatting) to temporary accommodation (defined as a hostel, hotel, crisis accommodation or rehabilitation centre5).

The key variable of interest uses a survey question from Journeys Home, where respondents must answer the following question:

As of today, in what kind of place do you live?

  • A house / townhouse
  • An apartment / unit / flat (includes granny flats and bed-sitters)
  • Caravan / mobile home / cabin / houseboat
  • Boarding house / rooming house / hostel**
  • Hotel or motel room**
  • Crisis accommodation or refuge**
  • Sleeping rough (for example, street, park, tent, train station, improvised shelter)*
  • A car or other vehicle (but not a mobile home)*
  • A squat / abandoned building*
  • Health, treatment, or rehabilitation centre / facility**

A fixed-effects regression was used to elicit this value. It is statistically significant at the 1% confidence level.

2.7. Feeling confident

This outcome captures the value of moving from losing confidence in oneself more than usual to not losing confidence in oneself any more than usual.

The key variable of interest uses a survey question from Understanding Society, where respondents must answer the following question:

Have you recently been losing confidence in yourself?

  • Not at all**
  • No more than usual**
  • Rather more than usual*
  • Much more than usual*

A fixed-effects regression was used to elicit this value. It is statistically significant at the 1% confidence level.

2.8. Sleep

This outcome captures the value of moving from having a poor sleep quality to having a good sleep quality.

The key variable of interest uses a survey question from HILDA, where respondents must answer the following question:

During the past month, how would you rate your sleep quality overall?

  • Very good**
  • Fairly good**
  • Fairly bad*
  • Very bad*

An OLS regression was used to elicit this value. It is statistically significant at the 1% confidence level.

2.9. Conduct problems

This outcome captures the value of a young person reducing their conduct problems from a score of 10 or over to a score of 9 or under (if the survey is self-completed) or from a score of 10 or over to a score of 8 or under (if the survey is not self-completed).

The key variable of interest uses a survey question from Understanding Society’s youth questionnaire, where respondents must answer the following questions:

For each item, please indicate whether the statement is Not True, Somewhat True or Certainly True as best you can. Please give your answers on the basis of how things have been for you over the last six months.

I get very angry and often lose my temper

  • Not True (1)
  • Somewhat True (2)
  • Certainly True (3)

I usually do as I am told

  • Certainly True  (1)
  • Somewhat True (2)
  • Not True (3)

I fight a lot. I can make other people do what I want

  • Not True (1)
  • Somewhat True (2) 
  • Certainly True (3)

I am often accused of lying or cheating

  • Not True (1)
  • Somewhat True (2)
  • Certainly True (3)

I take things that are not mine from home, school or elsewhere

  • Not True (1)
  • Somewhat True (2)
  • Certainly True (3)

A fixed-effects regression was used to elicit this value. It is statistically significant at the 1% confidence level.

2.10. Diet

This outcome captures the value of a young person moving from eating no/few fruit and veg per day to having at least 2-4 portions.

The key variable of interest uses a survey question from Understanding Society’s youth questionnaire, where respondents must answer the following question:

How many portions of fresh fruit or vegetables do you eat on a typical day? One portion is one piece of fruit or one serving of a vegetable or salad item.

  • 5 or more portions**
  • 3-4 portions**
  • 1-2 portions*
  • None*

A fixed-effects regression was used to elicit this value. It is statistically significant at the 5% confidence level.

2.11. Alcohol

This outcome captures the value of a young person moving from drinking alcohol at least once in the past four weeks to not having drank alcohol in the past four weeks.

The key variable of interest uses a survey question from Understanding Society’s youth questionnaire, where respondents must answer the following question:

How many times in the last four weeks have you had an alcoholic drink? That is a whole drink, not just a sip.

  • Most days*
  • Once or twice a week*
  • 2 or 3 times*
  • Once only*
  • Never**

A fixed-effects regression was used to elicit this value. It is statistically significant at the 5% confidence level.

2.12. Increased positive attitude to school

This outcome captures the value of a young person improving their attitude in school from a score of 17 or lower to a score of 18 or over.

The key variable of interest uses a survey question from the Millennium Cohort Study, where respondents must answer the following questions:

How often do you try your best at school?

  • Never (1)
  • Some of the time (2)
  • Most of the time (3)
  • All of the time (4)

How often do you find school interesting?

  • Never (1)
  • Some of the time (2)
  • Most of the time (3)
  • All of the time (4)

How often do you feel unhappy at school?

  • All of the time (1)
  • Most of the time (2)
  • Some of the time (3)
  • Never (4)

How often do you get tired at school?

  • All of the time (1)
  • Most of the time (2)
  • Some of the time (3)
  • Never (4)

How often do you feel school is a waste of time?

  • All of the time (1)
  • Most of the time (2)
  • Some of the time (3)
  • Never (4)

How often do you find it difficult to keep your mind on your work at school?

  • All of the time (1)
  • Most of the time (2)
  • Some of the time (3)
  • Never (4)

An OLS regression was used to elicit this value. It is statistically significant at the 1% confidence level.

2.13. Increased self-esteem

This outcome captures the value of a young person increasing their self-esteem by a certain amount.

The key variable of interest uses a survey question from Understanding Society’s youth questionnaire, where respondents must answer the following question:

For the following list of statements, do you Strongly Agree, Agree, Disagree or Strongly Disagree?

  • I feel I have a number good qualities
  • I am a likeable person
  • I am as able as most people
  • I can usually solve my own problems
  • I feel that I do not have much to be proud of
  • I certainly feel useless at times
  • I am inclined to feel I am a failure
  • At times I feel I am no good at all

A fixed-effects regression was used to elicit this value. It is statistically significant at the 1% confidence level.

2.14. Voluntary work

This outcome captures the value of moving from not undertaking unpaid voluntary work to volunteering at least once per year.

The key variable of interest uses a survey question from the British Household Panel Survey, where respondents must answer the following question:

How often do you do unpaid voluntary work?

  • At least once per week
  • At least once a month
  • Several times per year**
  • Once per year**
  • Never*

An OLS regression was used to elicit this value. It is statistically significant at the 1% confidence level.

Note that the British Household Panel Survey was used to estimate this value. This data set was superseded by Understanding Society in 2009, meaning the data is quite dated. However, we feel that this should not have a significant detrimental impact on the reliability of the estimated value since the relationship between voluntary work and life satisfaction likely hasn’t changed much in fifteen years.

2.15. Physical activity

This outcome captures the value of moving from doing a little/no sport (0-2 on a 0-10 scale) to doing an intense amount of sport (5+ on a 0-10 scale).

The key variable of interest uses a survey question from Understanding Society, where respondents must answer the following question:

On a scale of 0 to 10, with 0 being 'doing no sport at all' to 10 being 'very active through sport', where would you rank yourself?

  • 0 – 'doing no sport at all''
  • 1
  • 2
  • 3
  • 4
  • 5
  • 6
  • 7
  • 8
  • 9
  • 10 – 'very active through sport''

An OLS regression was used to elicit this value. It is statistically significant at the 1% confidence level.

Note that since this outcome uses the same survey question as 2.16 below, these two outcomes cannot be attributed to the same individual.

2.16. Sports

This outcome captures the value of moving from not doing any sport (0 on a 0-10 scale) to doing at least some sport (1+ on a 0-10 scale).

The key variable of interest uses a survey question from Understanding Society, where respondents must answer the following question:

On a scale of 0 to 10, with 0 being 'doing no sport at all' to 10 being 'very active through sport', where would you rank yourself?

  • 0 – 'doing no sport at all''
  • 1
  • 2
  • 3
  • 4
  • 5
  • 6
  • 7
  • 8
  • 9
  • 10 – 'very active through sport''

An OLS regression was used to elicit this value. It is statistically significant at the 1% confidence level.

Note that since this outcome uses the same survey question as 2.15 above, these two outcomes cannot be attributed to the same individual.

2.17. Cultural activities

This outcome captures the value of moving from not having participated/been in the audience of an arts event to having participated/been in the audience of an arts event at least once in the past 12 months.

The key variable of interest uses a survey question from Understanding Society, where respondents must answer the following question:

How often in the past 12 months have you done/attended any cultural activities such as music, dance, art, drama, crafts, creative writing, cinema or reading for pleasure? Please only include events done/attended in your own time or for the purpose of voluntary work.

  • At least once a week**
  • Less often than once a week but at least once a month**
  • Less often than once a month but at least 3 or 4 times a year**
  • Twice in the last 12 months**
  • Once in the last 12 months**
  • I have not done/attended any of these events*

An OLS regression was used to elicit this value. It is statistically significant at the 10% confidence level.

2.18. Financial distress

This outcome captures the value of moving from having been behind with rent/mortgage in the past 12 months to not having been behind with rent/mortgage in the past 12 months.

The key variable of interest uses a survey question from Understanding Society, where respondents must answer the following question:

Many people find it hard to keep up with their housing payments. In the past twelve months, have you ever found yourself behind with your rent/mortgage?

  • Yes*
  • No**

A fixed-effects regression was used to elicit this value. It is statistically significant at the 1% confidence level.

2.19. Social capital – high trust in others

This outcome captures the value of moving from having low trust in others (<4 on a 1-7 scale) to having trust in others (4+ on a 1-7 scale).

The key variable of interest uses a survey question from HILDA, where respondents must answer the following question:

To what extent do you agree or disagree with the following statement: Generally speaking, most people can be trusted.

  • 1 – Strongly disagree*
  • 2*
  • 3*
  • 4**
  • 5**
  • 6**
  • 7 – Strongly agree**

A fixed-effects regression was used to elicit this value. It is statistically significant at the 1% confidence level.

2.20. Feel in control of life

This outcome captures the value of moving from not feeling in control of life (<5 on a 1-7 scale) to feeling in control of life (5+ on a 1-7 scale).

The key variable of interest uses a survey question from HILDA, where respondents must answer the following question:

To what extent do you agree or disagree with the following statement: I can do just about anything I really set my mind to do.

  • 1 – Strongly disagree*
  • 2*
  • 3*
  • 4**
  • 5**
  • 6**
  • 7 – Strongly agree**

A fixed-effects regression was used to elicit this value. It is statistically significant at the 1% confidence level.

2.21. Full-time employment

This outcome captures the value of moving from unemployment to full-time employment, where full-time employment is defined as working at least 28 hours per week.

The outcome was estimated using two questions from Understanding Society, one of which asks respondents to describe their current employment situation and another which asks respondents how many hours they work each week. For simplicity, we have combined these survey questions into the following:

Which of these best describes your current employment situation?

  • Self-employed
  • Part-time employed (<28 hours per week)
  • Full-time employed (≥28 hours per week)**
  • Unemployed*
  • Retired
  • On maternity leave
  • Family care or home
  • Full-time student
  • Long-term sick or disabled
  • Government training scheme
  • Unpaid, family business
  • On apprenticeship
  • Doing something else

A fixed-effects regression was used to elicit this value. It is statistically significant at the 1% confidence level.

It should be noted that the value is based on responses from individuals aged 16 and over. Note also that the value of this outcome is lower than that of ‘Part-time employment’. However, since income is controlled for in the model, the values represents the impact on becoming employed holding income constant. In other words, it only represents the wellbeing impact on employment, not the monetary impact. Therefore, we feel that this finding is not of concern.

2.22. Not worried about crime

This outcome captures the value of moving from not feeling satisfied with how safe you feel (<6 on a 0-10 scale) to feeling satisfied with how safe you feel (6+ on a 0-10 scale).

The key variable of interest uses a survey question from HILDA, where respondents must answer the following question:

On a scale of 0 to 10, with 0 being 'Totally dissatisfied' to 10 being 'Totally satisfied', how satisfied or dissatisfied are you with how safe you feel?

A fixed-effects regression was used to elicit this value. It is statistically significant at the 1% confidence level.

2.23. Self-reported health

This outcome captures the value of moving from having ‘Fair’ or ‘Poor’ self-reported health to having at least a ‘Good’ level of self-reported health.

The key variable of interest uses a survey question from HILDA, where respondents must answer the following question:

In general, would you say your health is:

  • Excellent**
  • Very good**
  • Good**
  • Fair*
  • Poor*

An OLS regression was used to elicit this value. It is statistically significant at the 1% confidence level.

2.24. Loneliness

This outcome captures the value of moving from feeling lonely ‘Often’ to ‘Some of the time’.

The key variable of interest uses a survey question from Understanding Society, where respondents must answer the following question:

How often do you feel lonely?

  • Hardly ever or never
  • Some of the time**
  • Often*

A fixed-effects regression was used to elicit this value. It is statistically significant at the 1% confidence level.

2.25. Parental stress

This outcome captures the value of a parent moving from feeling stressed from meeting the needs of their children (4+ on a 1-7 scale for either of the below questions) to not feeling stressed from meeting the needs of their children (≤3 on a 1-7 scale for both of the below questions).

The key variable of interest uses survey questions from HILDA, where respondents must answer the following questions:

How strongly do you agree or disagree with the following statements?

I often feel tired, worn out or exhausted from meeting the needs of my children

  • 1 – Strongly disagree*
  • 2*
  • 3*
  • 4**
  • 5**
  • 6**
  • 7 – Strongly agree**

I find that taking care of my children is much more work than pleasure

  • 1 – Strongly disagree*
  • 2*
  • 3*
  • 4**
  • 5**
  • 6**
  • 7 – Strongly agree**

An OLS regression was used to elicit this value. It is statistically significant at the 1% confidence level.

2.26. Weight

This outcome captures the value of moving from being obese to being of normal weight, as defined by body mass index (BMI).

The key variable of interest uses a variable derived from individuals’ weight and height metrics from HILDA. We proposed the following question to attribute this outcome to respondents:

What is your body mass index (BMI)? Your BMI can be calculated by dividing your body weight in kilograms by the square of your height in metres.

An OLS regression was used to elicit this value. It is statistically significant at the 1% confidence level.

2.27. Rely on others

This outcome captures the value of moving from not definitely agreeing that there are people who are there for them for all three of the below questions to definitely agreeing that there are people who are there for them for at least one of the below questions.

The key variable of interest uses survey questions from Understanding Society, where respondents must answer the following questions:

How much can you rely on your friends if you have a serious problem?

  • A lot**
  • Somewhat*
  • A little*
  • Not at all*
  • I don't have any friends*

How much can you rely on your immediate family if you have a serious problem?

  • A lot**
  • Somewhat*
  • A little*
  • Not at all*
  • I don't have any immediate family*

How much can you rely on your partner if you have a serious problem?

  • A lot**
  • Somewhat*
  • A little*
  • Not at all*
  • I don't have a partner*

An OLS regression was used to elicit this value. It is statistically significant at the 1% confidence level.

2.28. Education

This outcome captures the value of moving from not having graduated high school to having graduated high school or graduated from university/college or attained a post-graduate degree.

The key variable of interest uses a survey question from Understanding Society, where respondents must answer the following question:

What is the highest educational or school qualification you have obtained?

  • University High Degree (e.g. MSc, PhD)**
  • First degree level qualification including foundation degrees, graduate membership of a professional Institute, PGCE**
  • A Level**
  • AS Level**
  • GCSE**
  • Did not graduate from high school*

An OLS regression was used to elicit this value. It is statistically significant at the 10% confidence level.

2.29. Independence

This outcome captures the value of moving from not being able to be independent at all/independent in a few things to being independent in many things/completely independent.

The key variable of interest uses survey questions from Understanding Society. For simplicity, we have combined some of the questions in order to not overburden respondents.

The next few questions are about tasks that some people may need help with and about help that you may have received in the last month. Please think only about help you need because of long-term physical or mental ill-health, disability or problems relating to old age.

Do you manage to dress or undress, including putting on shoes and socks...

  • On your own (without difficulty)**
  • On your own (with difficulty)*
  • Only with help from someone else*
  • Not at all*

Do you manage to do routine housework or laundry...

  • On your own (without difficulty)**
  • On your own (with difficulty)*
  • Only with help from someone else*
  • Not at all*

Do you manage to shop for food, including getting to the shops, choosing the items, carrying the items home and then unpacking and putting the items away...

  • On your own (without difficulty)**
  • On your own (with difficulty)*
  • Only with help from someone else*
  • Not at all*

Do you manage to take the right amount of medicine at the right times...

  • On your own (without difficulty)**
  • On your own (with difficulty)*
  • Only with help from someone else*
  • Not at all*

An OLS regression was used to elicit this value. It is statistically significant at the 1% confidence level.

2.30. Mental health

This outcome captures the value of moving from suffering from depression/anxiety to not suffering from depression/anxiety.

The key variable of interest uses a survey question from the British Household Panel Survey, where respondents must answer the following question:

Do you suffer from anxiety, depression or bad nerves, psychiatric problems?

  • Yes*
  • No**

A fixed-effects regression was used to elicit this value. It is statistically significant at the 1% confidence level.

2.31. Talks to neighbours regularly

This outcome captures the value of moving from talking to their neighbours ‘Sometimes’ or fewer to talking to their neighbours ‘Often’ or ‘Very often’.

The key variable of interest uses a survey question from HILDA, where respondents must answer the following question:

In general, how often do you chat with your neighbours?

  • Never*
  • Rarely*
  • Occasionally*
  • Sometimes*
  • Often**
  • Very often**

An OLS regression was used to elicit this value. It is statistically significant at the 1% confidence level.

2.31. Member of a social group

This outcome captures the value of moving from not being a member of a social group/not attending events to being a member of a social group/attending events.

The key variable of interest uses survey questions from HILDA, where respondents must answer the following questions:

Are you currently an active member of a sporting, hobby or community-based club or association?

  • Yes**
  • No*

In general, how often do you attend events that bring people together such as fetes, shows, festivals or other community events?

  • Never*
  • Rarely*
  • Occasionally*
  • Sometimes*
  • Often**
  • Very often**

A fixed-effects regression was used to elicit this value. It is statistically significant at the 1% confidence level.

5. Prison or other form of detention” was also defined as temporary accommodation in the original survey question. However, since this raises ethical questions around whether being in prison is better for your wellbeing that being homeless, we have decided to drop this answer category. Since the proportion of respondents choosing this answer option is low, we deem this to have little detrimental impact on the reliability of attribution.

Metodebeskrivelse (UK)

3. References

Fujiwara, D. and Campbell, R. (2011). Valuation Techniques for Social Cost-Benefit Analysis: Stated Preference, Revealed Preference and Subjective Well-Being Approaches. Department for Work and Pensions. Available here.

HM Treasury (2022). The Green Book – Central Government Guidance on Appraisal and Evaluation. Available here.

OECD (2018). Cost-Benefit Analysis and the Environment – Further Developments and Policy Use. Available here.

Waldron, S. (2010). Measuring Subjective Wellbeing in the UK. Office for National Statistics. Available here.

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Metodebeskrivelse (DK)

Sociale værdier i Danmark: Et valghandlingseksperiment

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1. Estimaterne i (2) er kausale, men de viser i sig selv ikke den effekt, som indkomst og de sociale parametre har for livskvalitet, men nærmere den effekt som respondenterne tror, indkomst og de sociale parametre har for livskvalitet. Man kan med andre ord sige, at de kausale estimater er skalerede. Ved at anvende MRS til at værdisætte de sociale parametre, hvor vi deler koefficienten for et socialt parameter med koefficienten for indkomst, overkommer vi denne udfordring under antagelse om, at skaleringsfaktoren er konstant på tværs af modellens parametre.

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Eksempler

Open Social Value Bank ønsker at skabe synlighed og forståelse omkring metoden bag beregning af den økonomiske værdi af trivsel. Trivsel måles som ændringer i en persons livstilfredshed som følge af sociale forandringer.

Nedenfor finder du eksempler relateret til metoden og udvalgte cases:
Ensomhed
Arbejdslyst
Ensomhed:

Case: Indsats mod ensomhed (fiktiv case)

En række sociale- og sundhedsmæssige problemstillinger kan forebygges eller afhjælpes med målrettede ensomhedsindsatser, der øger trivslen for borgeren og reducerer udgifter til social- og sundhedssektoren. I Danmark estimeres der at være 600.000 ensomme borgere, hvilket har en stor økonomisk byrde. Alene vurderes udgifterne til sundhed og pleje, ekstra førtidspensioner og tabt produktion pga. sygefravær at koste samfundet 7,4 mia. kr. årligt, mens trivselsomkostningen, for de 600.000 ensomme borgere, estimeres at være 13,5 mia. kr.

Internetbaseret Kognitiv Adfærdsterapi mod Ensomhed (Fiktiv case)

Indsatsen har til formål at behandle ensomme voksne gennem internetbaseret kognitiv adfærdsterapi (psykologisk behandling). Indsatsen varer 8 uger, koster samlet 400.000 kr. og har i alt 73 deltagere. Det estimeres at målgruppen kan opnå en effektstørrelse på 4,65 målt på UCLA-20 skalaen.

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Arbejdslyst:

Det betaler sig at øge arbejdslysten

Videncenter for God Arbejdslyst indsamler repræsentative data på danskernes arbejdslyst igennem deres GAI-undersøger. Arbejdslyst måles på en skala fra 0-100, som et gennemsnit af tre spørgsmål, der belyser den enkeltes arbejdslyst. I en række rapporter præsenterer de i samarbejde med Kraka Advisory beregninger på værdien af at øge arbejdslysten blandt medarbejdere i danske virksomheder. Konsekvenser ved lav arbejdslyst er bl.a. højere sygefravær, større sandsynlighed for jobskifte, tidligere tilbagetrækning og lavere livstilfredshed.

Fiktiv case: Estimater på gevinster ved at øge arbejdslyst

Rapporten viser et fiktivt eksempel på, hvordan værdien af livstilfredshed kan anvendes i en samfundsøkonomisk analyse af værdien af en indsats. Beregningerne er baseret på en fiktiv virksomheds indsats for at øge arbejdslysten blandt deres medarbejdere. Estimaterne er beregnet på baggrund af samfundsøkonomiske værdier fra Videncenter for God Arbejdslyst og Kraka Advisorys rapporter og OSVB’s værdi for ændringer i livstilfredshed. For at imødekomme usikkerheder, præsenteres den potentielle gevinst øget arbejdslyst har for medarbejdernes trivsel i et spænd på +/- 15% af OSVB’s værdi for livstilfredshed.

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Eksempel

6. Referenser

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