OECD Conference on New Frontiers in Subjective Well-being Measurement, 4 March 2024, Paris, France

1. Using experienced wellbeing measures in
cost-wellbeing analysis: recent developments
Conal Smith
OECD
March 2024

2. The issue: cost-benefit analysis
l'économie politique doit prendre pour
mesure de l'utilité d'un objet le sacrifice
maximum que chaque consommateur
serait disposé à faire pour se le procurer”
(Depuit, 1844, p65).

3. A brief history of cost-wellbeing analysis
HM Treasury Green Book
Campbell and Fujiwara, 2011
The use of subjective wellbeing data for environmental
valuation. Fereira and Moro, 2010
A simple statistical method for establishing how life
events effect happiness. Clark and Oswald, 2002
Inflation/Unemployment trade-off.
Di-Tella, MacCulloch, and Oswald, 2001
Foundations of Hedonic Psychology.
Kahneman, Diener, and Schwarz, 1999
Three-stage wellbeing valuation
Fujiwara, 2013

4. A brief history of cost-wellbeing analysis
HM Treasury Green Book
Campbell and Fujiwara, 2011
The use of subjective wellbeing data for environmental
valuation. Fereira and Moro, 2010
A simple statistical method for establishing how life
events effect happiness. Clark and Oswald, 2002
Inflation/Unemployment trade-off.
Di-Tella, MacCulloch, and Oswald, 2001
Foundations of Hedonic Psychology.
Kahneman, Diener, and Schwarz, 1999
Three-stage wellbeing valuation
Fujiwara, 2013
CV ≈
𝑑𝑊
𝑑𝑋
𝑑𝑊
𝑑𝑌

5. A brief history of cost-wellbeing analysis
HM Treasury Green Book
Campbell and Fujiwara, 2011
The use of subjective wellbeing data for environmental
valuation. Fereira and Moro, 2010
A simple statistical method for establishing how life
events effect happiness. Clark and Oswald, 2002
Inflation/Unemployment trade-off.
Di-Tella, MacCulloch, and Oswald, 2001
Foundations of Hedonic Psychology.
Kahneman, Diener, and Schwarz, 1999
Three-stage wellbeing valuation
Fujiwara, 2013
CV ≈
𝑑𝑊
𝑑𝑋
𝑑𝑊
𝑑𝑌
Compensating variation – how much
we would need to pay you to leave
indifferent to whether you
experienced non-market outcome X

6. A brief history of cost-wellbeing analysis
HM Treasury Green Book
Campbell and Fujiwara, 2011
The use of subjective wellbeing data for environmental
valuation. Fereira and Moro, 2010
A simple statistical method for establishing how life
events effect happiness. Clark and Oswald, 2002
Inflation/Unemployment trade-off.
Di-Tella, MacCulloch, and Oswald, 2001
Foundations of Hedonic Psychology.
Kahneman, Diener, and Schwarz, 1999
Three-stage wellbeing valuation
Fujiwara, 2013
CV ≈
𝑑𝑊
𝑑𝑋
𝑑𝑊
𝑑𝑌
Impact on life
satisfaction of change in
a non-market outcome

7. A brief history of cost-wellbeing analysis
HM Treasury Green Book
Campbell and Fujiwara, 2011
The use of subjective wellbeing data for environmental
valuation. Fereira and Moro, 2010
A simple statistical method for establishing how life
events effect happiness. Clark and Oswald, 2002
Inflation/Unemployment trade-off.
Di-Tella, MacCulloch, and Oswald, 2001
Foundations of Hedonic Psychology.
Kahneman, Diener, and Schwarz, 1999
Three-stage wellbeing valuation
Fujiwara, 2013
CV ≈
𝑑𝑊
𝑑𝑋
𝑑𝑊
𝑑𝑌
Impact on life
satisfaction of income

8. Problems with cost-wellbeing analysis
• Endogeneity and selection effects

9. Problems with cost-wellbeing analysis
• Endogeneity and selection effects

10. Problems with cost-wellbeing analysis
• Endogeneity and selection effects

11. Problems with cost-wellbeing analysis
• Geospatial and temporal matching
• Life evaluation measures – such as life satisfaction-
are global assessments of how we are doing
• It is very difficult to link them to the impact of
specific places, environments, and activities
• This makes it very difficult to identify the impact of
places, environments or activities on life
satisfaction
• The impact of differences in environmental
characteristics or the qualities of different
activities might be very small compared to other
drivers of life satisfaction

12. A brief history of cost-wellbeing analysis
HM Treasury Green Book
Campbell and Fujiwara, 2011
The use of subjective wellbeing data for environmental
valuation. Fereira and Moro, 2010
A simple statistical method for establishing how life
events effect happiness. Clark and Oswald, 2002
Inflation/Unemployment trade-off.
Di-Tella, MacCulloch, and Oswald, 2001
Experienced utility as a standard of policy
evaluation. Kahneman and Sugden, 2005
Foundations of Hedonic Psychology.
Kahneman, Diener, and Schwarz, 1999
Three-stage wellbeing valuation
Fujiwara, 2013
Day reconstruction method.
Kahneman, Krueger, Schkade, Schwarz, Stone, 2004
Developments in the Day Reconstruction
Method. Krueger in Smith and Stone, 2014

13. Experienced wellbeing measures
•Key obstacles:
•Availability of experienced wellbeing data – this remains much
scarcer than evaluative measures since it requires either a time use
survey or experience sampling
•Difficulty in obtaining a meaningful income coefficient for
measures of experienced wellbeing
CV ≈
𝑑𝑊
𝑑𝑋
𝑑𝑊
𝑑𝑌
Income coefficients for life satisfaction: 0.324 – 1.1
Income coefficients for affect: 0.04 - 0.09

14. Experienced wellbeing measures
•Key obstacles:
•Availability of experienced wellbeing data – this remains much
scarcer than evaluative measures since it requires either a time use
survey or experience sampling
•Difficulty in obtaining a meaningful income coefficient for
measures of experienced wellbeing
CV ≈
𝑑𝑊
𝑑𝑋
𝑑𝑊
𝑑𝑌
Income coefficients for life satisfaction: 0.324 – 1.1
Income coefficients for affect: 0.04 - 0.09

15. An application – valuing features of urban design
Photo: Emma Stewart, RNZ 22/9/22

16. Value of urban green space: meta-analysis
• Hedonic pricing estimates dominate
• Values cluster fairly closely despite
different countries/incomes
• Estimates cover a relatively narrow
range of outcomes
– Distance to nearest park
– Tree coverage
– Percentage green space within a given
distance

17. Value of urban green space: meta-analysis
• Hedonic pricing estimates dominate
• Values cluster fairly closely despite
different countries/incomes
• Estimates cover a relatively narrow
range of outcomes
– Distance to nearest park (km)
– Tree coverage (% increase)
– Percentage green space within a given
distance

18. Data
• Mappiness – collected by George MacKerron
between 2010 and 2016
• Opt-in survey of i-phone users
• Very large sample:
• c17,000 respondents
• c1.9 million EWB observations
• All observations geo-coded and time-stamped
• Results overlaid with UK land cover database

19. Method
• Where W is life satisfaction, A is a duration-weighted measure of experienced wellbeing, Y is income, and X
is the outcome of interest:
• Standard cost-wellbeing valuation: CV ≈
d𝑊
dX
d𝑊
dY

20. Method
• Where W is life satisfaction, A is a duration-weighted measure of experienced wellbeing, Y is income, and X
is the outcome of interest:
• Standard cost-wellbeing valuation: CV ≈
d𝑊
dX
d𝑊
dY
• Experienced wellbeing valuation: 𝐶𝑉 ≈
𝑑𝐴
𝑑𝑋
𝑥
𝑑𝑊
𝑑𝐴
𝑑𝑊
𝑑𝑌

21. Method
• Where W is life satisfaction, A is a duration-weighted measure of experienced wellbeing, Y is income, and X
is the outcome of interest:
• Standard cost-wellbeing valuation: CV ≈
d𝑊
dX
d𝑊
dY
• Experienced wellbeing valuation: 𝐶𝑉 ≈
𝑑𝐴
𝑑𝑋
𝑥
𝑑𝑊
𝑑𝐴
𝑑𝑊
𝑑𝑌

22. Method
• Where W is life satisfaction, A is a duration-weighted measure of experienced wellbeing, Y is income, and X
is the outcome of interest:
• Standard cost-wellbeing valuation: CV ≈
d𝑊
dX
d𝑊
dY
• Experienced wellbeing valuation: 𝐶𝑉 ≈
𝑑𝐴
𝑑𝑋
𝑥
𝑑𝑊
𝑑𝐴
𝑑𝑊
𝑑𝑌

23. Method
• Where W is life satisfaction, A is a duration-weighted measure of experienced wellbeing, Y is income, and X
is the outcome of interest:
• Standard cost-wellbeing valuation: CV ≈
d𝑊
dX
d𝑊
dY
• Experienced wellbeing valuation: 𝐶𝑉 ≈
𝑑𝐴
𝑑𝑋
𝑥
𝑑𝑊
𝑑𝐴
𝑑𝑊
𝑑𝑌

24. Results (1): Income coefficients
𝐶𝑉 ≈
𝑑𝐴
𝑑𝑋
𝑥
𝑑𝑊
𝑑𝐴
𝑑𝑊
𝑑𝑌

25. Results (1): Income coefficients
𝐶𝑉 ≈
𝑑𝐴
𝑑𝑋
𝑥
𝑑𝑊
𝑑𝐴
𝑑𝑊
𝑑𝑌

26. Results (2): Life satisfaction and EWB
Table 5. Experienced wellbeing and life satisfaction: regression models
(7) (8) (9) (10) (11)
VARIABLES
Life sat
(0-10)
Life sat
(0-10)
Regional
mean life
sat (0-10)
EWB:
happiness
(0-100)
EWB:
happiness
(0-100)
Age -0.07*** -0.09*** -0.38***
(0.01) (0.01) (0.01)
Age squared 0.00*** 0.00*** 0.00***
(0.00) (0.00) (0.00)
Male -0.06** -0.08*** 0.60***
(0.02) (0.02) (0.03)
In relationship 0.52*** 0.50*** 2.06***
(0.02) (0.03) (0.04)
Never married - - -
Married 0.15** 0.09+ 0.32***
(0.05) (0.05) (0.07)
Separated -0.21** -0.23** -2.82***
(0.08) (0.08) (0.11)
Divorced -0.11* -0.15** -0.70***
(0.05) (0.05) (0.07)
Widowed 0.00 -0.14 -0.50*
(0.23) (0.23) (0.22)
Bank holiday response -0.00 0.03 4.36***
(0.06) (0.07) (0.10)
Log equivalised HH income 0.21*** 1.70***
(0.01) (0.02)
EWB 0.025*** 0.025***
(0.00) (0.00)
Mean regional HH income 0.30**
(0.11)
Mean regional EWB 0.033***
(0.00)
In London -5.29***
(0.35)
During Olympics 0.48
(0.82)
In London during Olympics 1.96*
(0.89)
Day/month/year controls Yes Yes No Yes Yes
Constant 5.87*** 4.23*** 1.06 70.67*** 59.24***
(0.15) (0.18) (1.18) (0.36) (0.28)
Observations 22,692 21,243 773 611,131 1,965,735
R-squared 0.16 0.18 0.20 0.02 0.02
Number of user ids 17,937
Robust standard errors in parentheses. *** p<0.001, ** p<0.01, * p<0.05, + p<0.10
𝐶𝑉 ≈
𝑑𝐴
𝑑𝑋
𝑥
𝑑𝑊
𝑑𝐴
𝑑𝑊
𝑑𝑌

27. Table 5. Experienced wellbeing and life satisfaction: regression models
(7) (8) (9) (10) (11)
VARIABLES
Life sat
(0-10)
Life sat
(0-10)
Regional
mean life
sat (0-10)
EWB:
happiness
(0-100)
EWB:
happiness
(0-100)
Age -0.07*** -0.09*** -0.38***
(0.01) (0.01) (0.01)
Age squared 0.00*** 0.00*** 0.00***
(0.00) (0.00) (0.00)
Male -0.06** -0.08*** 0.60***
(0.02) (0.02) (0.03)
In relationship 0.52*** 0.50*** 2.06***
(0.02) (0.03) (0.04)
Never married - - -
Married 0.15** 0.09+ 0.32***
(0.05) (0.05) (0.07)
Separated -0.21** -0.23** -2.82***
(0.08) (0.08) (0.11)
Divorced -0.11* -0.15** -0.70***
(0.05) (0.05) (0.07)
Widowed 0.00 -0.14 -0.50*
(0.23) (0.23) (0.22)
Bank holiday response -0.00 0.03 4.36***
(0.06) (0.07) (0.10)
Log equivalised HH income 0.21*** 1.70***
(0.01) (0.02)
EWB 0.025*** 0.025***
(0.00) (0.00)
Mean regional HH income 0.30**
(0.11)
Mean regional EWB 0.033***
(0.00)
In London -5.29***
(0.35)
During Olympics 0.48
(0.82)
In London during Olympics 1.96*
(0.89)
Day/month/year controls Yes Yes No Yes Yes
Constant 5.87*** 4.23*** 1.06 70.67*** 59.24***
(0.15) (0.18) (1.18) (0.36) (0.28)
Observations 22,692 21,243 773 611,131 1,965,735
R-squared 0.16 0.18 0.20 0.02 0.02
Number of user ids 17,937
Robust standard errors in parentheses. *** p<0.001, ** p<0.01, * p<0.05, + p<0.10
Results (2): Life satisfaction and EWB
𝐶𝑉 ≈
𝑑𝐴
𝑑𝑋
𝑥
𝑑𝑊
𝑑𝐴
𝑑𝑊
𝑑𝑌
2A: Cross-sectional estimate

28. Table 5. Experienced wellbeing and life satisfaction: regression models
(7) (8) (9) (10) (11)
VARIABLES
Life sat
(0-10)
Life sat
(0-10)
Regional
mean life
sat (0-10)
EWB:
happiness
(0-100)
EWB:
happiness
(0-100)
Age -0.07*** -0.09*** -0.38***
(0.01) (0.01) (0.01)
Age squared 0.00*** 0.00*** 0.00***
(0.00) (0.00) (0.00)
Male -0.06** -0.08*** 0.60***
(0.02) (0.02) (0.03)
In relationship 0.52*** 0.50*** 2.06***
(0.02) (0.03) (0.04)
Never married - - -
Married 0.15** 0.09+ 0.32***
(0.05) (0.05) (0.07)
Separated -0.21** -0.23** -2.82***
(0.08) (0.08) (0.11)
Divorced -0.11* -0.15** -0.70***
(0.05) (0.05) (0.07)
Widowed 0.00 -0.14 -0.50*
(0.23) (0.23) (0.22)
Bank holiday response -0.00 0.03 4.36***
(0.06) (0.07) (0.10)
Log equivalised HH income 0.21*** 1.70***
(0.01) (0.02)
EWB 0.025*** 0.025***
(0.00) (0.00)
Mean regional HH income 0.30**
(0.11)
Mean regional EWB 0.033***
(0.00)
In London -5.29***
(0.35)
During Olympics 0.48
(0.82)
In London during Olympics 1.96*
(0.89)
Day/month/year controls Yes Yes No Yes Yes
Constant 5.87*** 4.23*** 1.06 70.67*** 59.24***
(0.15) (0.18) (1.18) (0.36) (0.28)
Observations 22,692 21,243 773 611,131 1,965,735
R-squared 0.16 0.18 0.20 0.02 0.02
Number of user ids 17,937
Robust standard errors in parentheses. *** p<0.001, ** p<0.01, * p<0.05, + p<0.10
Results (2): Life satisfaction and EWB
𝐶𝑉 ≈
𝑑𝐴
𝑑𝑋
𝑥
𝑑𝑊
𝑑𝐴
𝑑𝑊
𝑑𝑌
2B: Fixed effects for regional
mean life satisfaction

29. Table 5. Experienced wellbeing and life satisfaction: regression models
(7) (8) (9) (10) (11)
VARIABLES
Life sat
(0-10)
Life sat
(0-10)
Regional
mean life
sat (0-10)
EWB:
happiness
(0-100)
EWB:
happiness
(0-100)
Age -0.07*** -0.09*** -0.38***
(0.01) (0.01) (0.01)
Age squared 0.00*** 0.00*** 0.00***
(0.00) (0.00) (0.00)
Male -0.06** -0.08*** 0.60***
(0.02) (0.02) (0.03)
In relationship 0.52*** 0.50*** 2.06***
(0.02) (0.03) (0.04)
Never married - - -
Married 0.15** 0.09+ 0.32***
(0.05) (0.05) (0.07)
Separated -0.21** -0.23** -2.82***
(0.08) (0.08) (0.11)
Divorced -0.11* -0.15** -0.70***
(0.05) (0.05) (0.07)
Widowed 0.00 -0.14 -0.50*
(0.23) (0.23) (0.22)
Bank holiday response -0.00 0.03 4.36***
(0.06) (0.07) (0.10)
Log equivalised HH income 0.21*** 1.70***
(0.01) (0.02)
EWB 0.025*** 0.025***
(0.00) (0.00)
Mean regional HH income 0.30**
(0.11)
Mean regional EWB 0.033***
(0.00)
In London -5.29***
(0.35)
During Olympics 0.48
(0.82)
In London during Olympics 1.96*
(0.89)
Day/month/year controls Yes Yes No Yes Yes
Constant 5.87*** 4.23*** 1.06 70.67*** 59.24***
(0.15) (0.18) (1.18) (0.36) (0.28)
Observations 22,692 21,243 773 611,131 1,965,735
R-squared 0.16 0.18 0.20 0.02 0.02
Number of user ids 17,937
Robust standard errors in parentheses. *** p<0.001, ** p<0.01, * p<0.05, + p<0.10
Results (2): Life satisfaction and EWB
0.108 / 1.960 = 0.055
𝐶𝑉 ≈
𝑑𝐴
𝑑𝑋
𝑥
𝑑𝑊
𝑑𝐴
𝑑𝑊
𝑑𝑌
2C: Difference in difference
• Impact of London
Olympics on EWB
• We can compare this to
the impact of the
London Olympics on life
satisfaction from Dolan
et al (2019)

30. Results (3): urban green space and EWB
Table 4. Impact of environmental amenities on experienced wellbeing
(1) (2) (3) (4) (5) (6)
Dependent variable: experienced happiness (0-100)
Alone - - -
- - -
With partner 3.53*** 3.65*** 3.66***
(0.03) (0.03) (0.03)
With child 0.46*** 0.39*** 0.39***
(0.05) (0.05) (0.05)
With relative 0.80*** 0.75*** 0.76***
(0.04) (0.05) (0.05)
With peers -0.24*** -0.30*** -0.29***
(0.04) (0.05) (0.05)
With client 1.20*** 1.18*** 1.18***
(0.09) (0.10) (0.10)
With friend 4.19*** 4.07*** 4.09***
(0.04) (0.05) (0.05)
With other person -0.57*** -0.65*** -0.64***
(0.08) (0.09) (0.09)
Indoors - - - - - -
- - - - - -
Outdoors 2.13*** 2.81*** 2.82*** 1.99*** 1.99*** 2.90***
(0.04) (0.04) (0.05) (0.05) (0.05) (0.05)
In vehicle -3.53*** 0.07 0.14* -3.58*** -3.58*** 0.24***
(0.05) (0.06) (0.07) (0.05) (0.05) (0.07)
At home - - - - - -
- - - - - -
Not work or home 3.59*** 1.84*** 1.67*** 3.45*** 3.44*** 1.70***
(0.03) (0.03) (0.04) (0.04) (0.04) (0.04)
Work -4.16*** -1.60*** -1.99*** -4.66*** -4.67*** -1.98***
(0.03) (0.04) (0.05) (0.04) (0.04) (0.05)
First response -6.29*** -5.92*** -5.99*** -6.37*** -6.37*** -6.00***
(0.11) (0.10) (0.12) (0.13) (0.13) (0.12)
2nd - 11th response -2.75*** -2.73*** -2.72*** -2.75*** -2.75*** -2.73***
(0.04) (0.04) (0.05) (0.05) (0.05) (0.05)
12th
+ response - - - - - -
- - - - - -
Bank holiday response 2.80*** 1.30*** 1.24*** 2.87*** 2.87*** 1.25***
(0.08) (0.07) (0.08) (0.08) (0.08) (0.08)
𝐶𝑉 ≈
𝑑𝐴
𝑑𝑋
𝑥
𝑑𝑊
𝑑𝐴
𝑑𝑊
𝑑𝑌

31. Table 4. Impact of environmental amenities on experienced wellbeing
Controls are included for time of day, day of week, month, year, and weather conditions (wind, precipitation) in
all regressions. All variables are 0/1 dummies except Distance to nearest park and Living in London and
distance to nearest park.
(1) (2) (3) (4) (5) (6)
Dependent variable: experienced happiness (0-100)
Built up urban area - - -
- - -
Marine and coast 4.36*** 2.73*** 2.54***
(0.25) (0.24) (0.24)
Mountains and heath 3.63*** 2.21*** 2.18***
(0.37) (0.36) (0.37)
Forest and woodland 1.77*** 0.72*** 0.52***
(0.11) (0.11) (0.11)
Semi-natural grass 3.03*** 1.98*** 1.78***
(0.17) (0.16) (0.16)
Arable and farmland 1.84*** 0.88*** 0.75***
(0.06) (0.05) (0.06)
Fresh water and rivers 1.16*** 0.48* 0.51**
(0.20) (0.19) (0.19)
Suburban 0.50*** 0.11*** -0.06+
(0.03) (0.03) (0.03)
Inland rock 1.32*** 0.91*** 0.90**
(0.28) (0.27) (0.27)
Distance to nearest
park (km) 0.08*** 0.09*** 0.05***
(0.01) (0.01) (0.01)
Distance to nearest
park if in London (km) -0.81*** -0.28*
(0.12) (0.11)
Constant 68.34*** 62.65*** 63.81*** 69.44*** 69.44*** 63.83***
(0.13) (0.13) (0.32) (0.33) (0.33) (0.32)
Region controls No No Yes Yes Yes Yes
Activity controls No Yes Yes No No Yes
Observations 2,704,431 2,704,431 2,064,642 2,064,642 2,064,642 2,064,642
R-squared 0.05 0.12 0.12 0.05 0.05 0.12
Number of respondents 51,801 51,801 35,012 35,012 35,012 35,012
Robust standard errors in parentheses. *** p<0.001, ** p<0.01, * p<0.05, + p<0.10
Results (3): urban green space and EWB
𝐶𝑉 ≈
𝑑𝐴
𝑑𝑋
𝑥
𝑑𝑊
𝑑𝐴
𝑑𝑊
𝑑𝑌
3A: Forest cover

32. Table 4. Impact of environmental amenities on experienced wellbeing
Controls are included for time of day, day of week, month, year, and weather conditions (wind, precipitation) in
all regressions. All variables are 0/1 dummies except Distance to nearest park and Living in London and
distance to nearest park.
(1) (2) (3) (4) (5) (6)
Dependent variable: experienced happiness (0-100)
Built up urban area - - -
- - -
Marine and coast 4.36*** 2.73*** 2.54***
(0.25) (0.24) (0.24)
Mountains and heath 3.63*** 2.21*** 2.18***
(0.37) (0.36) (0.37)
Forest and woodland 1.77*** 0.72*** 0.52***
(0.11) (0.11) (0.11)
Semi-natural grass 3.03*** 1.98*** 1.78***
(0.17) (0.16) (0.16)
Arable and farmland 1.84*** 0.88*** 0.75***
(0.06) (0.05) (0.06)
Fresh water and rivers 1.16*** 0.48* 0.51**
(0.20) (0.19) (0.19)
Suburban 0.50*** 0.11*** -0.06+
(0.03) (0.03) (0.03)
Inland rock 1.32*** 0.91*** 0.90**
(0.28) (0.27) (0.27)
Distance to nearest
park (km) 0.08*** 0.09*** 0.05***
(0.01) (0.01) (0.01)
Distance to nearest
park if in London (km) -0.81*** -0.28*
(0.12) (0.11)
Constant 68.34*** 62.65*** 63.81*** 69.44*** 69.44*** 63.83***
(0.13) (0.13) (0.32) (0.33) (0.33) (0.32)
Region controls No No Yes Yes Yes Yes
Activity controls No Yes Yes No No Yes
Observations 2,704,431 2,704,431 2,064,642 2,064,642 2,064,642 2,064,642
R-squared 0.05 0.12 0.12 0.05 0.05 0.12
Number of respondents 51,801 51,801 35,012 35,012 35,012 35,012
Robust standard errors in parentheses. *** p<0.001, ** p<0.01, * p<0.05, + p<0.10
Results (3): urban green space and EWB
𝐶𝑉 ≈
𝑑𝐴
𝑑𝑋
𝑥
𝑑𝑊
𝑑𝐴
𝑑𝑊
𝑑𝑌
3B: Distance to the nearest park

33. $-
$1,000.00
$2,000.00
$3,000.00
$4,000.00
$5,000.00
$6,000.00
$7,000.00
$8,000.00
$9,000.00
EWB estimate (cross-
section)
EWB estimate (Olympics) Hedonic pricing (low) Hedonic pricing (high)
Household value of selected urban green space features
1% increase in forest cover 100m decrease in distance to nearest park
Comparison of EWB values with estimates from
hedonic pricing studies

34. Comparison of EWB values with estimates from
hedonic pricing studies
$-
$1,000.00
$2,000.00
$3,000.00
$4,000.00
$5,000.00
$6,000.00
$7,000.00
$8,000.00
$9,000.00
EWB estimate (cross-
section)
EWB estimate (Olympics) Hedonic pricing (low) Hedonic pricing (high)
Household value of selected urban green space features
1% increase in forest cover 100m decrease in distance to nearest park

35. Discussion
• Value estimates with the strongest identification strategy for the relationship between experienced
wellbeing and life satisfaction are higher than hedonic pricing estimates by 16% (forest cover) and 52%
(distance to park). This suggests that hedonic pricing estimates might under-estimate the value of urban
green space
• The type of urban green space appears to matter – semi-natural grassland has a much higher value than
woodland
• Applying experienced wellbeing measures to valuing non-market outcomes can produce plausible results
– MacKerron and Smith (2023)
– Krekel and MacKerron (2023)
• Next steps:
– Replication with datasets other than Mappiness
– Incorporating better measures of environmental amenity into Mappiness (e.g. urban canopy cover database)
– Testing the approach on a wider range of non-market outcomes

36. Acknowledgments
George MacKerron
University of Sussex
Arthur Grimes
V.U.W.
Kate Prickett
V.U.W.