Presentation at the HLEG thematic workshop on "Multidimensional Subjective Well-being", 30-31 October 2014, Turin, Italy, http://oe.cd/HLEG-workshop-subjective-wb-2014

1. Subjective Well-being: Time and Context
Andrew E. Clark (Paris School of Economics - CNRS)
http://www.parisschoolofeconomics.com/clark-andrew/
OECD HLEG
Turin
October 30th 2014

2. In terms of the correlates of subjective well-being,
I would like to ask three questions.
Two of these have to do with time, and one with
place (as it were).
I think that these are fascinating research
questions in their own right.
But that it is also crucial to answer them if we are
serious about thinking of a subjective well-being
policy.

3. 1) Do we adapt to everything?
2) If the child makes the man, then what is the
point of (adult) well-being interventions?
3) Who is most affected by which well-being
policy? (i.e. going beyond one estimated mean
effect for the whole population).

4. 1) Adaptation
Adaptation to income has been proposed as one explanation
of the Easterlin Paradox. With adaptation to income we
have a well-being function of:
W = W(y, yi,t-1, ....)
We suppose that W1 > 0, as is standard, but that W2 < 0: as
past income rises, my well-being falls (past income acts
as a benchmark or deflator).
If W1 + W2 = 0, then a rise in income has no long-run effect
on well-being.

6. There are a number of contributions suggesting
adaptation.
Using SOEP data, Di Tella et al. (2010) show
that complete adaptation to rising income occurs
within four years.
Wunder (2009) estimates that the improvement
in the financial situation in Germany from 1985
to 2006 was entirely mopped up by adaptation to
material well-being, which he calls
“desensitisation to the hedonic effects of
income”

7. Clark (1999) suggests that adaptation to changes in labour
income (while staying in the same job at the same
firm) in British Household Panel Survey (BHPS) data
occurs within one year.
Log current monthly pay 0.086 0.486 0.042 0.038
(0.071) (0.166) (0.072) (0.072)
Log current monthly hours -0.081 -0.428 0.114 0.067
(0.215) (0.295) (0.236) (0.219)
Log monthly pay one year ago .. -0.442 .. ..
(0.163)
Log monthly hours one year a g o .. 0.523 .. ..
(0.288)
% Change in pay/100 .. .. 0.439 ..
(0.146)
% Change in hours/100 .. .. -0.518 ..
(0.285)
% Change in hourly wage/100 .. .. .. 0.450
(0.126)

8. If we believe these results, then rising income doesn’t
matter for subjective well-being in the long run (in
rich countries).
Policy implication:
“Money/possessions aren’t making us any happier: we
should spend our time concentrating on X instead”
Candidates for X:
A (good) job
Marriage/Family
Social Activities
Freedom/Democracy
Health
Religion
But what if we find adaptation here too?

9. SOEP Results: there is little adaptation to unemployment
Unemployment starts bad, and stays bad

10. We get used to marriage

11. And we get used to divorce

12. Even widowhood is worse at the beginning than afterwards

13. And we can’t even count on our children

14. These adaptation results are identical in
BHPS data (Clark and Georgellis,
2013).
And in RLMS data (Clark and
Uglanova, 2012).
With one exception in the latter

15. Marriage works in Russia
0.6
0.4
0.2
0
-0.2
-0.4
-0.6
-0.8
-1
-4 -3 -2 -1 0 1 2 3 4 5
Number of years before and after the event. Marriage
Life satisfaction
0.6
0.4
0.2
0
-0.2
-0.4
-0.6
-0.8
-1
-4 -3 -2 -1 0 1 2 3 4 5
Number of years before and after the event. Marriage
Life satisfaction
Both for men
And for women

16. Rudolf and Kang (2013) also find that
marriage is lastingly good in Korea
(for men).

17. There is no adaptation to poverty in SOEP data

18. There is either partial (Oswald and
Powdthavee, 2008) or little (Lucas, 2007)
adaptation to disability (debate over method).
Wu (2001) considers health adaptation to an
exogenous event: heart attacks. New heart
conditions affect emotional health less for
individuals who have had such a condition in
the past.
Riis et al. (2005) uncover evidence of
adaptation to hemodialysis.
But there is a positive impact of cosmetic
surgery on subjective wellbeing, which is long-lasting
in some cases.

19. In the labour market, there is adaptation to
self-employment within three years, and to
unionization.
On the contrary, Burchell (2011) finds that
there is little adaptation to job insecurity in
BHPS data
There is adaptation to moving house in
BHPS (Nowok et al., 2013) and HILDA
(Frijters et al. 2011) data.

20. A summary table from six recent papers.
Colonne1
Anusic et al.(2014):
SHP
Clark et al. (2008):
SOEP
Clark and Georgellis
(2013): BHPS
Clark and Uglanova
(2011): RLMS
Rudolf and Kang (2014):
KLIPS
Frijters et al.
(2011): HILDA
Unemployment Partial None None None No Data F/None M
Marriage Full? Full Full None Full F/Partial M Full
Divorce/Separation Full/Over-full Full/Over-full Full Full F/None M Full
Widowhood Partial Full Full Full None F/Full M
Death of Spouse/Child None
Childbirth Full/Over-full Full/Over-full Full/Over-full Full/Over-full Full
Moved House Full
Disability Partial
Illness/Injury Partial
• The empirical results thus suggest that there is adaptation
in economic and social life, but that individuals take
longer to become used to some states than to others.
• This seems in particular to apply to negative events
(unemployment, insecurity, poverty and disability): is
there loss-aversion in adaptation?

21. I did want to say the word
“multidimensional” at some point today
Almost all of the work above has used life
satisfaction as the dependent variable.
But what do we know about adaptation in
terms of positive and negative effect?
Or in terms of eudaimonia?

22. 2) Does the Child Make the Man?
• Data from the British Cohort Study on children
born in1970. 8,868 obs.
• Aim: Explain adult life-satisfaction (0-10) at age
34: “How dissatisfied or satisfied are you about
the way your life has turned out so far?”
• We explain life-satisfaction by seven adult
outcome variables, three sets of childhood
characteristics, and family characteristics

23. 23
Economic Log income (equivalised)
Educational achievement
Employed (measured as not
unemployed)
at 34
by 34
at 34
Social Good conduct (= -no. of
crimes)
Has a partner
at 16-34
at 34
Personal Self-perceived health
Emotional health
at 26
at 26
Adult outcomes

24. • We measure emotional health and self-perceived
health at age 26 rather than at 34
• This avoids the charge that these are
synonyms of life-satisfaction rather than
predictors of it
• All of these seven adult outcomes can
depend on family background and the
childhood variables
• And so does life satisfaction itself directly24

25. • Childhood variables include variables
relating to the child and to the parents
(“family background”)
• Three main dimensions of child
development – intellectual performance,
social behaviour and emotional health.
25

26. • The BCS data provide us with
measurements on the three child variables at
5, 10 and 16.
• We also have measurements on the family at
different ages
• For simplicity we consolidate these into the
two sets of family variables
26

27. 27
Childhood variables
Age of child
Child characteristics
Intellectual performance 5, 10, 16
Good conduct 5, 10, 16
Emotional health 5, 10, 16
Family background
Economic
Father’s socio-economic group 10
Family income 10
Number of siblings 10
Father in work 0, 5, 10 average
Mother’s and father’s age on
--
leaving full-time education
Psycho-social
Mother’s emotional health 5, 10 average
Child conceived within marriage --
Both parents still together 10

28. Predictors of life-satisfaction at 34
Using adult
variables only
Using childhood
variables only Using both
Log income 5.5 5.2
Educational achievement 3.5 2.9
Employed 8.5 8.2
Good conduct 6.6 6.1
Has a partner 11.6 11.3
Self-perceived health (26) 6.8 6.5
Emotional health (26) 20.4 18.1
Intellectual performance (5 10 16) 4.5 -3.5
Good conduct (5 10 16) 8.5 5.2
Emotional health (5 10 16) 17.4 9.8
Family Economic 5.5 2.5
Family Psychosocial 3.0 2.4
Female 6.8 8.2 7.2
Observations 8,868 8,868 8,868
28
Partial correlation coefficients x100

29. 29
Structural equations for adult success

30. • At what stage of an individual’s
development can we predict their adult
outcomes?
• The proper test of predictability is the R2s:
these appear in the following Table
30
Does the child reveal the adult?

31. 31
Predicting adult outcomes from
different ages of childhood
• Apart from education, most adult variables cannot be
well-predicted from family background.
• We predict better and better as we add later ages
• It is not the case that everything is fixed by age 5.

32. Child emotional health is the largest predictor
of adult life satisfaction.
So what affects child emotional health?
Our recent work on ALSPAC has emphasised
childhood financial difficulties, the sibship,
moving house, and parental separation (and
arguing).
32

33. Not everyone’s well-being is affected by
income, education, unemployment etc. in the
same way.
We can identify heterogeneous effects ex ante,
or let the data decide.
33
3) Was it Good for You?

34. If we let the data decide, we can use finite
mixture models. These divide the data up into
a number j of different W = βj’X regressions,
with each observation i having a probability pij
of belonging to the jth regression (with the sum
over all j’s of pij being one).
This has been applied to well-being and
income, with the marginal effect of income on
well-being is being different across classes
34

35. We can also consider quantile regression
models, where the effect of a certain variable
differs across the well-being distribution.
35

36. Or we can ex ante cut the sample by sex, age,
education and so on.
I often say that men are more comparison-sensitive
than women, for example.
And we might expect the higher-educated to
have a different well-being relationship to
income, if education raises aspirations.
36

37. The variable used to define heterogeneity in
well-being can be contextual, as in the work on
social interactions.
Unemployment has a smaller effect on
subjective well-being in high-unemployment
regions, for example.
37

38. Along these lines, we can ask why some
individuals are less affected than others by
negative life shocks.
This is the analysis of resilience.
Which brings us back to cohort analysis. Are
there specific events in childhood that make
the individual more able to bounce back from
adverse events in adulthood?
38