Transcript Ballas, D.

Exploring geographies of
happiness and well-being
in Britain
Dimitris Ballas
Social and Spatial Inequalities (SASI)
research group
Department of Geography
University of Sheffield
http://www.sheffield.ac.uk/sasi
ESRC-funded research fellowship
Understanding Population Trends And Processes (UPTAP)
Aims (1)
• Investigate different definitions of happiness and explore
the degree to which happiness varies over time and
space
• Extend existing work on the perception of happiness by
providing a detailed explanation of what are the factors
and life events that make different types of individuals
happy and how these affect the overall structure and
cohesion of society.
• Produce an extensive critical review of existing theories
of happiness.
• Add a geographical dimension to the existing research
on happiness.
Aims (2)
• Build a geographical model of happiness that will be
capable of providing information on the different degrees
of happiness attained by people in different regions and
localities, under alternative scenarios and happiness
definitions.
• Produce an extensive critical review of existing theories
of happiness.
• Examine the factors and life events affecting happiness
during the lifetime of different types of individuals, in
order to build a model capable of predicting the future
trends in happiness and prosperity for different
geographical areas.
• Explore the relationship between what defines happiness
and socio-economic phenomena, such as
unemployment and income inequalities
Aims (3)
• Use a simulation model to estimate the different degrees
of happiness attained by people in different regions and
localities, under alternative scenarios and happiness
definitions.
• Examine the relationship of happiness and capability, on
the basis of past relevant research (such as the work of
Sen, 1993)
• Examine the possible impact of happiness of income and
wealth redistribution
• Investigate the possible impact on happiness of basic
income policies which could increase the economic
independence of all individuals in society (Van Parijs,
1997 and 2001).
• Provide projections of how British society will look in the
next 10 and 20 years, under alternative assumptions.
What is happiness?
• Greece, circa 500 BC
• Socrates, Plato 
Aristotle (384-322 BC)
Nichomachean Ethics (350 BC)
http://classics.mit.edu/Aristotle/nicomachaen.html
England, 18th century
Bentham (1748 – 1832), the principle of Utility
John Stuart Mill (1806 – 1873) – Utilarianism
http://www.utilitarianism.com/
What is happiness? Can it be
measured?
Human perceptions of happiness vary and depend on a
wide range of factors
What is the good life for man? The question of what is a full
and rich life cannot be answered for an individual in
abstraction from the society in which he lives
(Aristotle, Nicomachean Ethics)
Can happiness be measured?
Happiness is subjective and no objective theory about the
ordinary concept of happiness has the slightest plausibility
(Sumner, 1996)
What is happiness? Can it be
measured?
A person who has had a life of misfortune, with very little
opportunities, and rather little hope, may be more easily
reconciled to deprivations than others reared in more
fortunate and affluent circumstances. The metric of
happiness may, therefore, distort the extent of
deprivation in a specific and biased way.
(Sen, 1987: 45)
Can happiness be measured?
Oswald and Clark (2002): statistical regression models of
happiness measuring the impact of different life events
upon human well being
Happiness and economics
• Happiness is defined as utility
• Utility can be measured and compared
across people
• Marginal utility of income is assumed to be
higher for poor people than for rich people
Hicks and Kaldor proposed a measure of
national welfare similar to GDP adjusted
for leisure and pollution
BUT can Happiness be
measured?
Richard Layard (2005), Andrew Owswald (2002)
and others argue that it can!
“By happiness I mean feeling good – enjoying
Life and feeling is wonderful. And by
Unhappiness I mean feeling bad and wishing
things were different” (Layard, 2005)
General happiness Self Completion (4)
Question Number and Text KS1L :
Have you recently....been feeling reasonably happy, all things
considered?
Value Label
%
More so than usual 1
13.2
Same as usual 2
72.8
Less so than usual 3
11.8
Much less than usual 4
2.2
Source: The British Household Panel Survey, 2001
General Health Questionnaire (1)
Have you recently:
• Been able to concentrate on whatever you are
doing?
• Lost much sleep over worry?
• Felt that you are playing a useful part in things?
• Felt capable of making decisions about things?
• Felt constantly under strain?
• Felt you could not overcome your difficulties?
General Health Questionnaire (2)
Have you recently:
• Been able to enjoy your normal day-to-day
activities?
• Been able to face up to your problems?
• Been feeling unhappy or depressed?
• Been losing confidence in yourself?
• Been thinking of yourself as a worthless person?
• Been feeling reasonable happy all things
considered?
Happiness in different
activities (after Layard, 2005)
Happiness in different
activities (after Layard, 2005)
Interacting with:
Friends
Parents/relatives
Spouse
My children
Co-workers
Clients/customers etc
Alone
Boss
Average happiness
3.3
3
2.8
2.7
2.6
2.4
2.2
2
Can happiness be measured?
• Positive and negative feelings
are inversely correlated
• Happiness can be thought of
as a single variable (Layard,
2005)
Happiness and inequality
“A house may be large or small; as long as
the surrounding houses are equally small
it satisfies all social demands for a
dwelling. But if a palace arises beside the
little house, the little house shrinks to a
hovel… [and]… the dweller will feel more
and more uncomfortable, dissatisfied and
cramped within its four walls.”
(Marx and Engels, 1848: 268)
Happiness and inequality
“When we are at home, most of us like to
live in roughly the same style as our
friends or neighbours, or better. If our
friends start giving more elaborate parties,
we feel we should do the same. Likewise if
they have bigger houses or bigger cars.”
(Layard, 2005: 43)
Happiness and inequality
“… similarly at work, I compare my income
with what my colleagues get, in so far as I
hear about it. If they get a raise above
inflation and I get inflation only, I get mad.”
(Layard, 2005: 44)
Happiness and inequality
“Interviewing single mothers on council estates a few years
ago it was striking that most spoke about their
depressing social isolation. They couldn’t afford to keep
up with former friends, because they hadn’t the money to
make even the most minimal gestures required of a
friendship – sending birthday cards or buying rounds of
drinks. As one said at the time; ‘My friends will offer to
buy me a round - but I have to say no, because I can’t
buy the next’. As a consequence, these women’s social
circles had shrunk to their mothers and their lovers,
because these were the only relationships which could
be maintained without the expectation of financial
reciprocity.”
(Russell, 2006: 93)
The “One Percent Is Always The
Same” (OPIATS) rule
“This rule implies that if my income is $100,000 and I give $20,000 of it
to the poor, my well-being falls by a fifth. If I divide my $20,000
equally between ten people with incomes of $10,000 ten people’s
well-being will rise by a fifth. The gains from this gift will thus exceed
the losses by a factor of ten. The utilitarian case for governmental
redistribution almost always reflects this logic: taxing the rich won’t
do them much harm, and helping the poor will do them a lot of good.
If you look at the actual relationship between income and outcomes
like health and happiness the OPIATS rule seldom describes the
relationship perfectly but it comes far closer than the ‘One Dollar is
Always the Same’ rule, which is the only rule under which income
inequality does not affect health or happiness”.
(Jencks, 2002: 57)
Exploring geographies of
happiness
• What is the degree of happiness attained by
different types of individuals in various
localities and regions in Britain? Does
space matter?
• Happiness and inequality and space:
rethinking regional economic policy
• Happiness, prosperity and regional/local GDP
growth
• Is the source of happiness or unhappiness
personal or it has more to do with inequalities
in the distribution of income, wealth, skills and
capability?
• Rivalry and geography – rivalries of place
Exploring geographies of
happiness
“… the broad impression is that social class
stratification establishes itself primarily as a
national social structure, though there are perhaps
also some more local civic hierarchies – for
instance within cities and US states. But it should
go without saying that classes are defined in
relation to each other: one is higher because the
other is lower, and vice versa. The lower class
identity of people in a poor neighbourhood is
inevitably defined in relation to a hierarchy
which includes a knowledge of the existence of
superior classes who may live in other areas
some distance away.”
(Wilkinson and Pickett, 2006: 7, my emphasis)
Links between income inequality and
population health (Wilkinson and
Picket, 2006)
• The proportion of analyses classified as wholly
supportive falls from 83% (of all wholly
supportive or unsupportive) in the international
studies to 73% in the large sub-national areas,
to 45% among the smallest spatial units.
• The spatial scale at which people make their
social comparisons is more likely to be the
nation state (arguably reflecting socio-economic
position) than it is to locality (reflecting position
within neighbourhood).
Geographies of happiness in Britain
Region / Metropolitan Area * GHQ: general happiness Crosstabulation
% within Region / Metropolitan Area
Region /
Metropolitan
Area
Total
Inner London
Outer London
R. of South East
South West
East Anglia
East Midlands
West Midlands
Conurbation
R. of West Midlands
Greater Manchester
Merseyside
R. of North West
South Yorkshire
West Yorkshire
R. of Yorks & Humberside
Tyne & Wear
R. of North
Wales
Scotland
GHQ: general happiness
More than Same as
usual
usual
Less so
14.4%
66.7%
7.7%
10.6%
68.6%
10.2%
11.9%
70.2%
9.1%
11.3%
74.1%
8.0%
10.0%
77.4%
8.5%
10.9%
76.0%
8.3%
Missing
or wild
4.5%
2.8%
2.2%
1.7%
2.1%
2.2%
Proxy
respondent
4.3%
5.7%
5.0%
3.5%
1.3%
1.4%
6.6%
4.6%
11.5%
66.0%
.8%
1.0%
.4%
1.3%
1.0%
2.7%
1.2%
.4%
1.8%
3.9%
1.8%
2.2%
2.2%
2.6%
4.7%
4.0%
1.7%
2.7%
5.5%
3.8%
2.3%
1.5%
2.3%
3.4%
10.7%
11.1%
9.9%
14.5%
11.3%
10.7%
10.1%
14.0%
10.8%
8.8%
10.8%
11.3%
73.7%
75.2%
75.5%
70.7%
71.0%
73.9%
76.5%
72.7%
72.3%
70.9%
74.0%
72.2%
Much less
2.4%
2.1%
1.6%
1.4%
.8%
1.3%
Total
100.0%
100.0%
100.0%
100.0%
100.0%
100.0%
9.9%
1.3%
100.0%
10.7%
7.7%
8.6%
8.1%
13.3%
8.5%
5.5%
6.8%
11.5%
12.6%
9.9%
9.2%
2.0%
2.4%
.9%
1.3%
1.7%
1.4%
1.2%
2.3%
1.5%
2.3%
1.3%
1.6%
100.0%
100.0%
100.0%
100.0%
100.0%
100.0%
100.0%
100.0%
100.0%
100.0%
100.0%
100.0%
Source: The British Household Panel Survey, 2001
Geographies of unhappiness in Britain
REGION BY SOCIAL CLASS[
Rest of Yorks & Humberside
CLASS 1
CLASS 2
CLASS 3
CLASSES 1 - 3
N
3.3
7.1
7.0
5.9
328
Tyne & Wear
10.0
7.1
3.4
7.2
264
East Midlands
5.3
8.1
11.2
7.9
782
Inner London
10.3
5.2
8.8
7.9
418
4.9
9.2
12.3
8.5
454
South West
11.7
6.7
8.9
8.7
930
Greater Manchester
14.5
8.2
4.8
9.3
416
West Midlands Conurbation
10.5
8.9
8.8
9.3
453
East Anglia
10.7
6.5
13.3
9.5
390
Merseyside
17.6
9.2
0.0
9.5
233
West Yorkshire
14.5
7.7
9.6
10.2
364
Rest of South East
10.5
10.8
8.7
10.3
1,875
Outer London
8.9
13.3
6.9
10.7
668
Rest of West Midlands
8.9
11.6
14.9
11.5
506
Rest of North
19.7
10.4
8.5
12.4
400
Wales
11.1
12.9
15.3
13.0
533
South Yorkshire
17.6
11.6
24.2
15.4
293
Great Britain
10.5
9.3
9.7
9.8
10,264
Rest of North West
Spatial distribution of “unhappiness”
Modelling happiness and
well-being
• Regression models
• Multi-level modelling
approaches
• Microsimulation and
Spatial Microsimulation
What is microsimulation?
• A technique aiming at building large
scale data sets
• Modelling at the microscale
• A means of modelling real life events by
simulating the characteristics and
actions of the individual units that make
up the system where the events occur
A microsimulation approach to
happiness research
A person who has had a life of misfortune, with
very little opportunities, and rather little hope,
may be more easily reconciled to deprivations
than others reared in more fortunate and
affluent circumstances. The metric of
happiness may, therefore, distort the extent of
deprivation in a specific and biased way.
(Sen, 1987: 45)
Towards geographical
simulation models of happiness
Census of UK
population:
• fine geographical detail
• Small area data
available only in tabular
format with limited
variables to preserve
confidentiality
• cross-sectional
British Household
Panel Survey:
• sample size: more than
5,000 households
• Annual surveys
(waves) since 1991
• Coarse geography
• Household attrition
An extract from the BHPS
PERSO
N
AHID
PID
AAGE12
SE
X
AJBSTAT
…
AHLLT
AQFVOC
ATENURE
AJLSEG
…
1
100020
9
1000225
1
91
2
4
…
1
1
6
9
…
2
100038
1
1000449
1
28
1
3
…
2
0
7
-8
…
3
100038
1
1000452
1
26
1
3
…
2
0
7
-8
…
4
100066
7
1000785
7
58
2
2
…
2
1
7
-8
…
5
100122
1
1001457
8
54
2
1
…
2
0
2
-8
…
6
100122
1
1001460
8
57
1
2
…
2
1
2
-8
…
7
100141
8
1001681
3
36
1
1
…
2
1
3
-8
…
8
100141
8
1001684
8
32
2
-7
…
2
-7
3
-7
…
9
100141
8
1001687
2
10
1
-8
…
-8
-8
3
-8
…
10
100150
7
1001793
3
49
2
1
…
2
0
2
-8
…
11
100150
7
1001796
8
46
1
2
…
2
0
2
-8
…
12
100150
7
1001799
2
12
2
-8
…
-8
-8
2
-8
…
A simplified version of Census data
Small area table 1
Small area table
(household type)
2 (economic
activity of
household
head)
Small area table 3 (tenure
status)
Area 1
Area 1
Area 1
60 "married couple
households"
80 employed/selfemployed
60 owner occupier
20 "Single-person
households"
10 unemployed
20 Local Authority or Housing
association
20 "Other"
20 other
20 Rented privately
Area 2
Area 2
Area 2
40 "married couple
households"
60 employed/selfemployed
60 owner occupier
20 "Single-person
households"
20 unemployed
20 Local Authority or Housing
association
40 "Other"
20 other
20 Rented privately
Spatial microsimulation
procedures
The construction of a micro-dataset from samples and
surveys
Static What-if simulations, in which the impacts of
alternative policy scenarios on the population are
estimated: for instance if there had been no poll tax in
1991 which communities would have benefited most
and which would have had to have paid more tax in
other forms?
Dynamic modelling, to update a basic micro-dataset and
future-oriented what-if simulations: for instance if the
current government had raised income taxes in 1997
what would the redistributive effects have been between
different socio-economic groups and between central
cities and their suburbs by 2007?
Towards geographical models
of happiness
• adding a geographical dimension to
explore the geography of well-being,
based on the estimated database
through the 1990s and early 2000s
• maps of well-being can be produced for
different types of people (i.e. by age)
• Income and wealth inequalities and
happiness (what does money buy you in
different places?)