Transcript OswaldHappinessLecture1

The Economics of
Happiness and Health
Andrew Oswald
IZA and Warwick
I would like to acknowledge that much of this work is joint
with coauthors Chris Boyce, Andrew Clark, Nick Powdthavee,
David G. Blanchflower, and Steve Wu.
This week I’d like to propose
a number of ideas.
#1
‘Happiness’ data offer us
interesting potential as
proxy-utility data.
u = u(y, z, ..)
Regression equations
Mental well-being = f(Age, gender,
education level, income, marital
status, friendship networks,
region, year…)
We now know:
• There is a lot of regularity in these
regression-equation patterns, across
countries and well-being measures.
• Fairly robust to panel estimators and
different methods.
• Progress can be made on causality.
One potentially important
implication:
If this form of function can be estimated
(and K, L, M are life events):
Happiness = a + bK + cL + dM +eY
where Y is income,
If this form of function can be estimated
(and K, L, M are life events):
Happiness = a + bK + cL + dM +eY
where Y is income, then we may be
able to use such equations to calculate
the implied dollar value of the
happiness from life events K, L, M.
Monetary equivalences
A life satisfaction equation:
Life satisfaction = B1*income + B2*Event + error
Marriage - $100,000 (Blanchflower and
Oswald, 2004), Neuroticism - $314,000
(Boyce et al., in press), Widowhood –
($175,000-$496,000), Health limiting daily
activities ($473,000) (Powdthavee, van
den Berg, 2011)
#2
The next 20 years are likely to
see economists work more and
more with physiological and
hard-science data.
#3
Biomarker data will (slowly) be
used more and more in
economics.
#4
Empirically, there are strong
relative effects on utility:
#4
Empirically, there are strong
relative effects on utility:
u = u(y, y*)
eg. if y* is others’ incomes.
#5
A crucial role in social-science
behaviour is played by the
second derivative, v″, of the
function
utility = v(relative status)+ ..
In humans (I shall argue)
• Concavity of v(.) leads to
imitation and herd behaviour
• Convexity of v(.) leads to
deviance.
#6
The Stiglitz Commission’s ideas
will eventually take hold.
Stiglitz Report 2009:
“Measures of .. objective and subjective wellbeing provide key information about people’s
quality of life. Statistical offices [worldwide]
should incorporate questions to capture
people’s life evaluations, hedonic
experiences … in their own survey.” P.16.
Executive Summary of Commission Report.
So........
Could we perhaps learn …
..how to make whole countries
happier?
Preferably not like this…
Germany 4 England 1
Germany 4 England 1
Useful introductions
• “Relative Income, Happiness and
Utility: An Explanation for the Easterlin
Paradox and Other Puzzles” (Andrew
Clark, Paul Frijters and Mike Shields),
Journal of Economic Literature, 2008.
• The Happiness Equation (Nick
Powdthavee), Icon Books, 2010.
This is a good time for general
questions if people would like
to ask some?
Now let’s think about how
human beings report their
feelings (for example, in a
survey).
• First, they have genuine
feelings inside themselves
(about how happy they are,
say).
• Second, they make a decision
about how to report those
feelings.
There are then two processes
going on inside a person.
Human feelings
Human reporting
• Let’s think of the example of
money and people’s well-being.
Assume
Assume
People get true happiness, h,
from income, y. Call it h(y).
Assume
People get true happiness, h,
from income, y. Call it h(y).
They give a number for this,
which is their reported
happiness, r. Call it r(h).
The Reporting Function
The Reporting Function
Write R(y) which is reported
happiness as a function of
income.
This is what is studied in wellbeing regression equations.
Now think of the function-of-afunction rule in calculus.
By definition
R(y) = r(h(y))
By definition
R(y) = r(h(y))
so
Rʹ(y) = rʹ(h) hʹ(y) > 0
where y is income.
In the cross-section, income is positively
correlated with happiness
Take America in 1994 for example
From Deaton-Kahneman in PNAS 2010
Now let’s think of the second
derivative
The first derivative earlier was:
Rʹ(y) = rʹ(h) hʹ(y)
The first derivative earlier was:
Rʹ(y) = rʹ(h) hʹ(y)
where y is income, r is
reported happiness, h is actual
happiness.
Think of the second derivative
The curvature of reported
happiness is
Think of the second derivative
The curvature of reported
happiness is
R″(y) = r″(h) hʹ(y) hʹ(y)
+ rʹ(h) h″(y)
But if R″(y) is found to be
negative that does not prove
that h″(y) is negative.
R is reported happiness
h is true happiness
Hence there are lots and lots of
papers in the literature that get this
wrong.
Reiterating why:
The curvature of reported
happiness is
R″(y) = r″(y) hʹ(y) hʹ(y)
+ rʹ(h) h″(y)
Even if the estimated happiness
function itself is concave, we
cannot be certain that true
happiness is concave.
All social scientists (and many
medical scientists) need to know
more about the reporting function.
• So is there any way to make
progress on this tricky issue?
Height as an example
113 Men and 106 Women
• The respondents were asked to record
how tall they felt, using a continuous
un-numbered line with the words ‘very
short’ written at the left-hand end to
‘very tall’ at the right-hand end.
113 Men and 106 Women
• The respondents were asked to record
how tall they felt, using a continuous
un-numbered line with the words ‘very
short’ written at the left-hand end to
‘very tall’ at the right-hand end.
• Numbers were coded 1…10 afterwards.
• Then we looked at the
correlation between feelings of
being tall and actual true
height.
How well correlated are feelings of
height and actual height?
Feelings of height and actual
height in 113 men
y = -28.966 + 0.19528x R= 0.80909
Subjective assessment of height
from very short to very tall
10
8
6
4
2
0
150
160
170
180
Actual height of men (in cm)
190
200
Feelings of height and actual
height in 106 women
y = -38.202 + 0.26151x R= 0.85423
Subjective assessment of height
from very short to very tall
10
8
6
4
2
0
-2
140
145
150
155
160
165
170
Actual height of women (in cm)
175
180
These plots are consistent with
a linear reporting function.
Much more research on the
reporting function r(.) will be
required in the future.
Evidence from Neuroscience
• Positive feelings correspond to brain
activity in the left-side of the pre-frontal
cortex, above and in front of the ear
• Negative feelings correspond to brain
activity in the same place in the right side
of the brain
Happy and Sad Pictures
The Brain Responses to Two Pictures
(MRI Scan)
Source: Richard Davidson, University of Wisconsin
The types of statistical sources
General Social Survey of the USA
British Household Panel Study (BHPS)
German Socioeconomic Panel
Australian HILDA Panel
Eurobarometer Surveys
Labour Force Survey from the UK
World Values Surveys
NCDS 1958 cohort
BRFSS
From the U.S. General Social Survey
(sample size 40,000 Americans approx.)
• “Taken all together, how would you
say things are these days - would
you say that you are very happy,
pretty happy, or not too happy?”
An alternative DRM approach
• A study by Daniel Kahneman and his
colleagues on 1,000 working women in
Texas (see Kahneman et al, 2003)
• These women were asked to divide the
previous day into 15 episodes. They
were then asked what they were doing
in each episode, and who were they
doing it with.
Happiness in Different Activities
Happiness while Spending Time with
Different People
The average reported feelings across 1,000 people correspond well with
activities predicted to be good for us, as well as activities predicted to be
bad for us
So how has the modern work
on the economics of happiness
proceeded?
Here is a modern US happiness
equation (courtesy of David
Blanchflower, Dartmouth College
and NBER)
• Could you turn to the NBER
Blanchflower-Oswald paper on
international happiness?
Some cheery news:
Some cheery news:
In Western nations, most
people are pretty happy with
their lives.
Some cheery news:
In Western nations, most
people are pretty happy with
their lives.
Some cheery news:
In Western nations, most
people are pretty happy with
their lives.
Some cheery news:
In Western nations, most
people are pretty happy with
their lives.
The distribution of life-satisfaction levels
among British people
35
Percentage of Population
30
25
20
15
10
5
0
1
2
3
4
5
6
Self-rated Life Satisfaction
Source: BHPS, 1997-2003. N = 74,481
7
Exogenous shocks and happiness
New work looks at
Genes
Lottery wins
9-11’s effects
Deaths of children
Sporting results
Movements in air pollution
Other work on happiness as causal
• John Ifcher and Homa Zarghamee,
forthcoming in the AER, on happiness
leading to different rate of time
discount.
• Oswald, Proto, Sgroi on happiness
leading to higher productivity.
These randomly assign happiness.
Is modern society going
in a sensible direction?
This is an empirical question
• "Does Economic Growth Improve the
Human Lot?" Richard Easterlin
in Paul A. David and Melvin W. Reder,
eds., Nations and Households in
Economic Growth: Essays in Honor of
Moses Abramovitz, New York: Academic
Press, Inc., 1974.
• We will focus on it tomorrow.
Let’s return for a moment to the
microeconomics of human
well-being
What have we learned?
Big effects
Unemployment
Divorce
Marriage
Bereavement
Friendship networks
Health
No effects from children [but + for
grandchildren: Nick Powdthavee]
There is also an
intriguing life-cycle
pattern
The pattern of a typical person’s
happiness through life
Average life satisfaction score
5.6
5.5
5.4
5.3
5.2
5.1
5.0
4.9
15-20
21-30
31-40
41-50
Age group
51-60
61-70
Arthur Stone, Angus Deaton, et al (2010)
Overall well-being
Quadratic Life-Satisfaction in the US
Steve Wu on BRFSS 2010 data
age -.0030621
agesq .0000419
Again the U-shape.
A life satisfaction U-shape in age also
exists in many developing nations
In World Values Survey data, there is a Ushape and it reaches its minimum at:
A life satisfaction U-shape in age also
exists in many developing nations
In World Values Survey data, there is a Ushape and it reaches its minimum at:
Brazil 37
China 46
El Salvador 48
Mexico 41
Nigeria 42
Tanzania 46
Obviously life is a mixture of ups
and downs
Much of the recent research
follows people through time.
eg. Andrew Clark’s work
The unhappiness from
bereavement
Human beings also bounce
back from, say, disability.
Work with N. Powdthavee, Journal of Public
Economics, 2008
Life-Satisfaction Path of Those Who Entered Disability
at Time T and Remained Disabled in T+1 and T+2
BHPS data 1996-2005
6.5
6.0
Mean Life Satisfaction
5.5
5.0
4.5
4.0
3.5
3.0
2.5
2.0
T-2
T-1
T
T+1
T+2
However, there is a downside to
that adaptability (eg. marriage)
However, there is a downside to
that adaptability (eg. marriage)
Is there income adaptation?
Maybe.
The joy of having higher income may
also wear off …
Source: Di Tella et al (2008), German Socio-Economic Panel
And should you invest in a
baby?
Happiness and children
But people do not seem to adapt to
joblessness
The evidence suggests that when a
person is made unemployed:
The evidence suggests that when a
person is made unemployed:
• 20% of the fall in mental well-being
is due to the decline in income
• 80% is due to non-pecuniary things
(loss of self-esteem, status..).
An important question in a
modern society is the
impact of divorce.
Divorce (eventually) makes
people happier
Divorce (eventually) makes
people happier
Points or questions?
What about money and
happiness?
A key social-science fact
A key social-science fact
The data show that richer
people are happier and
healthier.
But some general economists
have low life-satisfaction when
they hear about this research.
The tradition of economics has
been to ignore what people say
about the quality of their own
lives.
The tradition of economics has
been to ignore what people say
about the quality of their own
lives.
Many are opposed to the idea
of measuring ‘happiness’.
I always liked the retort:
I always liked the retort:
If molecules could talk, would
physicists refuse to listen?
A. Blinder
I always liked the retort:
If molecules could talk, would
physicists refuse to listen?
A. Blinder
So how could we move forward?
So how could we move forward?
• Brain-science correlates as a
validation
So how could we move forward?
• Brain-science correlates as a
validation
• Physiological correlates as a
validation
A brain-science approach (Urry et al
Psychological Science 2004)
But, for a sceptic, there is a
major difficulty.
Biological data only validate
well-being scores in so far as
they are unambiguously
measures of utility or
‘happiness’.
A killer question
• Can we devise a test in the
economist’s spirit that shows,
once and for all, a match
between subjective well-being
data and objective well-being
data?
Yes.
I would like to give you the flavour
of the argument in Oswald-Wu in
Science in 2010.
Are objective and subjective data on
quality-of-life correlated?
13
4
We can exploit neo-classical
economic theory to assess the
validity of well-being data.
Think not about people but
about places.
Joint work with Steve Wu
• New data from the Behavioral Risk
Factor Surveillance System
(BRFSS)
• 1.3 million randomly sampled
Americans
• 2005 to 2008
• A life-satisfaction equation
Then we go to the compensatingdifferentials literature dating back
to Adam Smith, Sherwin Rosen,
Jennifer Roback, etc.
The most recent is Gabriel et al
2003.
Gabriel painstakingly takes data on
•
•
•
•
•
•
•
•
•
•
•
•
Precipitation
Humidity
Heating Degree Days
Cooling Degree Days
Wind Speed
Sunshine
Coast
Inland Water
Federal Land
Visitors to National Parks
Visitors to State Parks
Number of hazardous waste sites
and
•
•
•
•
•
•
•
Environmental Regulation Leniency
Commuting Time
Violent Crime Rate
Air Quality-Ozone
Air Quality-Carbon Monoxide
Student-teacher ratio
State and local taxes on property, income and sales
and other
• State and local expenditures on higher education,
public welfare, highways, and corrections
• Cost-of-living
Then there are 2 ways to
measure human well-being or
‘utility’ across space.
Subjective and objective
Gabriel’s work assigns a 1 to
the state with the highest
imputed quality-of-life, and 50
to the state with the lowest.
So we need to uncover a
negative association – in
order to find a match.
• And there is one.
One Million Americans’ Life Satisfaction
and Objective Quality-of-Life in 50 States
y = -0.0032082 - 0.0012154x R= 0.60938
Life Satisfaction Fully Adjusted (ie income also)
0.04
0.02
0
-0.02
-0.04
-0.06
-0.08
-0.1
0
10
20
30
40
50
Objective Quality of Life Ranking (where 1 is high and 50 is low)
60
To conclude across US states:
There is a match between lifesatisfaction scores and the quality
of life calculated using (only) nonsubjective data.
Some ideas to end:
My hunch
My hunch
The methods of the economics
of happiness and mental wellbeing will slowly enter public
life.
Other important applications
Other important applications
The valuation of environmental
amenities
Other important applications
The valuation of environmental
amenities
The valuation of health states
Other important applications
The valuation of environmental
amenities
The valuation of health states
The valuation of emotional
damages for the courts.
Conventionally:
• Economics is a social science
concerned with the efficient
allocation of scarce resources
We owe this definition to Lionel
Robbins of the London School
of Economics.
For a long time, it served us
well.
But perhaps the time has come
to think differently – and to
define economics differently.
An alternative definition:
An alternative definition for 2011:
• Economics is a social science
concerned with the best way to
allocate plentiful resources to
maximize a society’s well-being
and mental health.
Looking ahead
Policy in the coming century
may need to concentrate on
non-materialistic goals.
Looking ahead
Policy in the coming century
may need to concentrate on
non-materialistic goals.
GNH not GDP.
And the next research area?
Thank you.
The Economics of Happiness
and Health
Andrew Oswald
Research site: www.andrewoswald.com
I would like to acknowledge that much of this work is joint
with coauthors Chris Boyce, Andrew Clark, Nick Powdthavee,
David G. Blanchflower, and Steve Wu.