the economics of happiness and health andrew oswald iza and warwick i would like to acknowledge that...
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The Economics of Happiness and Health
Andrew OswaldIZA 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 well-
being 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 …
Preferably not like this…
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 well-being regression equations.
Now think of the function-of-a-function 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 exampleTake 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
0
2
4
6
8
10
150 160 170 180 190 200
y = -28.966 + 0.19528x R= 0.80909 S
ubje
ctiv
e as
sess
men
t of
hei
ght
from
ver
y sh
ort
to v
ery
tall
Actual height of men (in cm)
Feelings of height and actual height in 106 women
-2
0
2
4
6
8
10
140 145 150 155 160 165 170 175 180
y = -38.202 + 0.26151x R= 0.85423 S
ubje
ctiv
e as
sess
men
t of
hei
ght
from
ver
y sh
ort
to v
ery
tall
Actual height of women (in cm)
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 USABritish Household Panel Study (BHPS)German Socioeconomic PanelAustralian HILDA PanelEurobarometer SurveysLabour Force Survey from the UKWorld Values SurveysNCDS 1958 cohortBRFSS
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
0
5
10
15
20
25
30
35
Per
cen
tag
e o
f P
op
ula
tio
n
1 2 3 4 5 6 7
Self-rated Life Satisfaction
Source: BHPS, 1997-2003. N = 74,481
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
HealthNo 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
4.9
5.0
5.1
5.2
5.3
5.4
5.5
5.6
15-20 21-30 31-40 41-50 51-60 61-70Age group
Ave
rag
e li
fe s
atis
fact
ion
sco
re
Arthur Stone, Angus Deaton, et al (2010)
Overall well-being
Quadratic Life-Satisfaction in the US
Steve Wu on BRFSS 2010 data
age -.0030621agesq .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 U-shape 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 U-shape 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
2.0
2.5
3.0
3.5
4.0
4.5
5.0
5.5
6.0
6.5
T-2 T-1 T T+1 T+2
Me
an
Lif
e S
ati
sfa
cti
on
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.
134
Are objective and subjective data on quality-of-life correlated?
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 compensating-differentials 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
-0.1
-0.08
-0.06
-0.04
-0.02
0
0.02
0.04
0 10 20 30 40 50 60
y = -0.0032082 - 0.0012154x R= 0.60938 Li
fe S
atis
fact
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Fully
Adj
uste
d (ie
inco
me
also
)
Objective Quality of Life Ranking (where 1 is high and 50 is low)
To conclude across US states:
There is a match between life-satisfaction scores and the quality of life calculated using (only) non-subjective data.
Some ideas to end:
My hunch
My hunch
The methods of the economics of happiness and mental well-being 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.