An Introduction to the Behavioural Economics of

Happiness and Health

Andrew OswaldUniversity of Warwick

I would like to acknowledge that much of this work is joint

with coauthors Chris Boyce, Andrew Clark, Nick Powdthavee,

David G. Blanchflower, Eugenio Proto, and Steve Wu.

Why should we care about happiness and health?

Reason 1

Reason 1

We need to know if society is

going in a sensible direction.

Yet in 1934

Yet in 1934

• “...the welfare of a nation [can]

scarcely be inferred from a

measure of national income...”

Hug a tree today

Prof. Simon Kuznets

• The originator of the concept of GDP

• “...the welfare of a nation [can]

scarcely be inferred from a

measure of national income...”

S Kuznets

So even Simon Kuznets knew

that we require a different

yardstick.

Reason 2

Reason 2

Human beings have feelings.

Reason 2

Human beings have feelings.

Humans have feelings, and

feelings matter.

How do I know researchers

care about feelings of well-

being?

Say we do an electronic search.

Since 2008, approximately

110,000 articles have been

published in economics

journals.

The most-cited major article

in modern economics:

The most-cited major article

in modern economics:

Relative income, happiness, and utility:

An explanation for the Easterlin

paradox and other puzzles

Clark, Andrew E.; Frijters, Paul; Shields,

Michael A.

JOURNAL OF ECONOMIC LITERATURE

MAR 2008

In these lectures I want 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 …

..how to make whole countries

happier?

Though this would be my

favourite way…

England win world cup 2018!!

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 great time for general

questions if people would like

to ask any?

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 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?

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

ub

ject

ive

ass

ess

men

t of

heig

ht

fro

m v

ery

sh

ort

to v

ery

ta

ll

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

ub

ject

ive

ass

ess

men

t of

heig

ht

fro

m v

ery

sh

ort

to v

ery

ta

ll

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 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 table 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.

The distribution of life-satisfaction levels

among British people

0

5

10

15

20

25

30

35

Perc

en

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

Exogenous shocks and happiness

New work looks at

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, 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, in detail,

later.

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

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 61-70

Age group

Avera

ge l

ife s

ati

sfa

cti

on

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 -.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 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+2BHPS 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 mayalso 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

I wonder if anyone would like to

raise 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)

Andrew Steptoe’s work

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.

16

0

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

Life

Sa

tisfa

ctio

n F

ully A

dju

ste

d (

ie in

co

me

als

o)

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 (e.g. Levinson Journal of Public Economics 2011)

Other important applications

The valuation of environmental

amenities (e.g. Levinson Journal of Public Economics 2011)

The valuation of health states

Other important applications

The valuation of environmental

amenities (e.g. Levinson Journal of Public Economics 2011)

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?

An Introduction to the Behavioural 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.