Made in Chelsea? The evolution and
transmission of inequality
Andrew Hood
Outline
1. Theoretical framework: how do economists think about
inequality?
2. Measurement: how do economists measure inequality?
3. Evolution: what has happened to inequality?
4. Transmission: what will determine future inequalities?
•
An apology: empirics UK-focused throughout
© Institute for Fiscal Studies
How do economists think about inequality?
• Economic theory approaches inequality from the perspective of a
benevolent social planner maximising social welfare
– Usually assumed to be a function only of the welfare of individuals
• Why might reducing inequality increase social welfare?
1. Usually assumed that the marginal utility of income falls as
income rises (concave utility)
–
This means the most efficient use of income is to give everyone the
same amount (if the aim is to maximise utility)
2. Can choose to incorporate inequality in measure of social welfare
–
© Institute for Fiscal Studies
Care more about giving additional utility to those who are worse off
(Atkinson index)
3 (implicit) assumptions in welfare economics
1. The only inequalities that matter are inequalities in resources
(and hence in individual’s welfare)
–
No room for inequalities in rights, status etc.
2. People with expensive tastes should always be compensated
–
The social planner cares about the distribution of welfare, regardless
of the distribution of wealth required to achieve it
3. Increasing the welfare of an individual always increases social
welfare
–
© Institute for Fiscal Studies
The state of the world can never be improved by making the rich
worse off and leaving the poor unaffected
Inequality and economic policy (in theory)
• 2nd fundamental theorem of welfare economics: the market can
deliver any desired (efficient) allocation of resources given the
right initial conditions (endowments)
– Assuming perfect competition and perfect information
• Theoretical benchmark is that government should only seek to
change initial endowments, not allocation mechanism...
• ..but not possible to redistribute all endowments (eg. skills)
• Policy makers have to manage the disincentive effects of nonlump sum redistributive taxation
– Classic efficiency/equity trade-off
© Institute for Fiscal Studies
Inequality of what?
• Ultimately care about inequality in lifetime utility
– But economists have given up on directly measuring utility
• Usually assumed that people get utility from consumption and
leisure
– But economists don’t usually try to measure leisure
• So best proxy from a theoretical perspective is consumption
– Key determinant of individual welfare
– If individuals can borrow or save, a “snapshot” consumption measure
shouldn’t be too different to a “lifetime” measure
– Return to lifetime/snapshot issue later
© Institute for Fiscal Studies
Consumption inequality vs. income inequality
• Despite theoretical superiority of consumption, majority of work
in economics looks at income inequality
– Growing literature on wealth inequality
• Focus on income inequality is largely pragmatic
– Income data is easier to collect/more reliable than consumption data
– And in practice income and consumption look pretty closely related
• Important to remember the limitations of “snapshot” measures of
income
– Don’t distinguish between permanent and temporary inequalities
– Don’t account for any insurance against income shocks
© Institute for Fiscal Studies
Those with the lowest incomes do not have the
lowest consumption…
£490
Median Expenditure
£420
£350
£280
£210
£140
£70
£0
£0
£100
£200
£300
Income
£400
£500
...nor do they have the highest material
deprivation scores
Deprivation score
30
25
20
15
10
5
0
£0
£50 £100 £150 £200 £250 £300 £350 £400 £450 £500
Weekly BHC income, 2010-11 prices
How do we measure income?
• Income as measured by UK government in “Households Below
Average Income” (HBAI)
• Based on Family Resources Survey (from 1994-5 onwards)
– 25,000 households across the UK
– Subject to sampling error
• Income is measured net of direct taxes and benefits
• Measured at the household level (implicitly assumes income
sharing)
• Adjusted for inflation
© Institute for Fiscal Studies
The UK income distribution in 2012–13
Equivalised household income
(£ per week)
2,500
2,000
1,500
1,000
500
0
10
20
30
40
50
Percentile
© Institute for Fiscal Studies
60
70
80
90
The UK income distribution in 2012–13
Equivalised household income
(£ per week)
2,500
2,000
1,500
50th percentile:
£440pw
1,000
500
0
10
20
30
40
50
Percentile
© Institute for Fiscal Studies
60
70
80
90
The UK income distribution in 2012–13
Equivalised household income
(£ per week)
2,500
2,000
1,500
Childless couple:
£440pw
1,000
Single person:
£295pw
Couple with 2 young
children: £616pw
500
0
10
20
30
40
50
Percentile
© Institute for Fiscal Studies
60
70
80
90
The UK income distribution in 2012–13
Equivalised household income
(£ per week)
2,500
2,000
1,500
50th percentile:
£440pw
1,000
500
0
10
20
30
40
50
Percentile
© Institute for Fiscal Studies
60
70
80
90
The UK income distribution in 2012–13
Equivalised household income
(£ per week)
2,500
2,000
1,500
50th percentile:
£440pw
1,000
10th percentile:
£227pw
500
0
10
20
30
40
50
Percentile
© Institute for Fiscal Studies
60
70
80
90
The UK income distribution in 2012–13
Equivalised household income
(£ per week)
2,500
2,000
90th percentile:
£884pw
1,500
50th percentile:
£440pw
1,000
10th percentile:
£227pw
500
0
10
20
30
40
50
Percentile
© Institute for Fiscal Studies
60
70
80
90
The UK income distribution in 2012–13
Equivalised household income
(£ per week)
2,500
2,000
90th percentile:
£884pw
1,500
50th percentile:
£440pw
1,000
10th percentile:
£227pw
500
0
10
20
30
40
50
Percentile
© Institute for Fiscal Studies
60
70
80
90
How do we measure inequality?
• Key assumption: inequality is a relative concept
– If everyone’s income is doubled, inequality unchanged
1. Look at deviations from same proportional change across the
distribution
© Institute for Fiscal Studies
Income changes by percentile point: 2011-12 to
2012-13
4%
Cumulative income change
2%
0%
-2%
-4%
-6%
-8%
-10%
-12%
5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95
Percentile
© Institute for Fiscal Studies
How do we measure inequality?
• Key assumption: inequality is a relative concept
– If everyone’s income is doubled, inequality unchanged
1. Look at deviations from same proportional change across the
distribution
– Uses all the information, but a picture not a number
2. Compare incomes at different points (parts) of the income
distribution: ratio (share) measures
© Institute for Fiscal Studies
Measuring income inequality: the 90:10 ratio
Equivalised household income
(£ per week)
2,500
2,000
90th percentile:
£884pw
1,500
50th percentile:
£440pw
1,000
10th percentile:
£227pw
500
0
10
20
30
40
50
Percentile
© Institute for Fiscal Studies
60
70
80
90
Measuring income inequality: the 90:10 ratio
Equivalised household income
(£ per week)
2,500
2,000
90th percentile:
£884pw
1,500
1,000
10th percentile:
£227pw
500
0
10
20
30
40
50
Percentile
© Institute for Fiscal Studies
60
70
80
90
Measuring income inequality: the 90:10 ratio
Equivalised household income
(£ per week)
2,500
2,000
90th percentile:
£884pw
1,500
1,000
10th percentile:
£227pw
500
0
10
20
30
40
50
Percentile
© Institute for Fiscal Studies
60
70
80
90
Measuring income inequality: the 90:10 ratio
Equivalised household income
(£ per week)
2,500
2,000
90th percentile:
£884pw
1,500
50th percentile:
£440pw
1,000
10th percentile:
£227pw
500
0
10
20
30
40
50
Percentile
© Institute for Fiscal Studies
60
70
80
90
Measuring income inequality: the top 1% share
10%
20%
bottom 90%
next 9%
top 1%
70%
© Institute for Fiscal Studies
Measuring income inequality: the top 1% share
10%
10%
bottom 90%
next 9%
top 1%
80%
© Institute for Fiscal Studies
How do we measure inequality?
• Key assumption: inequality is a relative concept
– If everyone’s income is doubled, inequality unchanged
1. Look at deviations from same proportional change across the
distribution
– Uses all the information, but a picture not a number
2. Compare incomes at different points (parts) of the income
distribution: ratio (share) measures
– Easy to understand, but throws away lots of information
3. Summary measures of inequality
– Aim to capture the whole distribution in a single number
– Most popular measure is the Gini coefficient
© Institute for Fiscal Studies
Measuring income inequality: the Gini coefficient
100
Perfect equality
Share of total income (%)
90
Gini =
80
70
A
A + B
60
50
A
40
30
20
B
10
0
0
10
20
30
40
50
60
70
80
Percentage of population, ranked by income
90
100
Changes in income inequality: long run trends
• Sharp increase in inequality through the 1980s
– After at least 20 years of relative stability
© Institute for Fiscal Studies
Big rise in inequality through the 1980s
Gini coefficient
0.40
0.35
0.30
© Institute for Fiscal Studies
2012-13
2009–10
2006–07
2003–04
2000–01
1997–98
1994–95
1991
1988
1985
1982
1979
0.25
Unchanged since then across most of distribution...
5
4
3
2
1
90/10 ratio
© Institute for Fiscal Studies
2012-13
2009-10
2006-07
2003-04
2000-01
1997-98
1994-95
1991
1988
1985
1982
1979
1976
1973
1970
1967
1964
1961
0
...but top 1% continued to “race away”
© Institute for Fiscal Studies
2012-13
2009-10
2006-07
2003-04
2000-01
1997-98
1994-95
1991
top 1% share
1985
1982
1979
1976
1973
1970
1967
1964
1961
90/10 ratio
1988
10
9
8
7
6
5
4
3
2
1
0
Changes in income inequality: long run trends
• Sharp increase in inequality through the 1980s
– After at least 20 years of relative stability
• Since then, inequality broadly unchanged across most of the
distribution...
– Not often discussed – why?
• ...but the very top of the distribution has continued to “race away”
– The topic of most public discussion of inequality – why?
© Institute for Fiscal Studies
Why has income inequality risen over the long run?
• Lots of explanations
–
Skills-biased technological changes [see Acemoglu (2002), Machin
(2001) and Goldin and Katz (2008)]
–
Labour market institutions: weaker trade unions and a decline of
collective bargaining (Goodman and Shephard 2002)
–
More inequality in employment status across households (Gregg and
Wadsworth, 2008)
–
Changes in the tax and benefit system
• Requirements for a good explanation
–
Needs to explain similar trends across countries
–
In the UK, needs to explain why top 1% have continued to race away,
but inequality has been flat across rest of the distribution
© Institute for Fiscal Studies
Why has top income inequality continued to rise?
• Q1. Does increase in remuneration reflect higher marginal product?
– Globalisation could have increased the marginal product of the most
high-skilled individuals (Geoff Hurst vs. Wayne Rooney)
– Or those individuals could be extracting much larger rents (breakdown
of social norms)
• Q2. Does higher marginal private product reflect higher marginal
social product?
– Growing share of high-income individuals from the financial sector
– Is the financial sector more valuable in a globalised economy? Or are
employees sharing in abnormal profits?
© Institute for Fiscal Studies
Changes in income inequality: recent years
• Income inequality has fallen across most of the distribution in
recent years
© Institute for Fiscal Studies
Income inequality has fallen in recent years
4%
Cumulative income change
2%
0%
-2%
-4%
-6%
-8%
2007–08 to 2012–13
-10%
-12%
5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95
Percentile
© Institute for Fiscal Studies
Changes in income inequality: recent years
• Income inequality has fallen across most of the distribution in
recent years
– Although lower income households have faced higher inflation
• Real earnings fell sharply but benefit entitlements remained
relatively stable
– 40% of total fall in inequality explained by “catch up” of non-working
households
• Hard to say much about what has happened to the very top
– Underlying trends obscured by temporary responses to tax changes
© Institute for Fiscal Studies
What are the implications for public policy?
• We need to be clear what kind of inequality we’re talking about
– And what kind of inequality we care about
• Inequality broadly flat across the majority of the distribution (with
small fall in recent years)
– Although (given relative concept) this means real incomes have risen
more in cash terms further up the distribution
• Dramatic change has been increasing share of income going to the
top 1%
– Do we care? If so, why?
© Institute for Fiscal Studies
Inter- and intra-generational inequality
• Inequality in the population as a whole combines two kinds of
inequality that we might want to consider separately
1. Intergenerational inequality: inequality between birth cohorts
2. Intra-generational inequality: inequality within birth cohorts
• Intergenerational inequality has achieved greater prominence in
recent years
– Effect of the recession has varied significantly by age
© Institute for Fiscal Studies
Real median income by age group (2007-08=100)
110
105
100
95
90
85
2007–08
2008–09
2009–10
Age 22–30
© Institute for Fiscal Studies
2010–11
2011–12
Age 31–59
2012–13
2013–14
Age 60 and over
2014–15
Real median income by age group (2007-08=100)
110
105
100
95
90
85
2007–08
2008–09
2009–10
2010–11
2011–12
2012–13
2013–14
2014–15
Age 22–30
Age 22–30 (group-specific inflation)
Age 31–59
Age 31–59 (group-specific inflation)
Age 60 and over
Age 60 and over (group-specific inflation)
© Institute for Fiscal Studies
Intergenerational income inequality: big picture
•
Each cohort is usually better off than their predecessors were at
the same age...
–
•
As a result of economic growth
But this is no longer true in the UK and the US
–
© Institute for Fiscal Studies
Very slow income growth for those of working-age in the 2000s,
followed by the Great Recession
Equivalised median household income by age and
birth cohort
800
Real household income
(£ per week, 2011-12 prices)
700
600
500
400
300
200
1940s
1950s
1960s
1970s
100
20
© Institute for Fiscal Studies
25
30
35
40
45
Age
50
55
60
65
70
Intergenerational income inequality: big picture
•
Each cohort is usually better off than their predecessors were at
the same age...
–
•
As a result of economic growth
But this is no longer true in the UK and the US
–
•
Very slow income growth for those of working-age in the 2000s,
followed by the Great Recession
Those born in the 1960s and 1970s did have higher incomes in
early adult life
–
© Institute for Fiscal Studies
But also spent more and (if anything) saved less than predecessors
Intergenerational inequality: beyond income
• Income at a given age not enough to assess the relative position of
different cohorts
•
What we really want to know is how total economic resources
across the lifetime compare for each generation
•
Things other than earnings can matter a lot: 2 (UK-focused)
examples
1.
Home ownership – access to capital gains
2.
Inheritances and gifts
© Institute for Fiscal Studies
Intergenerational inequality: beyond income
1. Homeownership rates at a given age much lower for those born
in the 1970s and 1980s
– Looks unlikely these cohorts will ever achieve the homeownership
rates of their predecessors
© Institute for Fiscal Studies
Homeownership rates by age and birth cohort (1)
Percentage of individuals who own their
home
90%
80%
70%
60%
50%
40%
1940s
1950s
1960s
1970s
30%
25
30
35
40
Age
© Institute for Fiscal Studies
45
50
Homeownership rates by age and birth cohort (2)
Born 1963–67
Born 1973–77
Born 1983–87
Homeownership rate (%)
80%
70%
60%
50%
40%
30%
20%
10%
0%
20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40
Age
Source: Figure 3.13 of Living Standards, Poverty and Inequality: 2014
© Institute for Fiscal Studies
Intergenerational inequality: beyond income
1. Homeownership rates at a given age much lower for those born
in the 1970s and 1980s
– Looks unlikely these cohorts will ever achieve the homeownership
rates of their predecessors
– Smaller proportion access capital gains from housing
© Institute for Fiscal Studies
Real house prices in Great Britain (1968-69 = 100)
450
400
350
300
250
200
150
100
50
© Institute for Fiscal Studies
2011–12
2006–07
2001–02
1996–97
1991–92
1986–87
1981–82
1976–77
1971–72
0
Intergenerational inequality: beyond income
1. Homeownership rates at a given age much lower for those born
in the 1970s and 1980s
– Looks unlikely these cohorts will ever achieve the homeownership
rates of their predecessors
– Smaller proportion access capital gains from housing
2. But more recent cohorts much more likely to inherit
© Institute for Fiscal Studies
Percentage of individuals who have received, or
expect to receive, an inheritance, by birth year
70%
60%
50%
40%
30%
20%
10%
0%
1940–44
1945–49
1950–54
1955–59 1960–64
Year of birth
1965–69
1970–74
Source : Authors’ calculations using wave 1 of the Wealth and Assets Survey
© Institute for Fiscal Studies
1975–79
Intergenerational inequality: beyond income
1. Homeownership rates at a given age much lower for those born
in the 1970s and 1980s
– Looks unlikely these cohorts will ever achieve the homeownership
rates of their predecessors
– Smaller proportion access capital gains from housing
2. But more recent cohorts much more likely to inherit
– 70% of those born in the late ‘70s expect to receive or have received
an inheritance, compared to 28% of those born in the early ‘40s
– Main reason why younger cohorts might expect to have higher
incomes in later life than their predecessors
© Institute for Fiscal Studies
Distribution of size of inheritances received
16%
14%
12%
10%
8%
6%
4%
2%
0%
Total size of inheritance(s) received (2012 prices)
© Institute for Fiscal Studies
What about intra-generational inequality?
• Intra-generational income inequality similar across cohorts
– But younger cohorts have lived more of their working lives post-1980
© Institute for Fiscal Studies
Gini coefficients for equivalised household
income by age and birth cohort
Within-cohort Gini coefficient of household
income
0.45
0.40
0.35
0.30
0.25
1940s
1950s
1960s
1970s
0.20
20
25
30
35
40
45
Age
50
55
60
Source : Authors’ calculations using Family Expenditures Survey, various years
© Institute for Fiscal Studies
65
70
What about intra-generational inequality?
• Intra-generational income inequality similar across cohorts
– But younger cohorts have lived more of their working lives post-1980
• Tentative evidence of increasing inequality in housing wealth
– No decline in the proportion owning their home outright
© Institute for Fiscal Studies
Outright homeownership rates by age and cohort
Percentage of individuals who own their own
home outright
80%
70%
1940s
1950s
1960s
1970s
60%
50%
40%
30%
20%
10%
0%
25
30
35
40
45
50
55
60
Age
© Institute for Fiscal Studies
Source : Authors’ calculations using Family Expenditures Survey and Family
Resources Survey, various years
65
70
What about intra-generational inequality?
• Intra-generational income inequality similar across cohorts
– But younger cohorts have lived more of their working lives post-1980
• Tentative evidence of increasing inequality in housing wealth
– No decline in the proportion owning their home outright
– More generally, bigger minority with no access to (future) capital gains
• (Expected) inheritances very unequally distributed
© Institute for Fiscal Studies
Expected value of future inheritances, by age and
current net household wealth
£0
£1 to £9,999
£10,000 to £99,999
£100,000+
100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
Highest wealth
Mid wealth
Source : Authors’ calculations using wave 1 of the Wealth and Assets Survey
55–59
50–54
45–49
40–44
Lowest wealth
Age group and (within-age-group) wealth tertile
© Institute for Fiscal Studies
35–39
30–34
25–29
55–59
50–54
45–49
40–44
35–39
30–34
25–29
55–59
50–54
45–49
40–44
35–39
30–34
25–29
0%
Expected value of future inheritances among
those in their 30s, by partner’s expectations
£0
£1 to £9,999
£10,000 to £99,999
£100,000+
100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%
£0
£1 to £9,999
£10,000 to
£100,000+
£99,999
Partner's expected future inheritance
Source : Authors’ calculations using wave 1 of the Wealth and Assets Survey
© Institute for Fiscal Studies
No partner
What about intra-generational inequality?
• Intra-generational income inequality similar across cohorts
– But younger cohorts have lived more of their working lives post-1980
• Tentative evidence of increasing inequality in housing wealth
– No decline in the proportion owning their home outright
– More generally, bigger minority with no access to (future) capital gains
• (Expected) inheritances very unequally distributed
– Strong positive correlation with existing wealth
– Strong positive correlation across couples
• Inheritances increase absolute inequality, but impact on relative
inequality is ambiguous
© Institute for Fiscal Studies
A growing inheritance: implications for policy
• Key change: inherited wealth will account for a larger share of
lifetime economic resources for younger cohorts
– Not confined to the UK (Piketty etc.)
• Implication 1: increased inequality of opportunity
– Who my parents are matters more for my lifetime resources
– Usual remedies ineffective – not about earnings inequality
(productivity, access to professions etc.)
• Implication 2: relaxation of the equity/efficiency trade-off?
– Opportunity to shift from income (labour) taxation to lump-sum
(inheritance) taxation
– But creates disincentive to work and save for future givers
© Institute for Fiscal Studies
Conclusions
• 2 big stories in inequality over the last 20/30 years
1. The “racing away” of the very top of the income distribution
2. The shift from income inequality to wealth inequality, particularly the
growing importance of inheritances
• Both present new challenges for public policy
1. Given the Laffer curve, should governments attempt to reduce pre-tax
inequality? Is there rent-seeking behaviour that should be regulated?
2. How should wealth be taxed? Is there political appetite for a more
comprehensive wealth transfer tax?
• Important to bear in mind the limitations of economic analysis
– No room for non-material inequalities, social welfare the (weighted)
sum of individual welfare
© Institute for Fiscal Studies
References

Acemoglu, D. (2002)“Technical Change, Inequality and the Labor Market”, Journal of Economic Literature 40 (1)

Adam, S., and Browne ,J. (2010) “Redistribution, work incentives and thirty years of UK tax and benefit reform”, IFS Working Paper
10/24

Belfield, C., Cribb, J., Hood, A., and Joyce, R. (2014) “Living Standards, Poverty and Inequality in the UK: 2014” IFS Report R96

Brewer, M., and O’Dea, C. (2012) “Measuring Living Standards with income and consumption: Evidence from the UK”, IFS Working
Paper W12/12

Cribb, J., Hood, A., Joyce, R., and Phillips, D. (2013) “Living Standards, Poverty and Inequality in the UK: 2013” IFS Report R81

Cribb, J., Joyce, R., and Phillips, D. (2012) “Living Standards, Poverty and Inequality in the UK: 2012” IFS Report C124

Goldin, C., and Katz, L. (2008) “The Race Between Education and Technology”, Harvard University Press, Cambridge MA

Goodman, A. and Shephard, A. (2002), Inequality and living standards in Great Britain: some facts, IFS Briefing Note 19 , Institute for
Fiscal Studies, London

Gregg , P. and Wadsworth, J. (2008) “Two Sides to Every Story: Measuring Polarization and Inequality in the Distribution of Work”,
Journal of the Royal Statistical Society Series A

Hood, A. and Joyce, R. (2013) “The economic circumstances of cohorts born between the 1940s and 1970s”, IFS Report R89

Machin, S. (2001) “The Changing Nature of Labour Demand in the New Economy and Skill-Biased Technology Change”, Oxford
Bulletin of Economics and Statistics 63 (S1)
© Institute for Fiscal Studies