Presentation by: Martine Durand (OECD Chief Statistician and Director of Statistics and Data) OECD Conference on wealth inequalities: Measurement and policies Paris, 26 April 2018.

1. INEQUALITIES IN
HOUSEHOLD WEALTH
ACROSS OECD COUNTRIES
Evidence from the OECD Wealth Distribution Database
Martine Durand
OECD Chief Statistician and Director of Statistics
and Data
COPE event on Wealth Inequalities
Measurement and Policies
OECD, 26 April 2018

2. ADVANCES IN
MICRO STATISTICS ON
HOUSEHOLD WEALTH

3. • Measurement Framework
– OECD Guidelines for Micro Statistics on
Household Wealth first published in 2013
• Draws extensively on SNA
• But focus on household perspective rather than
economy at sector level/as a whole
• Leads to differences in concepts of interest
• Guidelines also highlight best practice in approach to
measurement
• Emerging area for research
– International data sources include:
– Luxembourg Wealth Study (2007, 13 OECD countries)
– Credit Suisse Global Wealth Databook
– Eurosystem Household Finance and Consumption
Survey (HFCS, 18 OECD countries)
– World Inequality Database (3 OECD countries)
Significant advances in micro
statistics on wealth in recent years

4. • Launched in 2015, to provide comparable statistics on
the distribution of wealth across the OECD
– Recently expanded to cover 28 OECD countries
– Estimates obtained from national contact points in National
Statistical Offices/ Central Banks, as well as from Euro-
system HFCS
– Concepts used are in line with OECD Guidelines for Micro
Statistics on Household Wealth
OECD Wealth Distribution Database

5. Non-financial assets
Principal residence
Other real estate property
Vehicles
Valuables
Other consumer durables and other non-financial assets
Financial assets
Currency & deposits
Bonds & other debt securities
Mutual funds & other investment funds
Net equity in own unincorporated enterprises
Stocks
Unlisted shares & other equity
Other non-pension financial assets
Voluntary individual life insurance & private pension
funds (exc. employment related funds)
Liabilities
Principle residence loans
Other residence & real estate loans
Other loans
Components of net wealth included in
OECD Wealth Distribution Database
• Pension schemes related to employment are recorded separately & not currently included in main
net wealth measure due to limited data availability in many countries

6. • Analysis unit: Basic unit of analysis is the household
– consistent with international standards for household income and
consumption
• Household sub-groups: Estimates can be broken down by:
– housing tenure, age, household size, education level, main source of
income, as well as by income/wealth quintile (plus top 10%, 5% & 1%
shares)
• Variables collected: In addition to main net wealth variables :
– share of households holding various types of assets and liabilities
– Mean/median value of assets and liabilities for households holding them
– joint distribution of wealth and income across household quintiles
– the extent of over-indebtedness across households
– share of individuals with liquid financial assets or net wealth below a given
threshold (e.g. 25 or 50% of the income poverty line)
– Receipt of inheritances/gifts and values receive
OECD Wealth Distribution Database

7. THE DISTRIBUTION OF
WEALTH ACROSS OECD
COUNTRIES

8.  Large differences in ranking of countries depending on
whether focus is on mean or median
There are big differences in household
wealth levels across OECD countries
Mean and median net wealth per household
2014 or latest available year, values in 2011 USD
Source: OECD Wealth Distribution Database (Balestra & Tonkin, 2018, forthcoming).
0
100000
200000
300000
400000
500000
600000
700000
800000
Mean net wealth (↗) Median net wealth

9.  A similar pattern of wealth inequality when considering the
share of net wealth held by the richest 10% of households
Similarly, wealth inequality also varies
considerably across the OECD
Ratio of mean to median net wealth
2014 or latest available year
Source: OECD Wealth Distribution Database.
0
1
2
3
4
5
6
7
8
9
SVK
BEL
ITA
GRC
JPN
POL
AUS
SVN
ESP
KOR
LUX
FIN
HUN
NOR
FRA IRL
NZL
PRT
CAN
EST
GBR
CHL
OECD
28
LVA
AUT
DEU
DNK
NLD
USA

10.  All 3 sources tell the same broad story for top wealth shares in France,
United Kingdom & United States
 WDD and Credit Suisse estimates for mean wealth broadly comparable
in most countries, though larger differences in some
How do WDD wealth inequality estimates
compare with other international databases?
Top wealth shares across different international databases
Concentration of wealth at the top of the distribution, percentages
Top 10% Top 1%
Source: Credit Suisse Global Wealth Databook; World Wealth & Income Database; and OECD Wealth Distribution
Database (Balestra & Tonkin, 2018, forthcoming).
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
France United Kingdom United States France United Kingdom United States
OECD WDD WID.world Credit Suisse

11. WHAT TYPE OF ISSUES
CAN THE OECD WDD HELP
ADDRESS?

12. How does the composition of net wealth
vary for different groups?
• Data on composition of wealth for different groups important for tax policy
• Can also be used to assess adequacy of savings (particularly for retirement)
and possible risk due to financial shocks
Composition of net wealth for poorest 20% of households
2014 or latest available year
-250 000
-200 000
-150 000
-100 000
-50 000
0
50 000
100 000
150 000
200 000
Financial wealth Real-estate wealth Other non-financial wealth Property liabilities Other liabilities Net wealth (↗)
Source: OECD Wealth Distribution Database
In some countries, households in the bottom net wealth quintile
have relatively substantial assets, but also high levels of debt.

13.  Over-indebtedness
– For many households, debt can have positive impact on economic
well-being
– Important to identify those situations where debt levels & demands of
meeting payments likely to have negative impact now or in future
– High levels of over-indebtedness in an economy is an issue not just for
individual households but also one of macroeconomic stability
• High debt relative to income
– Increases risks if rising interest rates or a sudden fall in income
– WDD indicator: Debt-to-income ratio > 3
• High debt relative to assets
– Greater exposure to impacts of falling asset prices: e.g. negative equity in real
estate may make it harder to move or remortgage at a competitive rate
– WDD indicator: Debt-to-asset ratio >75%
What share of households are
potentially over-indebted?

14. Share of over-indebted households
Percentage of over-indebted households
2014 or latest available year
 Share of households with high debt-to-income ratio varies largely
across countries, ranging from 32% in the Netherlands to 4% in
Poland.
Source: OECD Wealth Distribution Database
0%
5%
10%
15%
20%
25%
30%
35%
40%
Debt to income ratio > 3 (↗) Debt to asset ratio > 75%

15. Which groups felt the impact of the
Great Recession most strongly?
 Between 2006 & 2011, mean household wealth fell considerably for
younger households in United States, Italy, United Kingdom, Australia
 Since 2011, increase in mean wealth for under 35s very modest in
United Kingdom, United States & Australia, compared with growth for
over 65s.
-14%
-12%
-10%
-8%
-6%
-4%
-2%
0%
2%
4%
6%
8%
USA GBR AUS ITA CAN
Under 35 65 or above (↗)
-8%
-6%
-4%
-2%
0%
2%
4%
6%
8%
USA GBR AUS ITA CAN
Under 35 65 or above
Change in real mean household wealth by age of household reference person
Annual % change 2006-2011 Annual % change 2011-2015
Source: OECD Wealth Distribution Database.

16. • Understanding intergenerational wealth transfers important for
effective policy on equality of opportunity and social mobility
How does wealth get passed on
between generations?
0%
10%
20%
30%
40%
50%
60%
PRT ESP GRC SVK IRL EST FIN SVN OECD
18
FRA POL BEL HUN LVA ITA AUT DEU CAN LUX
Income: bottom quintile Income: top quintile
Source: OECD Wealth Distribution Database (Balestra & Tonkin, 2018, forthcoming).
Proportion of households receiving inheritances & gifts for bottom and top income quintiles
Average value received in 2011 USD
 In all countries, households with higher incomes are more likely to
have received inheritance or gift, but extent varies considerably

17. What is the value of inheritances
received by income quintile ?
0
50 000
100 000
150 000
200 000
250 000
300 000
350 000
BEL FRA GRC IRL SVN HUN SVK PRT ITA OECD
16
ESP EST LUX CAN DEU AUT LVA
Income: bottom quintile Income: top quintile
Average amount received in inheritances & gifts for bottom and top income quintiles
Average value received in 2011 USD
Source: OECD Wealth Distribution Database (Balestra & Tonkin, 2018, forthcoming)
 Among households receiving a gift or bequest, value is
considerably higher for those in top income quintile
– Implies strong link between households’ current income and wealth of
parents/relatives
 Relative to mean net wealth, inheritances average amount
received is larger for those in the bottom quintile in almost all
countries

18. How many individuals are potentially
vulnerable to a sudden fall in income?
0%
10%
20%
30%
40%
50%
60%
70%
Income & asset poor Income poor only Economically vulnerable (↗)
Source: OECD Wealth Distribution Database.
 Income poor are those with equivalised income less than 50% of national
median
 Asset-based poor are those with liquid financial wealth insufficient to
support them at income poverty line for 3 months
 On average, 14% of people in OECD countries are income poor, but a further
36% are economically vulnerable due to the limited assets they hold.
Percentage of individuals experiencing income and/or asset based poverty
2014 or latest available year

19. CONCLUSIONS

20. • WDD data can be used to inform policy in range of
areas including macro prudential, tax and
competition, social mobility and political inequalities
• Analysis in this presentation & background paper
would not have been possible a few years ago
• WDD complements well other sources of information
such as the World Inequality Database/Report and
the Credit Suisse Global Wealth Databook/Report
– Key messages provided by different sources consistent, and
strengthened by different approaches leading to same conclusions
– Where differences exist, important statisticians/researchers work
together to understand them and explain to users
OECD WDD is an important source of
information on wealth inequality

21.  Important challenges ahead:
– Improving coverage of some assets: consumer durables;
pension wealth; business assets
– Better measuring the top of the distribution: Learning
from best practice in official statistics and other research
– Strengthening the comparability of information:
Ensuring better alignment to international guidance and
addressing differences in practices in measuring specific items:
e.g. housing wealth
– Better understanding the differences between micro
statistics and National Accounts, reconciling where
appropriate
– Moving beyond study of household wealth on its own:
relationship with income & consumption; distribution within
households
Despite considerable progress of
recent years, more to be done

22. THANK YOU !
martine.durand@oecd.org

23. EXTRA SLIDES

24.  Many surveys used for OECD WDD oversample wealthy households.
 Wealthiest 10% of households make up 33% of sample in Spain and
25% in United States.
 No statistically significant correlation between degree of
oversampling and wealth share of top 10%
Do top wealth shares reflect degree
of oversampling in surveys?
AUS
AUT
BEL
CHL DEU
ESP
EST
FIN
FRA
GBR
GRC
HUN
IRL
ITAJPN
LUX
LVA
NZL
POL
PRT
SVK
SVN
USA
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
0% 5% 10% 15% 20% 25% 30% 35% 40%
Shareofwealthownedbytop10%
Achieved sampling rate on top 10%
Top wealth shares and degree of oversampling
2014 or latest available year
Source: OECD Wealth Distribution Database (Balestra & Tonkin, 2018).

25. • Differences between micro and macro wealth measures potentially reflect a
range of factors:
– Differences in wealth concepts due
– Population coverage
– Inclusion of NPISH in household balance sheets
– Measurement error in both sources
How do WDD wealth estimates
compare with National Accounts?
0
20000
40000
60000
80000
100000
120000
140000
160000
180000
200000
KOR NZL GBR FRA CAN JPN
National Accounts (↗) OECD Wealth Distribution Database
Net wealth per person in microdata and National Accounts
2014 or latest available year, values in 2011 USD
Source: OECD National Accounts Database and Wealth Distribution Database (Balestra & Tonkin, 2018).