Presentation at the HLEG thematic workshop on Measuring Inequalities of Income and Wealth, 15-16 September 2015, Berlin, Germany, http://oe.cd/hleg-workshop-inequalities-income-and-wealth

1. OECD GUIDELINES FOR
MICRO-STATISTICS ON
HOUSEHOLD WEALTH
(and evidence from OECD
wealth distribution database)
Marco Mira d’Ercole, OECD Statistics Directorate
High Level Expert Group on the Measurement
of Economic Performance and Social Progress
Workshop on Measuring Inequalities in Income and Wealth
Berlin, 15-16 September 2015

2. • Current state of household wealth statistics is similar to that of
income distribution 20 or 30 years ago
– No statistical standards exists
– Only half OECD countries have regular data collections in this field
• But it is an emerging area for research with new data initiatives
– Launch of Luxembourg Wealth Study, 5 OECD countries covered
in 2007 (OECD analysis in Growing Unequal? 2008), 11 today
– In 2010, Credit Suisse Global Wealth Database combing micro-
macro statistics and a variety of imputation methods, building on
efforts at UN University World Institute for Development
Economics Research (UNU-WIDER A. Shorrocks and J. Davies)
– In 2012, release of first results from the Eurosystem Household
Finance and Consumption Survey, covering 13 OECD countries
– In 2015, planned release of the Top Income and Wealth Database
by. F. Alvaredo, T. Atkinson, T. Piketty and E. Saez 2
Wealth distribution: current state

3. • Two main deliverables: 1) OECD methodological
guidelines; 2) OECD Wealth Database
• Motivation: SSF recommendations (2009)
– “emphasis the household perspective”
– “give more prominence to distribution of income, consumption
and wealth”
– “consider income and consumption jointly with wealth”
• OECD Response: creation in 2010 of OECD Expert
Group on Micro Statistics on Household Income,
Consumption and Wealth, led by Australia NSOs, with
participation of NSOs and agencies with experience in
field (Bank of Italy, Federal Reserve Board)
3
OECD initiatives in the field of statistics
on the distribution of household wealth

4. • Two main deliverables released in March 2013
– OECD Guidelines for Micro Statistics on Household Wealth
– OECD Framework for Statistics on the Distribution of
Household Income, Consumption and Wealth
• OECD guidelines are not ‘statistical standards’
(which require approval by UN Statistical
Commission) but carry some ‘institutional weight’
(they were discussed an approved by OECD
Committee on Statistics and Statistical Policy)
4
OECD methodological guidelines

5. • Guidelines build on detailed inventory of current measurement
initiatives in OECD counties
• They provide recommendations on:
1. Scope of measurement
2. Unit of measurement
3. Unit of analysis
4. Measurement framework
5. Principles of recording
6. Classification of assets and liabilities
7. Best practice for analysis and measurement
5
OECD Guidelines for Micro Statistics on
Household Wealth

6. 1. Scope of measurement
• Wealth as dimension of people’s material well-being
(with income and consumption)
– Ownership rather than ‘control’; assets as ‘store of wealth’
rather than productive use of assets in economic production
– Excludes assets such as human capital, social capital,
collectively held assets that are not material assets over
which people exercise ownership rights
– Moot point: ‘pension wealth’. Guidelines recommend:
• Including people’s claims on pension schemes (DB &DC, compulsory &voluntary,
private &public) provided that entitlements have separate accounting information
• Excluding entitlements on social security pensions (for practical reasons and to
maintain consistency with SNA). Large impacts on measures of household net
worth and wealth inequality. Practice may evolve. 6
OECD Guidelines for Micro Statistics on
Household Wealth

7. 7
Illustration of the (possible) importance
of pension wealth
Market and pension wealth to income ratios in the early 1990s, families with a head
around 55-years of age (OECD, 1998)

8. 2. Measurement unit: household
• Household definition controversial
– Most NSOs use the same definition of households to measure
wealth or I/C (i.e. people living together and sharing resources)
– Eurofund HFCS adds additional criterion of ‘financial
interdependence’ (important for borderline cases, e.g. students
living away from parental home most of the year)
• Guidelines practical recommendation to use same
definition as in Canberra Handbook
– People resident in country and living in housing units
– Private households, excluding those in collective living
quarter, no permanent address, non-profit institutions
serving households, unincorporated enterprises
8
OECD Guidelines for Micro Statistics on
Household Wealth

9. 3. Unit of analysis
• Measurement unit is not the same as unit of analysis
(e.g. for household income statistics the measurement
unit is household, the unit of analysis in individual)
• In the case of wealth:
– household composition when assets are owned will differ
from the one that will prevail when assets are disposed of
– No agreement of how to adjust households wealth to reflect
differences in needs
 OECD recommendation that unit of analysis be the household
rather than the individual or the consumption unit
 Recommendations on how to select the household reference
person, and common criteria for household’s breakdown 9
OECD Guidelines for Micro Statistics on
Household Wealth

10. 4. Measurement framework
– Similar to SNA (opening and closing stocks linked by various ‘accumulation
accounts’ (capital/ financial/ other changes in volumes/ revaluation accounts)
– In OECD Guidelines, changes in stocks reflect savings, holding gains/ losses,
inheritances/ intra vivos transfers (no guidance on how to measures these flows)
– Specific focus on ‘distribution’ rather than being limited to ‘composition’’
10
OECD Guidelines for Micro Statistics on
Household Wealth

11. 5. Principles of recording
– Market prices or closest equivalent on date of collection
– Recorded at the same point in time for all households
– Recorded gross, i.e. separate measurement of assets and
liabilities (except those between members of same
household)
11
OECD Guidelines for Micro Statistics on
Household Wealth

12. 6. Classification of assets and liabilities
– Follows closely SNA classification (non-financial assets,
financial assets, liabilities)
– Departs from it in some cases to better support
distributional analysis:
• includes aggregate ‘net equity in own unincorporated business’
among financial assets (alongside ‘shares in corporations’), rather
than detailing the various assets and liabilities and classifying
these according to their nature 9as done in SNA)
• includes consumer durables among assets (while they are excluded in
SNA), as they are often the only assets of those at the bottom of
the distribution 12
OECD Guidelines for Micro Statistics on
Household Wealth

13. 13
The importance of consumer durables for
household wealth
0.0
0.2
0.4
0.6
0.8
1.0
NOR NLD SVK FIN KOR DEU ESP USA AUT PRT AUS BEL LUX ITA GRC CAN GBR
All
Q1
Share of consumer durables among total assets, all
households and households in the bottom wealth quintile

14. 7. Best practice for analysis and measurement
• Data presentations, i.e. tabulations, frequency distribution,
cumulative distribution functions
• Choice of summary inequality indices, i.e. Gini (may be >1 when
wealth values are negative), rate ratios, effects of including/
excluding zero and negative values on summary measures
• Adjusting for prices differences across time and countries
• Best practice for measuring individual items
– Real estate (e.g. in some countries self-reported market valuation by households, in others
households are asked for purchase year and price which are then adjusted with information on
changes in dwelling prices in the local market)
– Durables (e.g. self-reports, prices on second-hand market for vehicles, replacement-costs with
discounting for depreciation for other consumer durables)
– Financial assets (e.g. pension entitlements are not traded, valuation requires estimating present
value of expected cash flows)
– Liabilities (e.g. assuming that the principal is paid off evenly over period of the loan, or
estimating the present value of the loan repayments still due)
14
OECD Guidelines for Micro Statistics on
Household Wealth

15. Released on 15 June 2015
• Covering 18 countries in most recent year, more than data-
point for 6 countries
• OECD estimates for 11 HFCS countries, data provided by
national contact points based on OECD specifications for 7
• Sourced from tax records for 2 countries (NL, NO), household
surveys for the others (dedicated wealth surveys in some cases,
US-SCF; special modules of income surveys in others, AL-SIH) :
15
OECD Wealth Distribution database

16. • Consistent classification of assets/ liabilities across countries
– Most analysis based on narrow definition of household wealth (excluding
employment related pensions)
• Households as units of analysis broken down by:
– Housing status (3 groups)
– Age of the household reference person (6)
– Education of the household reference person (4)
– Number of household members (5)
– Household type (6)
– Main income source (5)
– Wealth and income quintiles (with additional information on top 1 and 5%)
 OECD Statistical Brief (http://www.oecd.org/social/household-
wealth-inequality-across-OECD-countries-OECDSB21.pdf )
 Main results in Ch. 6 of “In It Together” (Murtin et al.) 16
OECD Wealth Distribution database

17. 17
Highlights: levels
Mean wealth-to-income ratio ranges between 3 and 9, avg. ~6;
median W/Y between 7 and 1, avg. ~4

18. Highlights: distribution (very unequal)
18
Wealth share of top 10% above 50% on avg., ranging between >
70% of total in the US and around 40% in GRC and SVK

19. Highlights: .. and much more
concentrated then income
19
On average, the Palma ratio (richest 10% to poorest 40%) is 1.1
for household disposable income (equivalised, across people),
and 14.8 for wealth (non-equivalised, across households)

20. Highlights: joint distribution of income
and wealth..
20
High correlation between income and wealth for individual
households, but with exceptions (e.g. low income, high wealth
households) and with large differences across countries

21. 21
.. more than 1/3 of households in the bottom 20%
of wealth are in the upper 60% of income..
Source: OECD wealth database
Bottom wealth quintile
Households in the bottom and top wealth quintiles across income quintiles
Average of 17 OECD countries, early 2010s, percentages
Top wealth quintile
0.00
0.20
0.40
0.60
0.80
1.00
0.00
0.20
0.40
0.60
0.80
1.00

22. Highlight: debt and over indebtedness
22
On average, ~ 50% of all households have some debt, and ~10%
have debt 3 times > than income, even higher in US, NOR, NLD

23. 23
Highlights: since the crisis, differences
across countries in trends
0.4
0.6
0.8
1.0
1.2
1.4
1.6
2001 2007 2010 2013
USA
Net wealth of the the top 10
Median net wealth
0.4
0.6
0.8
1.0
1.2
1.4
1.6
2005 2012
CAN
0.4
0.6
0.8
1.0
1.2
1.4
1.6
2007 2012
GBR
0.4
0.6
0.8
1.0
1.2
1.4
1.6
2006 2012
AUS
0.4
0.6
0.8
1.0
1.2
1.4
1.6
2006 2010 2012
ITA
Net wealth of the the top 10
Median net wealth
0.4
0.6
0.8
1.0
1.2
1.4
1.6
2006 2010 2013
NLD

24. • Despite progress, statistical agenda is huge
– High wealth concentration at the top may require using
complementary sources (e.g. tax records, Forbes list of the
very rich, estimates of wealth ‘concealed’ in tax heavens)
and/or better/more comparable oversampling in surveys
But oversampling comes at a cost (e.g. when measuring jointly wealth
and income)
– Limited understanding of the drivers of changes in wealth
holdings at the individual level
SNA balance sheet data show that changes in assets prices dominate
changes due to household savings
implications for policies on taxing wealth, bequest and intra vivos
transfers
Future statistical agenda
on wealth inequalities
24

25. 25
The importance of prices changes for
household net wealth
Composition of changes in
household net worth, United States
Accumulated savings and holding
gains, Sweden
Cagetti et al. (2012), The Integrated
Macroeconomic Accounts of the Unites States,
NBEAR Conference, Boston
Bo Bergman (2015), Balance-Sheets: A Financial/
Liability Approach, IARIW-OECD Conference, Paris

26. • OECD wealth data rely on ex post harmonisation, what is need is
more harmonisation ex ante
• Greater ex ante harmonisation will require highlighting patterns that
may reflect different measurement practices: use it or loose it!!
• Methodological guidance provides a natural reference point for
assessing differences in country practices and aim to encourage more
countries to enter this measurement field
Thank you!
marco.mira@oecd.org
Conclusion
26