Presentation by: Piotr Paradowski (Cross-National Data Center in Luxembourg) OECD Conference on wealth inequalities: Measurement and policies Paris, 26 April 2018.

1. Missing wealth components – should we care?
An evidence from the LWS database
Piotr Paradowski
Presentation prepared for
OECD Conference on wealth inequalities: measurement and policies
Paris, 26 April 2018

2. Motivation
• OECD guidelines for Micro Statistics on Household
Wealth (2013)
• The Household Finance and Consumption Network
(2006-
• Luxembourg Wealth Study (2003-
• Wealth inequality becomes a major concern for policy-
making
• So, we need to evaluate the sources of wealth
inequality as well as the effectives of policies
• We need to understand the distributional impact of
wealth components
• Concerns about wealth distribution should not only be
about the top part of this distribution

3. Questions
• Do we have all subcomponents of wealth
to understand the wealth distribution? If
not, what is missing?
• Do we still need to enlarge the range of
assets and liabilities?
• How much inequality indicators change if
we broaden the wealth components?
• Does broadening the range of assets
matter for the policy-making process?

4. Luxembourg Income Study (LIS)
Mission
To enable, facilitate, promote, and conduct cross-national
comparative research on socio-economic outcomes and on the
institutional factors that shape those outcomes.

5. The LIS Databases: LIS and LWS
1983 2018
 20 datasets
 12 high-income countries
 1994 - 2007
LWS Database
LIS Database
Pilot LWS project
New LWS
database
 37 datasets
 13 high-income countries
 1995 - 2016
312 datasets
Wave II around 1985
Wave I around 1980
Historical database
Wave V around 2000
Wave IV around 1995
Wave III around 1990
Wave VI around 2004
Wave VII around 2007
Wave VIII around 2010
Asia: 4 East, 1 South , 3 West
America: 2 North, 3 Central, 1
Caribbean, 6 South
Europe: 23 EU and 6 non EU
Oceania: 1 country
Africa: 2 countries
Time coverage Geographical
coverage
Wave IX around 2013
Wave X around 2016

6. LWS Coverage
Number of datasets included in LIS for each country
(7,15]
(4,7]
(2,4]
(1,2]
[.5,1]
not in LIS
Number of datasets included in
LWS
8 and more
5 to 7
3 to 4
2
1
Not in LWS

7. LWS – household balance sheet

8. LWS availability matrix of assets

9. LWS availability matrix of liabilities

10. LWS availability matrix

11. Changes in Gini index:
disposable wealth and adjusted wealth
Country Gini_dnw Gini_anw Gini_anw1 Gini_tnw Gini_d_a
(%)
Gini_d_a1
(%)
Gini_d_t
(%)
Rank_d_a
(%)
DE12 0.7836 0.7582 0.747 3.24145 4.67075 1
US16 0.8859 0.8675 0.8605 2.07698 2.86715 2
CA12 0.7131 0.7036 0.6714 0.671 1.33221 5.84771 5.9038 3
UK09 0.6127 0.6102 0.6083 0.6365 0.40803 0.718135 -3.88445 4
UK11 0.6281 0.6265 0.6239 0.6323 0.254731 0.66868 -0.66869 5
FI13 0.6498 0.6484 0.5477 0.21545 15.7125 6
GR14 0.5988 0.5986 0.033406 7
IT14 0.5896 0.5901 0.595 -0.0848 -0.91588 8
AU10 0.6113 0.6018 1.55406
Gini_dnw = Gini of disposable net worth
Gini_anw = Gini of adjusted net worth
Gini_d_a = % change in Gini (from disposable to adjusted)
Rank_d_a = country’s ranking based on % change in Gini (from disposable to adjusted)

12. Changes in Gini index:
disposable wealth and adjusted wealth
(with occupational pensions)
Country Gini_dnw Gini_anw Gini_anw1 Gini_tnw Gini_d_a
(%)
Gini_d_a1
(%)
Gini_d_t
(%)
Rank_d_a1
(%)
FI13 0.6498 0.6484 0.5477 0.21545 15.7125 1
CA12 0.7131 0.7036 0.6714 0.671 1.33221 5.84771 5.9038 2
US16 0.8859 0.8675 0.8605 2.07698 2.86715 3
UK09 0.6127 0.6102 0.6083 0.6365 0.40803 0.718135 -3.88445 4
UK11 0.6281 0.6265 0.6239 0.6323 0.254731 0.66868 -0.66869 5
IT14 0.5896 0.5901 0.595 -0.0848 -0.91588 6
DE12 0.7836 0.7582 0.747 3.24145 4.67075
AU10 0.6113 0.6018 1.55406
GR14 0.5988 0.5986 0.033406
Gini_dnw = Gini of disposable net worth
Gini_anw1 = Gini of adjusted net worth with occupational pensions
Gini_d_a1 = % change in Gini (from disposable to adjusted with occupational pensions)
Rank_d_a1 = country’s ranking based on % change in Gini (from disposable to adjusted with
occupational pensions)

13. Changes in Gini index:
disposable wealth and total wealth
Country Gini_dnw Gini_anw Gini_anw1 Gini_tnw Gini_d_a
(%)
Gini_d_a1
(%)
Gini_d_t
(%)
Rank_d_t
(%)
CA12 0.7131 0.7036 0.6714 0.671 1.33221 5.84771 5.9038 1
DE12 0.7836 0.7582 0.747 3.24145 4.67075 2
AU10 0.6113 0.6018 1.55406 3
UK11 0.6281 0.6265 0.6239 0.6323 0.254731 0.66868 -0.66869 4
UK09 0.6127 0.6102 0.6083 0.6365 0.40803 0.718135 -3.88445 5
IT14 0.5896 0.5901 0.595 -0.0848 -0.91588
US16 0.8859 0.8675 0.8605 2.07698 2.86715
FI13 0.6498 0.6484 0.5477 0.21545 15.7125
GR14 0.5988 0.5986 0.033406
Gini_dnw = Gini of disposable net worth
Gini_tnw = Gini of total net worth
Gini_d_t = % change in Gini (from disposable to total)
Rank_d_t = country’s ranking based on % change in Gini (from disposable to adjusted)

14. Gini index decomposition (gross assets)*:
AU10
Variable Share Gini Elasticity
Real Estate 0.5972 0.5761 -0.0181
Other Non-Fin 0.1224 0.518 -0.037
Financial Assets 0.1424 0.8769 0.0477
Pensions 0.138 0.7537 0.0073
TOTAL 1 0.565 0
Variable Share Gini Elasticity
Principal Residence 0.4353 0.5286 -0.0784
Other Real Estate 0.1628 0.9057 0.0604
Business 0.0258 0.9897 0.0119
Consumer Goods 0.0969 0.4125 -0.049
Cash/Savings 0.0393 0.7868 -0.0079
Debt securities 0.0005 0.9974 0
Stocks 0.0965 0.9656 0.0552
Alternative Investm 0.0047 0.9861 0.0004
Pensions 0.1382 0.7537 0.0073
TOTAL 1 0.565 0
* Lerman and Yitzhaki (1985)

15. Gini index decomposition (gross assets)*:
CA12
Variable Share Gini Elasticity
Real Estate 0.4447 0.6305 -0.04
Other Non-Fin 0.1432 0.7985 0.0165
Financial Assets 0.1112 0.8473 0.0151
Pensions 0.301 0.7433 0.0085
TOTAL 1 0.6217 0
Variable Share Gini Elasticity
Principal Residence 0.3497 0.5975 -0.0634
Other Real Estate 0.0998 0.9311 0.0235
Business 0.0847 0.9749 0.0366
Consumer Goods 0.06 0.5898 -0.0199
Cash/Savings 0.0441 0.7995 -0.0047
Debt securities 0.0026 0.9872 0.0004
Stocks 0.0292 0.9797 0.0117
Alternative Investm 0.0256 0.9646 0.0065
Occupational Pens 0.2013 0.813 0.0034
Volunt. Indiv. Pens 0.099 0.8042 0.006
Social Sec. Pens 0.004 0.9823 -0.0001
TOTAL 1 0.6217 0
* Lerman and Yitzhaki (1985)

16. Gini index decomposition (gross assets)*:
US16
Variable Share Gini Elasticity
Real Estate 0.3515 0.7465 -0.0416
Other Non-Fin 0.2047 0.9204 0.0159
Finanacial Assets 0.2843 0.933 0.0316
Volunt. Pens/Life Ins 0.1331 0.8782 -0.0024
Occup. Pens (DC) 0.0265 0.9487 -0.0036
TOTAL 1 0.8082 0
Variable Share Gini Elasticity
Principal Residence 0.2437 0.6894 -0.0534
Other Real Estate 0.11 0.9597 0.0116
Business 0.1715 0.9878 0.0307
Cons Goods 0.033 0.6165 -0.015
Cash/Savings 0.0561 0.863 -0.0036
Debt securities 0.0129 0.9958 0.0021
Stocks 0.0818 0.9832 0.0138
Alternative Investm 0.1305 0.9744 0.0197
Life Insure 0.0092 0.9585 -0.0009
Volunt. Indiv. Pens 0.1247 0.8868 -0.0014
Occup. Pens (DC) 0.0266 0.9487 -0.0036
TOTAL 1 0.8082 1
* Lerman and Yitzhaki (1985)

17. Gini index decomposition (gross assets)*:
UK11
Variable Share Gini Elasticity
Real Estate 0.4366 0.5617 -0.0536
Other Non-Fin 0.1739 0.6185 -0.0169
Financial Assets 0.1316 0.8066 0.0255
Pensions 0.2579 0.7868 0.0449
TOTAL 1 0.584 0
Variable Share Gini Elasticity
Principal Residence 0.5036 0.5514 -0.0481
Other Real Estate 0.0359 0.9696 0.0139
Business 0.0717 0.9917 0.048
Cons Goods 0.1432 0.4463 -0.0593
Cash/Savings 0.0678 0.7695 0.0012
Debt securities 0.0268 0.9409 0.0079
Stocks 0.0251 0.9786 0.0138
Alternative Invest 0.0232 0.9549 0.0091
Other Finan. Assets 0.0062 0.9937 0.003
Volunt. Indiv. Pens 0.025 0.9403 0.0043
Occupational Pens 0.0148 0.9545 0.001
Social Sec. Pens 0.0565 0.9144 0.0052
TOTAL 1 0.584 0
* Lerman and Yitzhaki (1985)

18. Conclusions
• We need to have detailed components of
financial and non-financial assets,
specifically pension assets
• We can be misinformed if we have only
aggregated measures of assets
• All this is necessary for informed
governmental policies.

19. Thank you for your attention
Any questions are welcome !
“When you can measure what you are speaking about and express
it in numbers you know something about it. But when you cannot
measure it or express it in numbers, you knowledge is of a meager
and unsatisfactory kind.”
Sir William Thomson
British Mathematician and physician (Belfast, 1824 - Netherhall, 1907)