LWS Database
The Luxembourg Wealth Study Database (LWS) is the first cross-national wealth database in existence. Harmonized into a common framework (2024 Template User Guide), parallel to the one created for the LIS datasets, LWS datasets also contain household- and person-level data ( List of Variables, Printable version ) on assets and debt, market and government income, household characteristics, labour market outcomes and, in some datasets, expenditures and behavioural indicators.
Content of LWS Balance Sheet & Flow Variables
In order to provide more detailed documentation to our users, LIS has published detailed content tables of the flow, asset & liability variables for each dataset on, available in three downloadable Excel documents. The information is organised by country and within each country by year, giving a comprehensive overview to the users.
- How to read the tables
Read more »
These tables show the mapping of content at the level of each LWS flow variable and asset and liability variable. If a field is empty, no data was mapped at the level of that variable for that specific country in that year. However, due to the nesting system in the LWS database (see the variable list), an empty field for a lower-level variable means that either the information was not collected at all or that it was not collected at that level of detail. For example, if all pension data is collected in one variable, only pipension variable will be filled, and not the lower-level variables (universal pensions, assistance pensions, public contributory pensions, occupational and individual pensions). Consequently, the total pension income is available, but detailed information on the types of pensions is not.
If an upper-level flow variable (e.g., pilabour ) field is empty, no data was mapped directly at that level. Nevertheless, if the lower-level variables that constitute the components of this upper-level variable (in this example, wage income ( pi11 ), self-employment income ( pi12 ), and fringe benefits ( pi13)) are filled, the upper-level variable contains all the contents of these lower-level variables. If, in addition to the lower-level variables, there is content in the field of an upper-level variable (e.g., in pilabour, the content ‘income from secondary labor market activities’), this content describes the differential amounts in the microdata to which is added the content of the lower level variables that enter in its composition.
- Balance Sheet Variables:
Find detailed information on the content of LWS variables for Assets and Liabilities by purpose, organised at the country and by years here. Read more »
This document provides the contents of LWS assets and liabilities variables. For example, under Investment Funds and Alternative Investments (hafii), users will find detailed information about country-specific financial assets categorised there (e.g., the market value of managed accounts, value of unit and investment trusts, value of tax-free bond mutual funds, etc.). The same approach applies to other assets and liabilities variables.
The contents for all assets and liabilities variables refer to household‐level information, except for Pension Assets and Other Long‐Term Savings variables, available at both household and individual levels.
- Flow Variables:
Find detailed information on the content of LWS flow variables here. Read more »
In this document the users can find the original content that was mapped in each LIS flow variable (at the detail level provided by the data provider) from the main flow variables blocks: Current Income (with details on labour income, capital income, pensions, other public social benefits, and private transfers), Extraordinary Income, Income Deductions Transfers Paid and Loans Repayments (with details on income taxes and contributions, other direct taxes, inter-household transfers paid, mortgage and other loans instalments paid), Consumption Expenditure (by 12 categories), and Imputed Rent. The details are particularly useful for the content of public social benefits in which are listed the original benefits included in the original variables at the level provided by the original data source. The document details what is mapped at the individual level for the variables provided at the individual level and at the household level for all variables.
- Public Transfers by type (alternative set):
Find detailed information on the content of LWS variables for the alternative set of variables for Public Transfers by type here. Read more »
This document provides the contents of the alternative set of variables that splits the benefits by type in insurance-based (contributory) – p/hpub_i, universal benefits (non-contributory and non-means tested) – hpub_u, and assistance benefits (means and/or assets tested) – hpub_a. Please note that this breakdown might not be available for all datasets or all benefits (e.g., some of the original variables could contain more benefits of different types). In the cases where the original variable contains a mix of benefits of different types, or if for other reasons the benefit type cannot be determined, these variables are mapped at the upper level in the hpublic variable. Additionally, a benefit type may change over time; for example, policymakers can restrict eligibility for an initial universal benefit to only those in need, effectively transforming it into a means-tested benefit.
Note: These documents will be updated every time LIS releases new datasets with the new countries added, additional years for existing countries, and any revisions to previous data that might occur.
Generic codebook and extensive documentation
- For generic codebook of the LWS Database variables’ names, definitions, codes, comments, see here.
- For extensive documentation on the LWS Database, enter METIS.
List of LWS Datasets
Note: Year given is the wealth reference year, that is the year to which the wealth data pertain.
Newly added datasets (2025 Summer Data Splash) are listed in blue
* Forthcoming datasets are listed in red
Countries |
Wave III |
Wave IV |
Wave V |
Wave VI |
Wave VII |
Wave VIII |
Wave IX |
Wave X |
Wave XI |
Wave XII |
Australia |
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AU04 |
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AU10 |
AU14 |
AU16 |
AU18 AU20 |
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Austria |
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AT11 |
AT14 |
AT17 |
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AT21 |
Canada |
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CA99 |
CA05 |
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CA12 |
CA16 |
CA19 |
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Chile |
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CL07 |
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CL14 |
CL17 |
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CL21 |
China |
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*CN11 |
*CN13 |
*CN15 *CN17 |
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Denmark |
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DK15 DK16 DK17 |
DK18 DK19 DK20 |
DK21 DK22 |
Estonia |
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EE13 |
EE17 |
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EE21 |
Finland |
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FI09 |
FI13 |
FI16 |
FI19 |
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France |
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FR09 |
FR14 |
FR17 |
FR20 |
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Germany |
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DE02 |
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DE07 |
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DE12 |
DE17 |
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Greece |
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GR09 |
GR14 |
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GR18 |
GR21 |
India |
*IN91 |
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*IN02 |
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*IN12 |
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*IN18 |
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Italy |
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IT95 |
IT98 IT00 IT02 |
IT04 |
IT06 IT08 |
IT10 |
IT12 IT14 |
IT16 |
IT20 |
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Japan |
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JP04 |
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JP09 JP10 JP11 |
JP12 JP13 JP14 |
JP15 JP16 JP17 |
JP18 JP19 JP20 |
JP21 |
Luxembourg |
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LU10 |
LU14 |
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LU18 |
LU21 |
Mexico |
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MX19 |
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Norway |
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NO10 |
NO13 |
NO16 |
NO19 NO20 |
NO21 NO22 |
Slovakia |
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SK10 |
SK14 |
SK17 |
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SK21 |
Slovenia |
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SI14 |
SI17 |
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SI21 |
South Africa |
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ZA15 ZA17 |
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South Korea |
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KR17 |
KR18 KR19 KR20 |
KR21 KR22 |
Spain |
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ES02 |
ES05 |
ES08 |
ES11 |
ES14 |
ES17 |
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ES21 ES22 |
Sweden |
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*SE97 |
*SE98 *SE99 *SE00 *SE01 SE02 |
*SE03 *SE04 SE05 |
*SE06 *SE07 |
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United Kingdom |
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UK07 |
UK09 UK11 |
UK13 |
UK15 UK17 UK19 |
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*UK21 |
United States |
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US95 |
US98 US01 |
US04 |
US07 |
US10 |
US13 |
US16 |
US19 |
US22 |
For convenience, throughout our documentation, LIS uses short country/territory names – i.e., those that are commonly used in cross-national academia – in conjunction with standard two-letter ISO abbreviations. This convention does not imply the expression of any opinion whatsoever on the part of LIS concerning the legal status of any country or territory. LIS recognizes that several supranational organizations designate country/territory names which may differ from the ones that LIS uses. Examples include:
United Nations
World Bank
International Labour Organization
Organisation for Economic Co-operation and Development