The Luxembourg Wealth Study – A cross-country comparable database for household wealth research

Sierminska, Eva; Brandolini, Andrea; Smeeding, Timothy M.

doi:10.1007/s10888-006-9030-z

Cited by 120 publications

(61 citation statements)

References 3 publications

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“…Differences in welfare regimes and the emphasis these regimes put on the magnitude and generosity of publicly provided old-age insurance systems call for the consideration of pension entitlements in comparative wealth studies, for example the analyses based on the Luxembourg Wealth Study (LWS, see Sierminska et al 2006). While net worth can be successfully collected by means of survey data, the knowledge of pension entitlements on behalf of respondents is often limited.…”

mentioning

confidence: 99%

Extending the Empirical Basis for Wealth Inequality Research Using Statistical Matching of Administrative and Survey Data

Rasner¹,

Frick

Grabka

2011

SSRN Journal

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. This series presents research findings based either directly on data from the German SocioEconomic Panel Study (SOEP) or using SOEP data as part of an internationally comparable data set (e.g. CNEF, ECHP, LIS, LWS, CHER/PACO). SOEP is a truly multidisciplinary household panel study covering a wide range of social and behavioral sciences: economics, sociology, psychology, survey methodology, econometrics and applied statistics, educational science, political science, public health, behavioral genetics, demography, geography, and sport science. Terms of use: Documents inThe decision to publish a submission in SOEPpapers is made by a board of editors chosen by the DIW Berlin to represent the wide range of disciplines covered by SOEP. There is no external referee process and papers are either accepted or rejected without revision. Papers appear in this series as works in progress and may also appear elsewhere. They often represent preliminary studies and are circulated to encourage discussion. Citation of such a paper should account for its provisional character. A revised version may be requested from the author directly.Any opinions expressed in this series are those of the author(s) and not those of DIW Berlin.Research disseminated by DIW Berlin may include views on public policy issues, but the institute itself takes no institutional policy positions. Abstract:Social security entitlements are a substantial source of wealth that grows in importance over the individual's lifecycle. Despite its quantitative relevance, social security wealth has been thus far omitted from wealth inequality analyses. In Germany, it is the lack of adequate micro data that accounts for this shortcoming. The two main contributions of this paper are: First, to elaborate a statistical matching approach that complements information on net worth as surveyed in the German Socio-Economic Panel (SOEP), a population representative panel study, with information on social security wealth from the Sample of Active Pension Accounts (SAPA), a large-scale administrative dataset maintained by the German Statutory Pension Insurance. Second, we show to what extent the inclusion of social security wealth affects the level and the distribution of individual net worth as well as overall inequality. The present value of pension entitlements (including entitlements from the statutory pension system as well as from the separate system for civil servants) amounts to 5.6 trillion Euros, which correspond...

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confidence: 99%

Extending the Empirical Basis for Wealth Inequality Research Using Statistical Matching of Administrative and Survey Data

Rasner¹,

Frick

Grabka

2011

SSRN Journal

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“…However, as Figure 4 shows, signi…cant improvements in data availability are not con…ned to developing countries. A renewed interest in the …ne detail of the income distribution among the seriously rich has led to the synthesis of data from tax authorities that has added a new perspective to international comparisons Piketty (2007); new work making available micro-data on wealth will also enhance understanding of what is going on in the upper tail of the income distribution (Sierminska et al 2006). …”

Section: Welfare Economics and Distributionmentioning

confidence: 99%

Income distribution and inequality

Cowell¹

2015

The Elgar Companion to Social Economics, Second Edition

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“…At the time of data collection, all of these countries were experiencing low unemployment and positive GDP growth (Table 1) The data contain detailed information on multiple income sources and financial and nonfinancial assets and debts. On the basis of this detailed information, we use the conceptual framework developed by the Luxembourg Wealth Study (described in Sierminska et al (2006)) for creating harmonized variables of net worth (total assets: financial assets, principal residence, investment real estate and business equity minus liabilities: mortgages and non-housing debt) and income. Each of the wealth variables have been bottom and top coded at their 1% and 99% levels to stop outliers from over-influencing our results and monetary variables have been converted to 2007 Euros using PPP and price indices.…”

Section: Datamentioning

confidence: 99%

“…Our focus is on the main assets and liabilities held by households; financial assets, main residence, investment real estate and debt, with a focus on mortgages and non-housing debt. 2 Past research suggests a large role for institutions in explaining cross-national differences in portfolios. Christelis et al (2012) find that characteristics play a small or negligible role in generating observed international differences for households 50 years and over.…”

Section: Introductionmentioning

confidence: 99%

Cross-National Differences in Wealth Portfolios at the Intensive Margin: Is there a Role for Policy?

Doorley¹,

Sierminska²

2014

Research on Economic Inequality

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. www.econstor.eu The Institute for the Study of Labor (IZA) in Bonn is a local and virtual international research center and a place of communication between science, politics and business. IZA is an independent nonprofit organization supported by Deutsche Post Foundation. The center is associated with the University of Bonn and offers a stimulating research environment through its international network, workshops and conferences, data service, project support, research visits and doctoral program. IZA engages in (i) original and internationally competitive research in all fields of labor economics, (ii) development of policy concepts, and (iii) dissemination of research results and concepts to the interested public. Terms of use: Documents in D I S C U S S I O N P A P E R S E R I E SIZA Discussion Papers often represent preliminary work and are circulated to encourage discussion. Citation of such a paper should account for its provisional character. A revised version may be available directly from the author. Using harmonized wealth data and a novel decomposition approach in this literature, we show that cohort effects exist in the income profiles of asset and debt portfolios for a sample of European countries, the U.S. and Canada. We find that the association between household wealth portfolios at the intensive margin (the level of assets) and household characteristics is different from that found at the extensive margin (the decision to own). Characteristics explain most of the cross-country differences in asset and debt levels, except for housing wealth, which displays large unexplained differences for both the under-50 and over-50 populations. However, there are cohort differences in the drivers of wealth levels. We observe that younger households' levels of wealth, given participation, may be more responsive to the institutional setting than mature households. Our findings have important implications, indicating a scope for policies which can promote or redirect investment in housing for both cohorts and which promote optimal portfolio allocation for mature households.JEL Classification: G11, G21, J10

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The Luxembourg Wealth Study – A cross-country comparable database for household wealth research

Abstract: household wealth, household portfolios, distribution of net worth, international comparative data sources,

Cited by 120 publications

References 3 publications

Extending the Empirical Basis for Wealth Inequality Research Using Statistical Matching of Administrative and Survey Data

Extending the Empirical Basis for Wealth Inequality Research Using Statistical Matching of Administrative and Survey Data

Income distribution and inequality

Cross-National Differences in Wealth Portfolios at the Intensive Margin: Is there a Role for Policy?

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