In recent years, data from the Luxembourg Income Study (LIS) and Luxembourg Wealth Study (LWS) Databases have been extensively featured across multiple flagship United Nations publications.

The UNDP Human Development Report 2025 – A Matter of Choice: People and Possibilities in the Age of AI lists LIS among its official statistical references, underscoring the database’s global relevance. Similarly, UN Women’s World Survey on the Role of Women in Development 2024 draws on LIS data for several of its calculations.

At the regional level, the ESCWA Inequality Projection for Poverty Analysis (2024) cites LIS as an additional source for harmonized income distribution data. The UNICEF Report Card 18 – Child Poverty in the Midst of Wealth (2023) also references LIS as a key data source for its analyses.

Moreover, the ECLAC publication La distribución del ingreso y la riqueza: nuevas aproximaciones (2023) features a major chapter constructed directly from the LWS Database, with multiple figures and tables attributed to the “LIS Data Center, Luxembourg Wealth Study Database (LWS).”

Additionally, the ILO Working Paper 128 – Combating Inequalities: What Role for Universal Social Protection? (2024) draws upon LIS data to examine the role of social protection in reducing inequality.

Collectively, these reports highlight the central role of LIS and LWS data in advancing evidence-based policymaking and comparative research on inequality, poverty, and development across the globe.

LIS and LWS data were used extensively in the OECD’s new flagship report “To Have and Have Not – How to Bridge the Gap in Opportunities.” The report applies an innovative methodology to measure inequality of opportunity across OECD countries, going beyond outcome analysis to consider how individual circumstances shape opportunities throughout the life cycle.

In particular, Chapter 3, “Geographic Inequalities in Access to Opportunities,” draws on LIS and LWS data to produce several sub-national indicators. It examines how the places where people are born and raised influence their opportunities in life, showing how geography contributes to long-term inequalities in outcomes. The report also identifies policy options to promote social mobility at both national and local levels.

by Denys Orlov, (National Bank of Slovakia, Bratislava University of Economics and Business)

Understanding the determinants of voluntary savings is essential for ensuring both individual financial security and broader economic stability. Savings act as a crucial buffer against unexpected financial shocks and play a central role in sustaining living standards throughout retirement. In this article, Denys Orlov explores how the propensity to save for old age in the United Kingdom may be associated with financial literacy and a range of socio-demographic characteristics.

Full article is available here.

by Chiara Mussida, (Università Cattolica del Sacro Cuore), Dario Sciulli, (University of Chieti-Pescara)

In-work poverty (IWP) has become a persistent challenge in Europe, reflecting both the expansion of non-standard and low-paid employment, as well as the varying ability of welfare states to mitigate income inequalities. This contribution by Chiara Mussida and Dario Sciulli examines how social protection expenditure and labor market institutions affect the incidence of IWP across 22 European countries over the period 2009 to 2023.

Full article is available here.

by Jörg Neugschwender, (LIS)

Luxembourg’s unique demographic and economic profile, marked by a large foreign population and daily inflows of cross-border workers, raises important questions about inequality and social protection. Using LIS data for Luxembourg, France, Germany, and Belgium, this contribution by Jörg Neugschwender compares median incomes across household types, focusing on differences shaped by labour markets, pensions, and family benefits.

Full article is available here.

LIS is happy to announce the following data updates:

• France (2 new LIS datasets and 23 revised) – Addition of FR21 and FR22 to the LIS Database.
  Read more »
  Two new datasets from France (FR21 and FR22) have been added to the LIS Database. The datasets are based on the Tax and Social Incomes Survey (ERFS), conducted by the National Institute of Statistics and Economic Studies (INSEE). In addition, many datasets of the existing series have been revised to incorporate several improvements. FR98-FR20: The General Social Contribution on capital income, previously recorded under private transfers (hiprivate), is now recorded together with the capital incomes they relate to hi21 (interest and dividends) and hicapital (capital income). This reallocation has no effect on hitotal (total income) or dhi (disposable household income). FR19 and FR20: The 100€ “indemnité inflation” (a one-time payment to most working-age people earning below a certain income threshold) has been moved from pi11 (wage income) to hipubsoc (public social benefits (excl. pensions)). Minor revisions were also made to the calculation of social security contributions for the self-employed workers, resulting in small adjustments to pxitsc (income taxes and contributions), pi12 (self-employment income), and the corresponding upper level variables until dhi (disposable household income).
• Germany (2 new LIS datasets and 37 revised; 4 revised LWS datasets) – Update of the LIS series for DE21 and DE22 and revision based on SOEP-Core v40.1eu Edition.
  Read more »
  Update of the LIS series
  Two new datasets from Germany have been added to the LIS Database (DE21 and DE22). The data are harmonised from the German Socio-Economic Panel (GSOEP) and the German series DE84 to DE22 in LIS now aligns with the SOEP-Core v40.1eu edition provided by the German Institute for Economic Research (DIW), superseding the previous release that relied on v38.1eu edition. This new version implements besides the improved weighting and income imputation for non-respondents revised variables for edmom_c / eddad_c (mother’s / father’s highest education level). Information on parents country origin (immigr_c) is now available for the entire GSOEP series.
  
  
  Revisions of the LWS series
  The previous released datasets from the GSOEP series DE02-DE17 have been updated to reflect the improvements in the latest version v40.1eu edition by DIW, mostly concerning the update of the imputation of incomes for non-respondents. The balance sheet amounts are not concerned by this update.
• India (4 new LWS datasets) – NEW country! Addition of IN91, IN02, IN12, IN18 to the LWS Database.
  Read more »
  One new country has been added to the LWS Database: India. Four LWS datasets from have been harmonised and added (IN91, IN02, IN12, IN18) — these are based on the All India Debt and Investment Survey (AIDIS) and the related National Sample Survey (NSS) rounds carried out by the National Sample Survey Office (NSSO), Ministry of Statistics and Programme Implementation (MoSPI).
• Luxembourg (2 new LIS datasets and 6 revised) – Addition of LU22 and LU23 to the LIS Database.
  Read more »
  Two new datasets from Luxembourg have been added to the LIS Database (LU22 and LU23). The data are based on the Socio-economic Panel “Living in Luxembourg” / Panel socio-économique “Liewen zu Letzebuerg“ (PSELL III), from which is also created the Survey on Income and Living Conditions (EU-SILC). The data are provided by the National Institute for Statistics and Economic Studies of the Grand Duchy of Luxembourg (STATEC).
  The datasets LU15-LU18, and LU21 and LU22 have been revised for consistency. In LU15-LU18 public contributory pensions (pi32) were revised for a small number of individuals which had an impact on the poverty rate of elderly in LU15-LU17, decreasing it slightly. Minor consistency revisions were carried out in LU21 and LU22 which do not affect the LIS Key Figures.
• Switzerland (3 new LIS datasets and 14 revised) – Annualisation to CH22 in the LIS Database.
  Read more »
  Three new datasets from Switzerland have been added to the LIS Database (CH20, CH21, and CH22). The datasets are based on the Swiss Statistics on Income and Living Conditions (SILC) from the Swiss Federal Statistical Office (FSO). Revisions to the earlier datasets CH06-CH19 concern the variable wexptl (total work experience), where additional ‘0 years work experience’ values were placed.
• United Kingdom (1 new LWS dataset and 7 revised) – Addition of UK21 to the LWS Database.
  Read more »
  One new LWS dataset from the UK has been added (UK21 ). The dataset is harmonised from the Wealth and Assets Survey (WAS) produced by the Office for National Statistics (ONS).
  The previous datasets of the UK wealth series (UK07, UK09, UK11, UK13, UK15, UK17, and UK19) were revised following changes in the methodology introduced by the UK Office for National Statistics (ONS) to estimate defined benefit (DB) pension wealth. Because revised estimates for earlier waves have not yet been produced using the new approach, the variable hasodb (defined benefit occupational pensions) was emptied in all these datasets. As a result, the variables inw (integrated net worth) and haso (occupational pensions) differ from their values in previous releases of the LWS UK data. For more information see Compare.It.
  In addition, the UK19 dataset was revised to ensure consistency with other UK waves in the treatment of public transfers. Specifically, the variables hpub_i (insurance transfers) and hpublic (public transfers) were adjusted.

• Uruguay (2 new LIS datasets and 15 revised) – Addition of UY23 and UY24 to the LIS Database.
  Read more »
  Two new datasets from Uruguay have been added to the LIS Database (UY23 and UY24). The datasets are based on the Continuous Household Survey (ECH) from the Uruguayan National Institute of Statistics (INE).
  The datasets UY06 to UY22 have been slightly revised. The variable nrooms (number of rooms available in the household) is now included in UY22. In addition, the variable disabled (indication of disability) was constructed for all datasets from UY06 to UY18, based on an approximation using the type of pensions received. The income section has been marginally revised for UY13-UY22, with little to no effect on the LIS Key Figures.








  Click on `Read more’ to access more details on the newly added and revised datasets

Marc Fleurbaey, Chaired Professor at Paris School of Economics, presented the LIS Summer Lecture: Social contagion, inequality and mobility.

Marc Fleurbaey is a CNRS Senior Researcher, Chaired Professor at the Paris School of Economics, and Associate Professor at ENS-Ulm, where he co-directs the Center on the Environment and Society (CERES). Formerly Robert E. Kuenne Professor at Princeton University, he has authored several books including Beyond GDP and A Theory of Fairness and Social Welfare, and published over 200 academic articles. A coordinating lead author for the IPCC and a founding member of the International Panel on Social Progress, he has served on the UN Committee for Development Policy and received the CNRS Silver Medal in 2024. He is a Fellow of the Society for the Advancement of Economic Theory.

by Supriya Lakhtakia, Deepak Malghan (Indian Institute of Management Bangalore), and Hema Swaminathan, (Asian Development Bank & Indian Institute of Management Bangalore)

The authors explore occupational assortative mating and its implications for gender inequality in earnings. Using LIS data across countries and time, they investigate how patterns of occupational similarity between partners influence both inter- and intra-household inequality, offering new insights into the global dynamics of household-level gender disparities.

Full article is available here.

by Jonathan Bradshaw, (University of York), Gianluca Munalli, (The Learning for Well-being Institute), and Dominic Richardson, (The Learning for Well-being Institute)

Using recent LIS data, the authors conduct a comparative analysis of child poverty across countries. They analyse a set of poverty rates by household composition and offer evidence-based policy recommendations to address child poverty and its long-term consequences.

Full article is available here.

by Vladimir Hlasny , (UN Economic and Social Commission for Western Asia (ESCWA))

This article addresses the issue of earnings underreporting and tax overreporting in global household surveys. Drawing on earlier literature and comparative LIS-based analysis, the author examines the risks of measurement error in survey-based income data, highlighting its impact on assessments of inequality and poverty.

Full article is available here.