Data

European Social Survey (ESS)

The ESS is an academically driven cross-national survey that has been conducted across Europe since its establishment in 2001. Every two years, interviews are conducted with newly selected, cross-sectional samples. The survey measures the attitudes, beliefs and behaviour patterns in more than thirty nations. In 2018/19, the ESS collected survey data on justice and fairness with the aim of investigating how people feel that they are coping with increasing economic and educational inequalities. The ESS data is available free of charge for non-commercial use and can be downloaded from the ESS Data Portal.

International Social Survey Programme (ISSP)

The ISSP is a cross-national collaboration programme conducting annual surveys on diverse topics relevant to social sciences. Every year, interviews are conducted with newly selected, cross-sectional samples. ISSP modules specialising in social inequality were conducted in 1987, 1992, 1999, 2009, and 2019. The ISSP data is available free of charge for non-commercial use and can be downloaded from the ISSP Data Portal of GESIS Leibniz Institute for the Social Sciences.

European Values Study (EVS)

The EVS is an academically driven cross-national survey research programme on human values that has been conducted across Europe since its establishment in 1981. Every nine years, interviews are conducted with newly selected, cross-sectional samples. The survey provides insights into ideas, beliefs, preferences, attitudes, values and opinions of citizens across Europe including topics of social inequality and the distribution of scarce resources. In 2017, the EVS data was collected jointly with the World Values Survey (WVS) programme (see below). The EVS data is available free of charge and can be downloaded from the EVS Data Portal.

World Values Survey (WVS)

The WVS is an academically driven cross-national survey programme on social, political, economic, religious, and cultural values of people around the world including topics of social inequality and the distribution of scarce resources. Initiated by Ronald Inglehart in 1981, interviews are conducted with newly selected, cross-sectional samples every five years. In 2017, the data was collected jointly with the European Values Study (EVS) research programme (see above). The eighth wave of the WVS (2024-2026) plans to cover approximately 80 countries worldwide. The WVS data is free of charge and can be downloaded from the WVS Data Portal.

Standardized World Income Inequality Database (SWIID)

The SWIID is an academically led, cross-national dataset developed by Frederick Solt (University of Iowa) that aims to maximise the cross-national and over-time comparability of income inequality estimates for the widest possible range of countries and years. SWIID integrates information from international databases, national statistical offices, and academic sources, using the Luxembourg Income Study as its primary benchmark. The dataset provides Gini coefficients for disposable (post-tax, post-transfer) income and market (pre-tax, pre-transfer) income, as well as measures of absolute redistribution (market-income inequality minus disposable-income inequality) and relative redistribution (market-income inequality minus disposable-income inequality, divided by market-income inequality). SWIID currently covers 199 countries spanning from the 1960s/80s to the early 2020s and is updated on a regular basis. The data is available free of charge and can be downloaded from the author’s website or the Harvard Dataverse.

World Inequality Database (WID)

The WID is an academically led, cross-national database that provides open access to harmonised data on the historical evolution of income and wealth inequality worldwide. The database is coordinated by the World Inequality Lab at the Paris School of Economics and the University of Berkeley, California and builds on the foundational work of leading inequality scholars, including Anthony Atkinson, Thomas Piketty, and Emmanuel Saez. WID integrates information from national accounts, household surveys, fiscal data, and wealth rankings to produce a wide range of inequality indicators, including Gini coefficients and top-bottom income share ratios based on income (pre-tax and post-tax) and wealth data. In addition, the database provides indicators on gender inequality in labour income and carbon inequality. WID covers all countries worldwide and spans from the 1800s to the present; where proper data is unavailable, estimates are constructed using imputation methods based on regional and country-level information from comparable cases. The database represents a substantial update and extension of the World Top Incomes Database (2011) and the World Wealth and Income Database (2015). The data is available free of charge and can be downloaded from the WID Data Portal.

The Chartbook of Economic Inequality

The Chartbook of Economic Inequality is an academically led, cross-national database established by Anthony Atkinson, Joe Hasell (University of Oxford), Salvatore Morelli (University of Roma Tre) and Max Roser (University of Oxford). It documents long-term changes in economic inequality drawing on data from academic and institutional sources, including data collected by Anthony Atkinson, Thomas Piketty, and Andrea Brandolini, the World Inequality Database (WID), the OECD, EU-SILC and the LIS. Key inequality indicators include the Gini coefficient (typically based on the equivalised household disposable income), income shares of the top 1 per cent (mainly based on gross incomes derived from tax records), income- or consumption-based relative poverty measures, the dispersion of individual earnings measured as the ratio of the top 10 per cent to the median earnings, and wealth shares of the top 1 per cent (based on net wealth data). The Chartbook of Economic Inequality covers 25 countries from around the world, and spans over more than one hundred years (for selected countries). The data is available free of charge and can be downloaded from the project’s website.

Leiden University Datasets on Poverty, Fiscal Redistribution & Sectoral Income Inequality

The Department of Economics at Leiden University offers a collection of academically led cross-national datasets, including data on poverty, fiscal redistribution and sectoral income inequality. The datasets draw on the Luxembourg Income Study (LIS) and can be downloaded free of charge from the department’s website. (1) The Budget Incidence Fiscal Redistribution Dataset on Relative Income Poverty Rates (2019), assembled by Koen Caminada and Jinxian Wang, provides information on the disentanglement of relative income poverty measures and anti-poverty effects of social transfers and income taxes. Currently, the database covers 49 countries for the period 1967-2016. (2) The Budget Incidence Fiscal Redistribution on Income Inequality (2017), assembled by Jinxian Wang and Koen Caminada, is a partial follow-up to the Budget Incidence Fiscal Redistribution Database (2011), and provides information on the disentanglement of income inequality and the redistributive effect of social transfers and income taxes. Currently, the database covers 47 countries for the period 1967-2014. (3) The Sectoral Income Inequality Dataset (2014), assembled by Chen Wang, Stefan Thewissen and Olaf van Vliet, contains information on multiple indicators of earnings inequality and employment within 21 industrial (sub-)sectors for a total of 12, primarily European, countries between 1969 and 2005. Sectors include agriculture, mining, manufacturing, utilities, construction, wholesale, transport and telecommunications, financial services and community services.

OECD Income & Wealth Distribution Database (IDD/WDD)

The Organisation for Economic Co-operation and Development (OECD) administers two cross-national databases to monitor trends in economic inequality. Both databases are updated on a regular basis and can be downloaded free of charge. (1) The Income Distribution Database (IDD) provides harmonised indicators on income inequality and relative poverty. Key inequality indicators include Gini coefficients (incl. standard errors), income share ratios (80/20, 90/10, 90/50, 50/10), the Palma ratio, and absolute income shares of the top and bottom 10, 20, and 40 per cent of the population. Indicators are primarily based on disposable equivalent household income, with selected measures also available for market income and for specific age groups. The IDD currently covers 45 countries, with data for most countries spanning from the early 2000s to the early 2020s. (2) The Wealth Distribution Database (WDD) provides harmonised indicators on wealth inequality, debt, and asset poverty. Key inequality indicators include mean-to-median wealth ratios, wealth shares of the bottom 20 and 40 per cent, the middle 50 per cent, and the top 10, 5, and 1 per cent, as well as indicators on household debt-to-asset ratios. Indicators are based on net wealth. The WDD currently covers 30 countries, with data generally available from the 2010s onward.

UNU-WIDER World Income Inequality Database (WIID)

The WIID, established and administered by UN-WIDER, provides cross-national information on income inequality worldwide drawing on data from historical repositories, current institutional databases, national statistical offices, and independent academic sources. The WIID includes a large variety of inequality estimates and indices, such as the Gini coefficient, Theil indices, Atkinson measures, as well as different income shares and ratios. For selected countries, it also provides estimates on within- and between group rural-urban inequality. Currently, the WIID covers 201 countries (including historical entities), mainly from 1940 onward. The WIID datasets, including the WIID Companion, are available free of charge and can be downloaded from the WIID Data Portal.

EUROSTAT Income and Living Conditions Database

Eurostat, the statistical office of the European Union (EU), provides a database on Income and Living Conditions using comparable cross-sectional and longitudinal survey data of the EU Statistics on Income and Living Conditions (EU-SILC). The database includes a collection of datasets on income inequality (ilc_iei). Datasets depict Gini coefficients (ilc_di12 a-c) and income share ratios (ilc_di11 a-i) for different income types by sex, age and region (NUTS 2) and provide information on the effects of taxes and social transfers. In addition, the database offers collections of datasets on the risk of poverty or social exclusion (ilc_pe), income distribution and monetary poverty (ilc_ip), living conditions (ilc_lv), and material deprivation (ilc_md). The database covers EU Member States, Iceland, Norway, Switzerland, the United Kingdom, the Western Balkans and Türkiye. Datasets are updated regularly and can be downloaded free of charge for a period of ten years (on a rolling basis) from the Eurostat Data Portal.

World Bank Poverty & Inequality Platform (PIP)

The PIP, established and administered by the World Bank, provides information on poverty, inequality, and shared prosperity on the global, regional, and country-level and over time. Estimates are based on country-level household survey data, primarily obtained by the Poverty and Equity Global Practice, which works closely with national statistical offices, and forms part of the World Bank’s Global Monitoring Database. PIP offers harmonised poverty and inequality estimates, including the poverty headcount ratio, the poverty gap index, the poverty severity index, the Gini index, the Theil index, income deciles, the Palma Ratio, the top 20 to bottom 20 per cent ratio, the mean log deviation, and the Wolfson polarisation index. Currently, PIP covers 172 countries around the world, spanning from 1981 to 2024. The platform replaces PovcalNet and the Poverty and Equity Data Portal, which were phased out in March 2022. All data and visualisations are available free of charge and can either be downloaded from the platform’s website or accessed directly within statistical packages, such as R and Stata.

University of Texas Inequality Project (UTIP)

The UTIP is concerned with measuring and explaining inequality in wages and earnings around the world. The project is directed by Lyndon B. Johnson (University of Texas at Austin) and offers academically led datasets on various pre-computed inequality measures at the national and sub-national level. (1) The UTIP-UNIDO Dataset on Industrial Pay Inequality is a global cross-national dataset using statistics of the United Nations Industrial Development Organization and provides information on industrial pay-inequalities covering 151 countries from 1963 to 2015. (2) The Estimated Household Income Inequality Data Set (EHII) is a cross-national dataset based on the UTIP-UNIDO Dataset and the World Bank’s Deininger and Squire Dataset and provides Gini coefficients and Theil indices for gross/market incomes covering 154 countries from 1963 to 2015. (3) Additional datasets provide inequality estimates at the regional, national, and sub-national level, including sector-specific estimates for selected countries and time periods: European countries (2001-2010), Argentina (annual data for 1994-2005, monthly data for 1994-2006), Brazil (1996-2005), China (1987-2012), Cuba (1991-2001), India (1979-1998), Russia (1990-2000), Taiwan (1979-2006), Türkiye (1980-2013) and the US (1969-2022). All datasets are available free of charge and can be downloaded from the UTIP Data Portal.

Global Database on Intergenerational Mobility (GDIM)

The GDIM, established and administered by the World Bank, provides cross-national estimates on intergenerational mobility in income and education that can be downloaded free of charge from the World Bank website. (1) The Global Database on Intergenerational Income Mobility provides information on the extent to which a child’s income depends on his or her parents’ income. Estimates on intergenerational income elasticity are based on nationally representative surveys of individuals born in the 1980s and 1990s. Estimates are currently available for father-son pairings only. The dataset includes 87 countries, representing 84% of the world population. (2) The Global Database on Intergenerational Education Mobility provides information on the extent to which an individual’s educational attainment is independent of the education of his or her parents. Estimates on intergenerational education elasticity are based on surveys of individuals born between 1940 and 1989. Estimates are available for different choices of parental (mothers/fathers/average/max) and child (sons/daughters/all, individuals of the surveys) educational attainment and are provided for different (10-year) cohorts separately. The dataset includes 153 countries, representing 97% of the world population.

Intergenerational Educational Inequality in Sub-Saharan Africa Dataset

The Intergenerational Educational Inequality in Sub-Saharan Africa Dataset is an academically led, cross-national dataset assembled by Ilze Plavgo (Lille Catholic University). It provides intergenerational educational inequality coefficients and other contextual, open-source macro-indicators. Intergenerational inequality estimates are regression coefficients, calculated at the individual level for each country-year. They measure the strength of association between parental socio-economic status and children’s educational outcomes controlling for age and gender. Regressions are based on nationally representative cross-sectional demographic and health surveys, and multiple cluster surveys, which were collected between 1990 and 2017. The analytical sample comprises children age 14 to 16, matched with their parents’ or caretakers’ information. The dataset includes 40 sub-Saharan African countries and covers (selected) birth cohorts between 1975 and 2002. The data is available free of charge and can be downloaded from the EUI SPS Data Portal.

UNDP Inequality-adjusted Human Development Index (IHDI)

The IHDI is a summary measure, created and administered by the United Nations Development Program (UNDP), that accounts for the level of inequality in human development. It builds on the Human Development Index (HDI) which uses a life expectancy index, an education index and a gross national income per capita index to empirically assess three key dimensions of human development: a long and healthy life, knowledge and a decent standard of living. The inequality-adjusted HDI is based on a distribution-sensitive class of composite indices proposed by James Foster, Luis López-Calva and Miguel Székely and draws on Anthony Atkinson’s family of inequality measures. It is computed as a geometric mean of inequality-adjusted dimensional indices and accounts for inequalities in HDI by ‘discounting’ each dimension’s average value according to its level of inequality. IHDI values equal HDI values in absence of inequality, but they fall below them as inequality rises. The IHDI series is available for 195 countries from 2010 onwards. The data is available free of charge and can be downloaded from UNDP’s Data Portal.

Comparative Welfare Entitlements Project (CWEP)

The CWEP is an academically led, cross-national dataset that systematically documents the structure and generosity of social insurance benefits. The project is directed by Lyle A. Scruggs (University of Connecticut) and coordinated by Gabriela Ramalho Tafoya (Manchester University). CWEP is designed to complement programme spending data by offering quantitative indicators on income replacement rates of cash benefits, eligibility criteria, and programme coverage for unemployment and sickness insurance benefits, as well as for standard and minimum pensions. Replacement rates are available for ten household types. The dataset includes 33 countries and spans the period from the early 1970s onwards. CWEP represents a substantial update and extension of two Comparative Welfare Entitlements Datasets (CWED and CWED2). CWED data is available free of charge for non-commercial use and can be downloaded after registration from the CWEP Data Portal.

Comparative Welfare States Data Set (CWS)

The CWS dataset is an academically led, cross-national dataset compiled by David Brady (University of Southern California), Evelyne Huber, and John D. Stephens (both at the University of North Carolina at Chapel Hill). The dataset provides a broad set of quantitative indicators drawn from academic and non-academic sources on earnings and income distributions and welfare state institutions, including measures of expenditure, coverage, and generosity across policy areas such as old-age benefits, incapacity and survivor benefits, healthcare, and unemployment protection. These indicators are complemented by information on education, labour force characteristics and labour market institutions, as well as demographic, macroeconomic, and political variables. The data covers 22 OECD countries over the period 1960 to 2018. The CWS 2020 dataset represents a substantial update and extension of the earlier CWS 2004 dataset. The CWS data is available free of charge and can be downloaded from the author’s joint Data Portal.

Pension Maps: Visualising the Institutional Structure of Old Age Security

Pension Maps is an academically led research project that provides a systematic, cross-national overview of the institutional structure of national old age security systems in Europe and beyond. The project is directed by Simone Schneider and Ulrich Becker (Max Planck Institute for Social Law and Social Policy=. Pension Maps complements quantitative social policy datasets by offering standardised visualisations of old age security systems, classifying schemes according to their legal form and function, rights of access and legal form of affiliation, modes and sources of financing, and the use of means testing. Visual representations are complemented by detailed legal documentation on each pension scheme, including information on coverage, financing arrangements, administrative responsibility, qualifying conditions, and benefit calculation rules. Pension Maps covers 29 countries and reflects the status quo as of January 2020. All visualisations and accompanying legal information are available free of charge via the Pension Maps Data Portal and as downloadable Report from the Institute’s website. 

The Mutual Information System on Social Protection (MISSOC)

MISSOC is an EU-coordinated information system that provides systematically organised and regularly updated information on national social protection systems in Europe. The system is coordinated by the European Commission in close cooperation with national correspondents. Through harmonised comparative tables, MISSOC offers detailed and comparable legal information on social protection across 12 policy areas, including financing, sickness, maternity and paternity, invalidity, old-age, survivors, employment injuries and occupational diseases, family benefits, unemployment, guaranteed minimum resources, and long-term care. In addition, MISSOC provides organisational charts and concise descriptions of the overall social protection structure in each country, and includes dedicated modules documenting the main social protection arrangements for the self-employed. The database covers 31 countries – the 27 EU Member States plus Iceland, Liechtenstein, Norway, and Switzerland – and is updated twice yearly (January and July). Historical information is available for many countries dating back to 1998 accessible via an online archive. Comparative tables and related documentation are available free of charge and can be downloaded from the MISSOC’s Data Portal.

ISSA Social Security around the World

The Social Security Around the World country profile series administered by the International Social Security Association (ISSA) features qualitative information on various social security programmes worldwide, including old-age, disability and survivors, health and long-term care, sickness and maternity, work injury, unemployment, and family allowances. Country profiles offer detailed information on the regulatory framework, coverage, funding sources, qualifying conditions, benefit amounts, and the administrative organisation of available programmes. Comparative scheme tables provide a systematic comparison of the existence of programme branches, types of old-age pensions, pensionable ages and contribution rates across countries. Publications cover more than 190 countries and are published with a two-year regional update cycle for Europe, Asia-Pacific, Africa and the Americas. ISSA country profiles can be downloaded free of charge from the ISSA Data Portal. The ISSA country profile series is a continuation of the Social Security Programs Throughout the World (SSPTW) series administered by the U.S. Social Security Administration (SSA) until 2019. SSPTW country profiles and regional reports can be downloaded free of charge from the SSA archives.

Social Policy Indicators Database (SPIN)

SPIN is an academically led, cross-national database for the comparative and longitudinal study of social policies and the organisation of welfare states, established and administered by the Swedish Institute for Social Research (SOFI) at Stockholm University. To date, SPIN provides eight different datasets covering up to 39 countries from 1930 to 2019. (1) The Child Benefit Dataset (CBD) covers various child benefit programmes and is available for 36 countries between 1960 and 2020. (2) The Child Care Dataset (CCD) is still under construction, and focuses on the coverage, financing, and level of childcare provision for EU member states as well as Australia, Canada, New Zealand, Norway, Switzerland and the United States. (3) The Housing Benefits Dataset (HBEN) provides data on social policies in general, and means-tested housing benefits in particular, covering 39 countries from 2001 to 2020. (4) The Out-of-Work Benefits Dataset (OUTWB) provides data on various types of out of-work benefits (including unemployment insurance and assistance, social assistance, child benefits, fiscal benefits and housing allowances) for 39 countries between 2001 and 2021. (5) The Parental Leave Benefit Dataset (PLB) offers indicators on parental leave benefits and related family programmes for 36 countries between 1950 and 2020 (in 5-year intervals). (6) The Social Assistance and Minimum Income Protection Interim Dataset (SAMIP) includes detailed information on the benefit position of low-income households in industrialised welfare democracies and covers 34 countries between 1990 and 2019. (7) The Social Citizenship Indicator Program (SCIP) informs about the institutional structures of core social insurance programmes in 18 countries during the post-war period with data ranging from 1930s to 2005. (8) The Social Insurance Entitlements Dataset (SIED) is a continuation of SCIP with an extended geographical and temporal scope covering 37 countries from 2000 to 2023.  (9) The Student Support and Fees Dataset (SSFD) focusses on the social rights and obligations of full-time undergraduate students for three family models. It covers 33 high-income countries for the years 2005, 2010, 2015, 2020, and 2022. All SPIN datasets are available free of charge and can be downloaded from the SPIN Data Portal.

The Comparative Unemployment Benefit Conditions & Sanctions Dataset

The Comparative Unemployment Benefit Conditions & Sanctions Dataset is an academically led, cross-national dataset on unemployment protection compiled by Carlo Knotz (University of Stavanger) and Moira Nelson (Lund University). The dataset provides quantitative indicators on the strictness of job search and reporting requirements, definitions of ‘suitable work’, and unemployment benefit sanction rules. The dataset covers 21 countries in Europe, North America and Australasia and spans three decades from 1980 to 2012. The dataset is available free of charge and can be downloaded from the main author’s website and Data Portal.

Leiden University Datasets on Social Assistance, Minimum Income Levels and Unemployment Replacement Rates

The Department of Economics at Leiden University offers a collection of academically led, cross-national datasets, including data on social assistance, minimum income levels, and unemployment replacement rates. The datasets update, extend, and modify the Social Assistance and Minimum Income Protection Interim Dataset (SAMIP) and the Comparative Welfare State Entitlements Dataset (CWED). Data can be downloaded free of charge from the department’s website. (1) The Social Assistance and Minimum Income Levels and Replacement Rates Dataset (2016), assembled by Jinxian Wang and Olaf van Vliet, focuses on minimum income benefit schemes. It provides real net minimum income benefit levels for different household-types for 33 countries between 1990 and 2009. (2) The Unemployment Replacement Rates Dataset 2012, assembled by Olaf Van Vliet and Koen Caminada, focuses on unemployment benefit schemes. It provides net and gross unemployment replacement rates for different worker categories and for two household-types, covering 34 countries between 1971 and 2009.

UNU-WIDER Social Assistance, Politics and Institutions Database (SAPI)

The SAPI, established and administered by the United Nations University World Institute for Development Economics Research (UNU-WIDER), provides harmonised cross-national information on social assistance programmes in developing countries. The database offers information on several programme characteristics (incl. programme objectives, targeted populations, beneficiary selection criteria, quality and conditionality of transfers) and provides measures on the degree of programme institutionalisation (i.e. centralisation in programme administration and formalisation of beneficiary registration and evaluation procedures), nominal budgets and financing structures. It is an expansion of the Social Assistance in Developing Countries Database (SADC, version 5.0), which was created by Armando Barrientos (University of Manchester) and Miguel Niño-Zarazúa (UNU-WIDER Research Fellow). SAPI covers more than 70 countries between 2000 and 2015. The dataset is available free of charge and can be downloaded from the UNU WIDER Data Portal and Data Archive.

FLOOR Project on Social Cash Transfers in the Global South (FLOORCASH)

FLOORCASH is a collection of four academically led, cross-national datasets on social cash transfers in the Global South which were created within the interdisciplinary Research Project Financial assistance, Land policy, glObal sOcial Rights (FLOOR) directed by Lutz Leisering (Bielefeld University). (1) The FLOORCASH-Basic Dataset, assembled by Katrin Weible, Tobias Böger, and John Berten, provides qualitative and quantitative information on social cash transfers, focusing on conditions of eligibility, benefits, implementation, institutional core features, evolution, and goals. The dataset is based on academic and governmental sources as well as on expert interviews and covers 148 developing and emerging economies of the Global South as of 2012/2013. (2) The FLOORCASH-SocCIT Dataset, assembled by Katrin Weible and Lutz Leisering, provides a computable form of the all data gathered for countries within FLOORCASH-Basic. It focuses on entitlements to social cash transfers rather than welfare outcomes and emphasises three aspects: inclusion of social groups (with more refined data than the usual target groups), conditions of access to benefits, and institutionalisation of the programmes. (3) The FLOORCASH-SocPen Dataset, assembled by Tobias Böger, provides time series data on the introduction and reform of non-contributory pension programmes and encompasses cross-sectional information on benefit levels, means-testing and qualifying ages as well as information on beneficiary numbers and expenditure. It covers 70 independent economies across the global South from 2001 to 2011. (4) The FLOORCASH-Discourse Dataset, assembled by Moritz von Gliszczynski, provides an analysis of over 250 publications of international organisations, representing global discourses on social policy, especially social cash transfers. FLOORCASH datasets are available free of charge and can be downloaded from the FLOORCASH Data Portal.

University of Cambridge – Centre for Business Research Labour Regulation Index Dataset (CBR-LRI)