Complementary Databases: country-level data
LIS makes available complementary databases that provide country-level indicators that might be useful for comparative research. Codebooks and other details about these compilations are included for each. Please contact the producers of these data directly if you have questions.
Note: If you have a dataset or database containing country-level variables that might be of use to LIS researchers, please contact us. We would be happy to lodge your data on our website!
LIS country-year samples isoginis (2024)
prepared by Louis Chauvel >>
This dataset provides estimates, including standard deviations, of isoginis across 864 ccyyyy country-year samples from the LIS dataset (LIS release March 2024). Isoginis represent innovative indicators of inequality across various percentile levels, akin to the conventional Gini index. For further details, refer to the paper:
Louis Chauvel, 2024, “Isogini as a Set of Indicators to Compare Trends and Shapes of Income Inequality: The Fading Swedish Middle-Class Society in a World of Diverse Dynamics”, Inequality Matters, Quarterly updates on inequality research, Issue No.29 (March 2024). https://www.lisdatacenter.org/newsletter/nl-2024-29-im-1/)
In addition to isoginis, the dataset includes indicators such as sigma (indicating the slope of imbalance between upper and lower tail inequality) and pi (measuring polarization). Furthermore, the proportion at risk of poverty (pora) ie below 50% of the median, and its log-symmetric for those at risk of richness (rira) ie above 2 times the median, are also provided.
Isoginis were computed using version 2 of the STATA module ‘isogini’ (accessible via ‘ssc install isogini’), as described by Louis Chauvel in the associated publication.
(see Louis Chauvel, 2024. “ISOGINI: Stata module to estimate isogini measures at different percentiles,” Statistical Software Components S459299, Boston College Department of Economics, revised 16 Mar 2024. https://ideas.repec.org/c/boc/bocode/s459299.html)
The standard deviation of each estimate come from a 50-repetitions bootstrap included in then isogini module.
Users of this database are kindly requested to cite it as follows: “Chauvel, L. (2024). ‘864 LIS Country-Year Samples Isoginis’, available at https://www.lisdatacenter.org/resources/other-databases/.”
Documentation and Codebook
Database (Stata format)
Database (CSV format)
The Atlas of Inequality Aversion (2022)
prepared by Stanislaw Maciej Kot and Piotr R. Paradowski >>
This complementary dataset contains the estimates of inequality aversion parameter ε of the constant relative inequality aversion utility function (Atkinson, 1970). The sole parameter ε of this function expresses a society’s aversion to inequality and is derived from the mathematical condition of the existence of the social welfare function estimated from a parametric distribution of income (GB2(a,b,p,q)). As a result of these analytical advancements, the data also contains the Atkinson Index and the equally distributed equivalent income (Atkinson, 1970) for 56 countries over time. The authors call it the Atlas of Inequality Aversion parameters. It is the first such database that allows researchers not only from the field of welfare economics but also in other social science disciplines to obtain inequality aversions that they can use in various ways to benefit their scientific investigations. Understanding the threshold of a population’s tolerance to inequality can also help steer economic policy decision-making.
The data included here is an extension of the data estimated from the LIS database, presented by Stanislaw Maciej Kot (Gdansk University of Technology) and Piotr R. Paradowski (LIS and Gdansk University of Technology) in the LIS Working Paper #826 and published in Equilibrium. Quarterly Journal of Economics and Economic Policy (June 2022); the open access for the published article is available at http://economic-research.pl/Journals/index.php/eq/article/view/1972/1908
We ask that users of this database to cite it as
Kot, S.M. and P.R. Paradowski (2022). The Atlas of Inequality Aversion, https://www.lisdatacenter.org/resources/other-databases/.
and
Kot, S. M., & Paradowski, P. R. (2022). The atlas of inequality aversion: theory and empirical evidence on 55 countries from the Luxembourg Income Study database. Equilibrium. Quarterly Journal of Economics and Economic Policy, 17(2), 261–316. https://doi.org/10.24136/eq.2022.010
Documentation and Codebook
Database (Stata format)
Database (CSV format)
Leave and ECEC policy dimensions dataset (2021)
assembled by Sarah L. Kostecki >>
The Leave and ECEC policy dimensions dataset includes country-level policy indicators on leave and early childhood education and care (ECEC) for 31 countries: 24 high-income countries and seven middle-income countries (Latin America) based on policy and ECEC utilization information compiled from international organizations and country-specific sources. The 21 country-level leave and ECEC policy dimension indicators in this dataset are categorized into four policy dimension groups. The indicators measure three dimensions of leave policy (generosity, gender equality, and universality) and one dimension of ECEC policy (generosity, measured by enrollment rates of children in ECEC). Four country identifier indicators are also included in the dataset for a total of 25 indicators. The year selections of the country-level policy information used to construct the indicators are from between the years 2009 to 2013.
Please cite the work as: Kostecki, Sarah L. (2021). Leave and ECEC policy dimensions dataset, https://www.lisdatacenter.org/resources/other-databases/.
Documentation
Descriptives
Database
Family Tax Benefit Database (2020)
assembled by Manuel Schechtl >>
The dataset includes country-level indicators on the national income tax system and family-related tax expenditures (such as single parent reliefs or joint filing for couples) based on OECD benefits and wages data country reports and national expert’s responses to an online survey. The country and year selection of the tax indicator information matches the latest available dataset for most countries that provide tax data in the Luxembourg Income Study (LIS). Therefore, the data can be used for cross-national comparisons of public policy, tax policy or social policy.- See below.
Documentation
Database
Leiden LIS Budget Incidence Fiscal Redistribution Dataset on Relative Income Poverty Rates (2019)
assembled by Koen Caminada and Jinxian Wang >>
The Leiden LIS Budget Incidence Fiscal Redistribution Dataset on Relative Income Poverty Rates 2019 presents the disentanglement of relative income poverty rates and the redistributive effect of social transfers and income taxes all LIS-countries and waves (339 datasets) for the period 1967-2016. This dataset allows researchers and public policy analysts to compare fiscal redistribution across developed and middle income countries.
It is related to our 2017-database on Budget Incidence Fiscal Redistribution on Income Inequality (Jinxian Wang & Koen Caminada) – See. below.
Documentation
Database
LIS Working Paper 761
Routine Task Intensity” (RTI) and “Offshorability” (OFFS) for Use with the Luxembourg Income Study (LIS) (2018)
prepared by , Matthew C. Mahutga,Michaela Curran and Anthony Roberts >>
This is a new dataset on occupational routine task intensity (RTI) and offshorability (OFFS) for use with the Luxembourg Income Study (LIS). These data will be of use to LIS users with questions related to income distribution, poverty, labor markets, globalization, skill-biased/routine-biased technological change, and other processes. To produce these data, we recoded 23 country-specific occupational schemes (76 LIS country-years) to the two-digit ISCO-88 scheme, and then cross-walked from ISCO-88 to the RTI and OFFS scores of Goose, Manning and Salomons (2014). In addition to RTI and OFFS, our recodes also allowed us to expand the coverage of ISCO-88 and variables based on it (e.g. occa1 and occb1). When combining our recoded cases with those that already reported in ISCO-88 at the 2 digit level or higher, we produced RTI and OFFS scores for 38 LIS countries and 160 LIS country-years. We also make our code available so that users can recode newer waves as they come online. Details on the recoding procedures and validity of the recodes can be found in Mahutga, Curran and Roberts (2018). Additional details on the data can be found at matthewcm.ucr.edu. We ask that users of these data cite it with Mahutga, Curran and Roberts (2018) as elaborated below.
Goos, Martin, Manning, Alan, and Anna Salomons. 2014. “Explaining Job Polarization: Routine-Biased Technological Change and Offshoring.” American Economic Review 104(8): 2509-2526.
Mahutga, Matthew C., Michaela Curran and Anthony Roberts. 2018. “Job Tasks and the Comparative Structure of Income and Employment: Routine Task Intensity and Offshorability for the LIS.” International Journal of Comparative Sociology 59(2): 81-109.
Codebook
Data
Script to reproduce current data and code future LIS waves
Detailed country-specific occupation scheme recode notes
Leiden LIS Budget Incidence Fiscal Redistribution Dataset on Income Inequality (2017)
prepared by Jinxian Wang and Koen Caminada >>
The Leiden LIS Budget Incidence Fiscal Redistribution Dataset on Income Inequality 2017 presents the disentanglement of income inequality and the redistributive effect of social transfers and taxes in 47 LIS countries for the period 1967-2014 (Waves I – Wave IX of LIS). This dataset allows researchers and public policy analysts to compare fiscal redistribution across developed and middle income countries
Documentation
Database
LIS Working Paper 724
A. LIS / New York Times Income Distribution Database (2016)
assembled by Janet Gornick (LIS), Thierry Kruten (LIS), Branko Milanovic (LIS), David Leonhardt (NYT), and Kevin Quealy (NYT) >>
It includes detailed information on the distribution and growth of household income across countries. The database contains results from 178 LIS datasets from 23 countries, covering the period 1979 to 2013.
The database is based primarily on the microdata brought together by LIS, and includes observations for 180 country-years. In addition to providing levels of incomes across the distribution, it includes a set of summary inequality measures as well as Gini Indices.
Database
B. Incomes across the Distribution Database (2016)
assembled by Stefan Thewissen, Brian Nolan and Max Roser >>
It includes detailed information on income distribution for 27 developed countries between 1978 and 2013.
The database is based primarily on the microdata brought together by LIS, and includes observations for 180 country-years. In addition to providing levels of incomes across the distribution, it includes a set of summary inequality measures as well as Gini Indices.
Database
Report
Note: Databases A and B are complementary. LIS/NYT Income Distribution Database presents results based on household disposable income for entire populations. Incomes across the Distribution Database also presents results based on household market income, and for working-age populations.
Comparative Political Data Set (2016)
assembled by Klaus Armingeon, Christian Isler, Laura Knöpfel, David Weisstanner and Sarah Engler (University of Bern) >>
This is a collection of political and institutional country-level data. It consists of annual data for 36 democratic countries for the period of 1960 to 2014 or since their transition to democracy
Database
Comparative Welfare States Data Set (2014-2020)
compiled by David Brady, Evelyne Huber, and John D. Stephens >>
It provides an array of country-level welfare state, economic, institutional, political, policy, and demographic indicators. The CWS includes information on 22 rich democracies from 1960-2018.
2014 version
Codebook
Database
Stata
2020 version
Codebook
Database
Stata
Social Policy and Politics in Latin America and the Caribbean Datasets
compiled by Evelyne Huber and John D. Stephens >>
This database provides country-level social policy indicators over time, including social welfare, economic, and demographic indicators, and strength and codings of political parties. The Latin American Welfare Dataset covers the period 1960-2014. The Latin America and Caribbean Political Dataset covers the period 1945-2012.
OECD Income Distribution Database (2013) >>
It includes a set of poverty and inequality measures, as well as average and median disposable income and other related indicators.
Database
Comparative Welfare Entitlements Dataset (2013)
assembled by Lyle Scruggs, Detlef Jahn, and Kati Kuitto >>
It provides systematic data on institutional features of social insurance programs in 33 countries spanning much of the post-war period. Data are provided for unemployment insurance, sickness insurance, and standard and minimum pensions; indicators include replacement rates, eligibility criteria, and coverage.
Database
The Work-Family Policy Indicators (2012)
assembled by Irene Boeckmann, Michelle Budig, and Joya Misra >>
Those indicators include country-level data on birth-related and extended leave policies, early childhood education and care, and the regulation of working time. The dataset includes 12 country-level indicators, covering 22 countries, including countries in Europe and North America, as well as Australia. The indicators are intended to be used together with microdata from the Luxembourg Income Study Database (LIS). With a few exceptions, the policy measures are matched to the years corresponding to LIS’ Wave 5 microdata. The construction of this database was funded by the United States’ National Science Foundation.
Documentation and Institutional Details
Indicators
Social Assistance and Minimum Income Protection Interim Data Set (SaMip) (2009)
assembled by Kenneth Nelson >>
It includes detailed information on the benefit position of low-income households in industrialized democracies. SaMip is an ongoing research project based at the Swedish Institute for Social Research at Stockholm University.
Details
Data
Variables and Codes
Documentation
Fiscal Redistribution Data Set (2005, 2008, 2010, 2013)
prepared by David Jesuit and Vincent Mahler >>
Institutions that Build Economic Security and Asset Holdings Database (2008)
compiled by Janet Gornick, Timothy Smeeding, Eva Sierminska, and Maurice Leach >>
includes variables on countries’ institutions related to income security and wealth. This database is designed to be useful to researchers using the LWS microdata.
Details
Database
References
A Detailed Look at Parental Leave Policies in 21 OECD Countries (2008)
compiled by Rebecca Ray of the Center for Economic and Policy Research in the United States >>
It provides country-level data on the leave eligibility, duration, benefit levels, part-time options, and job protections. An associated report by Rebecca Ray, Janet Gornick and John Schmitt synthesizes findings based on the policy data.
Details
Report
Measures that Govern Rights to Alternate Work Arrangements in 21 OECD Countries (2007)
assembled by Ariane Hegewisch and Janet Gornick >>
It provides country-level information on working time regulations pertaining to alternative work arrangements. An associated report by Ariane Hegewisch and Janet Gornick synthesizes findings based on the policy data.
Details
Report
Employment Key Figures by Gender(2007)
assembled by The LIS Team >>
It includes a large set of national-level indicators presented in ten tables that highlight women’s economic outcomes and gender inequality in poverty and employment.
These figures – generated with the support of the World Bank – are based on the the LIS pre-revised datasets.
Tables
| 1 |
Population composition of all individuals age 20-54 who are not in the military, by demographic characteristics |
| 2 |
Poverty rates of all individuals age 20-54 who are not in the military, by demographic characteristics |
| 3i |
Employment rates based on the ILO definition of employment of all individuals age 20-54 who are not in the military, by demographic characteristics |
| 3m |
Employment rates of all individuals age 20-54 who are not in the military and who are currently primarily employed, by demographic characteristics |
| 3u |
Employment rates of all individuals age 20-54 who are not in the military and who are usually primarily employed, by demographic characteristics |
| 4 |
Population composition of all employed individuals age 20-54 who are not in the military, by employment characteristics |
| 5 |
Hours based on usual hours worked, by demographic characteristics |
| 6 |
Female/male annual earnings ratios, by demographic characteristics |
| 7 |
Characteristics of the not employed, for those mainly not employed, by category |
| 8 |
Characteristics of the youth population, by demographic and employment characteristics |
Employment by Gender Key Figures
Tables Notes
Column Notes
Family Policy Database (1997, 2003)
compiled by Janet Gornick, Marcia Meyers and (for the 1997 version) Katherin Ross >>
