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The Luxembourg Income Study

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  • Martin Ravallion

Abstract

The Luxembourg Income Study (now known as LIS) provides public access for research purposes to harmonized unit-record data sets for multiple countries, in addition to providing summary statistics from those data, including poverty and inequality measures. LIS is a well-managed and undeniably important global public institution for research on inequality and social policy in rich countries. However, LIS’s eligibility criteria, country coverage, timeliness and some of its measurement practices limit its usefulness for many other purposes. The paper identifies a number of issues that would need to be addressed by a truly global micro-data base for studying poverty and inequality. Copyright Springer Science+Business Media New York 2015

Suggested Citation

  • Martin Ravallion, 2015. "The Luxembourg Income Study," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 13(4), pages 527-547, December.
  • Handle: RePEc:kap:jecinq:v:13:y:2015:i:4:p:527-547
    DOI: 10.1007/s10888-015-9298-y
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    Cited by:

    1. Francisco G. Ferreira & Nora Lustig & Daniel Teles, 2015. "Appraising cross-national income inequality databases: An introduction," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 13(4), pages 497-526, December.
    2. Nora Lustig, 2018. "Measuring the Distribution of Household Income, Consumption and Wealth: State of Play and Measurement Challenges," Working Papers 1801, Tulane University, Department of Economics.
    3. Marco Ioffredi, 2018. "Income Inequality and Economic Growth: Decomposing the Effects of the Income Distribution," LIS Working papers 751, LIS Cross-National Data Center in Luxembourg.
    4. Brian Nolan, 2020. "The Median Versus Inequality-Adjusted GNI as Core Indicator of ‘Ordinary’ Household Living Standards in Rich Countries," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 150(2), pages 569-585, July.
    5. Stanislaw Maciej Kot & Piotr Paradowski, 2022. "The Atlas of Inequality Aversion: Theory and Empirical Evidence from the Luxembourg Income Study Database," LIS Working papers 826, LIS Cross-National Data Center in Luxembourg.
    6. Javier Martín-Román & Luis Ayala & Juan Vicente, 2017. "Regional inequality in decentralized countries: a multi-country analysis using LIS," LIS Working papers 697, LIS Cross-National Data Center in Luxembourg.
    7. Stefan Thewissen & Lane Kenworthy & Brian Nolan & Max Roser & Tim Smeeding, 2018. "Rising Income Inequality and Living Standards in OECD Countries: How Does the Middle Fare?," Journal of Income Distribution, Ad libros publications inc., vol. 26(2), pages 1-23, July.
    8. Gründler, Klaus & Köllner, Sebastian, 2017. "Determinants of governmental redistribution: Income distribution, development levels, and the role of perceptions," Journal of Comparative Economics, Elsevier, vol. 45(4), pages 930-962.
    9. Michael A. Nelson & Rajeev K. Goel, 2021. "Does Gender Equality Translate into Economic Equality? Evidence from about 150 Nations," CESifo Working Paper Series 8949, CESifo.
    10. Koen Caminada & Kees Goudswaard & Chen Wang & Jinxian Wang, 2019. "Income Inequality and Fiscal Redistribution in 31 Countries After the Crisis," Comparative Economic Studies, Palgrave Macmillan;Association for Comparative Economic Studies, vol. 61(1), pages 119-148, March.
    11. Brian Nolan & Max Roser & Stefan Thewissen, 2016. "GDP Per Capita Versus Median Household Income: What Gives Rise to Divergence Over Time?," LIS Working papers 672, LIS Cross-National Data Center in Luxembourg.
    12. Peter Bofinger & Philipp Scheuermeyer, 2019. "Income Distribution and Aggregate Saving: A Non‐Monotonic Relationship," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 65(4), pages 872-907, December.
    13. Ravallion, Martin & Chen, Shaohua, 2019. "Global poverty measurement when relative income matters," Journal of Public Economics, Elsevier, vol. 177(C), pages 1-1.
    14. Koen Caminada & Kees Goudswaard & Chen Wang & Jinxian Wang, 2021. "Antipoverty Effects of Various Social Transfers and Income Taxes Across Countries," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 154(3), pages 1055-1076, April.
    15. Ana Suárez Álvarez & Ana Jesús López Menéndez, 2018. "Inequality of Opportunity in Developing countries: Does the income aggregate matter?," LIS Working papers 739, LIS Cross-National Data Center in Luxembourg.
    16. Ana Suárez Álvarez & Ana Jesús López Menéndez, 2020. "Trends in Inequality of Opportunity for Developing Countries: Does the Economic Indicator Matter?," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 149(2), pages 503-539, June.
    17. Björklund, Anders & Waldenström, Daniel, 2021. "Facts and Myths in the Popular Debate about Inequality in Sweden," Working Paper Series 1392, Research Institute of Industrial Economics.
    18. Marco Lilla, 2016. "Falling Behind or Catching Up? Cross-Country Evidence in Intra-Generational Wages Mobility through Pseudo-Panels," LIS Working papers 669, LIS Cross-National Data Center in Luxembourg.
    19. Erauskin, Iñaki & Turnovsky, Stephen J., 2019. "International financial integration and income inequality in a stochastically growing economy," Journal of International Economics, Elsevier, vol. 119(C), pages 55-74.
    20. Brian Nolan & Max Roser & Stefan Thewissen, 2016. "Models, Regimes, And The Evolution Of Middle Incomes In OECD Countries," LIS Working papers 660, LIS Cross-National Data Center in Luxembourg.

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    More about this item

    Keywords

    Income; Poverty; Inequality; Household surveys; Data access;
    All these keywords.

    JEL classification:

    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • I32 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Measurement and Analysis of Poverty

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