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The Luxembourg Income Study

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  • Martin Ravallion

    (Department of Economics, Georgetown University)

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.

Suggested Citation

  • Martin Ravallion, 2014. "The Luxembourg Income Study," Working Papers 332, ECINEQ, Society for the Study of Economic Inequality.
  • Handle: RePEc:inq:inqwps:ecineq2014-332
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    File URL: http://www.ecineq.org/milano/WP/ECINEQ2014-332.pdf
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    1. Martin Ravallion & Shaohua Chen, 2013. "A Proposal for Truly Global Poverty Measures," Global Policy, London School of Economics and Political Science, vol. 4(3), pages 258-265, September.
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    11. Korinek, Anton & Mistiaen, Johan A. & Ravallion, Martin, 2007. "An econometric method of correcting for unit nonresponse bias in surveys," Journal of Econometrics, Elsevier, vol. 136(1), pages 213-235, January.
    12. Anton Korinek & Johan Mistiaen & Martin Ravallion, 2006. "Survey nonresponse and the distribution of income," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 4(1), pages 33-55, April.
    13. Brigitte Buhmann & Lee Rainwater & Guenther Schmaus & Timothy M. Smeeding, 1988. "Equivalence Scales, Well‐Being, Inequality, And Poverty: Sensitivity Estimates Across Ten Countries Using The Luxembourg Income Study (Lis) Database," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 34(2), pages 115-142, June.
    14. Andrea Brandolini & Anthony B. Atkinson, 2001. "Promise and Pitfalls in the Use of "Secondary" Data-Sets: Income Inequality in OECD Countries As a Case Study," Journal of Economic Literature, American Economic Association, vol. 39(3), pages 771-799, September.
    15. World Bank, 2013. "World Development Indicators 2013," World Bank Publications - Books, The World Bank Group, number 13191, December.
    16. Buhmann, Brigitte, et al, 1988. "Equivalence Scales, Well-Being, Inequality, and Poverty: Sensitivity Estimates across Ten Countries Using the Luxembourg Income Study (LIS) Database," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 34(2), pages 115-142, June.
    17. Jefferson, Philip N. (ed.), 2012. "The Oxford Handbook of the Economics of Poverty," OUP Catalogue, Oxford University Press, number 9780195393781.
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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. Chiara Burlina & Andrés Rodríguez-Pose, 2024. "Inequality, poverty, deprivation and the uneven spread of COVID-19 in Europe," Regional Studies, Taylor & Francis Journals, vol. 58(2), pages 263-284, February.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. Javier Mart n-Rom n & 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.
    8. 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.
    9. 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.
    10. Michael A. Nelson & Rajeev K. Goel, 2023. "Spillovers from gender equality onto economic equality: Evidence from 162 nations," Journal of International Development, John Wiley & Sons, Ltd., vol. 35(6), pages 1365-1388, August.
    11. 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.
    12. 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.
    13. 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.
    14. Ravallion, Martin & Chen, Shaohua, 2019. "Global poverty measurement when relative income matters," Journal of Public Economics, Elsevier, vol. 177(C), pages 1-1.
    15. 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.
    16. Ana Su rez lvarez & Ana Jes s L pez Men ndez, 2018. "Inequality of Opportunity in Developing countries: Does the income aggregate matter?," LIS Working papers 739, LIS Cross-National Data Center in Luxembourg.
    17. 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.
    18. 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.
    19. 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.
    20. 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.
    21. 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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