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The Evolution of Poverty in the European Union: Concepts, Measurement and Data

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  • Koen Decancq
  • Tim Goedemé
  • Karel Van den Bosch
  • Josefine Vanhille

Abstract

This paper considers the measurement of poverty in the European Union (EU). Starting from a definition of poverty that is suitable for the European context, a flexible measurement framework is proposed based on the Foster-Greer-Thorbecke class of poverty measures. Three key issues need to be addressed in the measurement of poverty. First, one has to determine the appropriate metric of individual well-being. Second, a cut-off value or threshold needs to be established under which persons are considered to be poor. Third, it is necessary to outline an aggregation procedure to attain a poverty figure for society as a whole. In what follows, we discuss the different answers that are implicit in the poverty measures applied in this book* and the EU’s social strategy. The EU Statistics on Income and Living Conditions (EU-SILC) are introduced as the main data source for poverty analysis in the EU. Finally, an illustration is provided of how the different conceptual choices in the measurement of poverty affect the empirical findings regarding the evolution of poverty between 2005 and 2009. It turns out that the selection of individual well-being metric and the choice between a county-specific and a pan-European poverty line strongly affect observed patterns of poverty in the EU. * Cantillon, B. and Vandenbroucke, F. (eds.), For Better For Worse, For Richer For Poorer. Labour market participation, social redistribution and income poverty in the EU. Oxford: Oxford University Press (forthcoming).

Suggested Citation

  • Koen Decancq & Tim Goedemé & Karel Van den Bosch & Josefine Vanhille, 2013. "The Evolution of Poverty in the European Union: Concepts, Measurement and Data," ImPRovE Working Papers 13/01, Herman Deleeck Centre for Social Policy, University of Antwerp.
  • Handle: RePEc:hdl:improv:1301
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    References listed on IDEAS

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    1. Aaberge, Rolf & Bhuller, Manudeep & Langørgen, Audun & Mogstad, Magne, 2010. "The distributional impact of public services when needs differ," Journal of Public Economics, Elsevier, pages 549-562.
    2. Rolf Aaberge & Audun Langørgen & Magne Mogstad & Marit Østensen, 2008. "The Impact of Local Public Services and Geographical Cost of Living Differences on Poverty Estimates," Discussion Papers 551, Statistics Norway, Research Department.
    3. Gerlinde Verbist & Michael F. Förster & Maria Vaalavuo, 2012. "The Impact of Publicly Provided Services on the Distribution of Resources: Review of New Results and Methods," OECD Social, Employment and Migration Working Papers 130, OECD Publishing.
    4. Atkinson,Anthony Barnes & Micklewright,John, 1992. "Economic Transformation in Eastern Europe and the Distribution of Income," Cambridge Books, Cambridge University Press, number 9780521438827, November.
    5. Atkinson, Tony & Cantillon, Bea & Marlier, Eric & Nolan, Brian, 2002. "Social Indicators: The EU and Social Inclusion," OUP Catalogue, Oxford University Press, number 9780199253494.
    6. Andrea Brandolini, 2006. "Measurement of Income Distribution in Supranational Entities: The Case of the European Union," LIS Working papers 452, LIS Cross-National Data Center in Luxembourg.
    7. Natascha Van Mechelen & Sarah Marchal & Tim Goedemé & Ive Marx & Bea Cantillon, 2011. "The CSB-Minimum Income Protection Indicators dataset (CSB-MIPI)," Working Papers 1105, Herman Deleeck Centre for Social Policy, University of Antwerp.
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    Citations

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    Cited by:

    1. David Madden, 2015. "The Poverty Effects Of A ‘Fat‐Tax’ In Ireland," Health Economics, John Wiley & Sons, Ltd., vol. 24(1), pages 104-121, January.
    2. Anna B. Kis & András Gábos, 2015. "Consistent poverty across the EU," ImPRovE Working Papers 15/22, Herman Deleeck Centre for Social Policy, University of Antwerp.
    3. Bea Cantillon, 2012. "GINI DP 52: Virtuous Cycles or Vicious Circles? The Need for an EU Agenda on Protection, Social Distribution and Investment," GINI Discussion Papers 52, AIAS, Amsterdam Institute for Advanced Labour Studies.
    4. Branko Milanovic & Sean Higgins & Nora Lustig & Whitney Ruble & Timothy M. Smeeding, 2016. "Comparing the Incidence of Taxes and Social Spending in Brazil and the United States," Review of Income and Wealth, International Association for Research in Income and Wealth, pages 22-46.
    5. Brunori, Paolo & Ferreira, Francisco & Lugo, Maria Ana & Peragine, Vito, 2013. "Opportunity-sensitive poverty measurement," Policy Research Working Paper Series 6728, The World Bank.
    6. Janský & Kalíšková & Münich, 2016. "Does the Czech Tax and Benefit System Contribute to One of Europe’s Lowest Levels of Relative Income Poverty and Inequality?," Eastern European Economics, Taylor & Francis Journals, vol. 54(3), pages 191-207, May.
    7. Wim Van Lancker & Natascha Van Mechelen, 2014. "Universalism under siege? Exploring the association between targeting, child benefits and child poverty across 26 countries," Working Papers 1401, Herman Deleeck Centre for Social Policy, University of Antwerp.
    8. Geranda Notten, 2013. "Measuring performance: does the assessment depend on the poverty proxy?," ImPRovE Working Papers 13/13, Herman Deleeck Centre for Social Policy, University of Antwerp.
    9. Tim Goedemé & Karel Van den Bosch & Lina Salanauskaite & Gerlinde Verbist, 2013. "Testing the Statistical Significance of Microsimulation Results: A Plea," International Journal of Microsimulation, International Microsimulation Association, vol. 6(3), pages 50-77.
    10. repec:mes:eaeuec:v:54:y:2016:i:3:p:191-207 is not listed on IDEAS
    11. Geranda Notten, 2016. "How Poverty Indicators Confound Poverty Reduction Evaluations: The Targeting Performance of Income Transfers in Europe," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, pages 1039-1056.
    12. Goedemé, Tim & Van den Bosch, Karel & Salanauskaite, Lina & Verbist, Gerlinde, 2013. "Testing the statistical significance of microsimulation results: often easier than you think. A technical note," EUROMOD Working Papers EM18/13, EUROMOD at the Institute for Social and Economic Research.
    13. Goedemé, Tim & Van den Bosch, Karel & Salanauskaite, Lina & Verbist, Gerlinde, 2013. "Testing the statistical significance of microsimulation results: often easier than you think. A technical note," EUROMOD Working Papers EM18/13, EUROMOD at the Institute for Social and Economic Research.

    More about this item

    Keywords

    Europe; Poverty; FGT; EU-wide poverty; Concept; measurement; EU-SILC; top-bottom coding;

    JEL classification:

    • D31 - Microeconomics - - Distribution - - - Personal Income and Wealth Distribution
    • D63 - Microeconomics - - Welfare Economics - - - Equity, Justice, Inequality, and Other Normative Criteria and Measurement
    • O52 - Economic Development, Innovation, Technological Change, and Growth - - Economywide Country Studies - - - Europe
    • I32 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Measurement and Analysis of Poverty

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