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Notes on updating the EU-SILC UDB sample design variables 2012-2014

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  • Lorena Zardo Trindade
  • Tim Goedemé

Abstract

Indicators based on EU-SILC should be accompanied by appropriate standard errors, and in order to do so, it is necessary to consider the sample design. Because important sample design variables are missing in the EU-SILC User Database (UDB), the aim of this note is to explain the update of EU-SILC UDB sample design variables for 2012 (version 4), 2013 (version 3) and 2014 (version 1), based on the methodology developed by Goedemé (2010b, 2013a). Although several of the challenges for reconstructing the EU-SILC sample design variables are identical for all releases of the data, the update required minor adjustments in the computation of the new sample design variables psu1 and strata1. The effect of the use of the new sample design variables on standard errors is observed for ‘At risk of povertyÂ’ and ‘Material deprivationÂ’, for which SE values are found to be larger when the sample design variables are considered.

Suggested Citation

  • Lorena Zardo Trindade & Tim Goedemé, 2016. "Notes on updating the EU-SILC UDB sample design variables 2012-2014," Working Papers 1602, Herman Deleeck Centre for Social Policy, University of Antwerp.
    • Handle: RePEc:hdl:wpaper:1602
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    References listed on IDEAS

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    1. Joan R. Rodgers & John L. Rodgers, 1993. "Chronic Poverty in the United States," Journal of Human Resources, University of Wisconsin Press, vol. 28(1), pages 25-54.
    2. Dean Jolliffe & Gaurav Datt & Manohar Sharma, 2004. "Robust Poverty and Inequality Measurement in Egypt: Correcting for Spatial‐price Variation and Sample Design Effects," Review of Development Economics, Wiley Blackwell, vol. 8(4), pages 557-572, November.
    3. Stephen Howes & Jean Olson Lanjouw, 1998. "Does Sample Design Matter For Poverty Rate Comparisons?," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 44(1), pages 99-109, March.
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    2. Iryna Kyzyma, 2020. "How Poor Are the Poor? Looking beyond the Binary Measure of Income Poverty," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 18(4), pages 525-549, December.
    3. Bernhard Hammer & Sonja Spitzer & Alexia Prskawetz, 2022. "Age-Specific Income Trends in Europe: The Role of Employment, Wages, and Social Transfers," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 162(2), pages 525-547, July.
    4. Nerijus Cerniauskas & Andrius Ciginas, 2019. "Measurement and decomposition of Lithuania’s income inequality," Bank of Lithuania Discussion Paper Series 14, Bank of Lithuania.

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    More about this item

    Keywords

    EU-SILC; sample design; sampling variance; Standard error;
    All these keywords.

    JEL classification:

    • D31 - Microeconomics - - Distribution - - - Personal Income and Wealth Distribution
    • O52 - Economic Development, Innovation, Technological Change, and Growth - - Economywide Country Studies - - - Europe

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