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A note on how to realize the full potential of the EU-SILC data

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  • Berger, Melissa
  • Schaffner, Sandra

Abstract

The European Union Statistics on Income and Living Conditions (EU-SILC) is a rotational panel provided by Eurostat that covers variables with a high potential for comparative European labour market and social research. Unfortunately, its current availability limits its potential research applications. This research note describes these shortcomings of the current data provision. Furthermore, we make two contributions for a better exploitation of these data sets: First, we develop a method for combining the different waves in order to increase the number of usable observations; and second, we indicate how monthly data on income and hourly pay can be derived.

Suggested Citation

  • Berger, Melissa & Schaffner, Sandra, 2015. "A note on how to realize the full potential of the EU-SILC data," ZEW Discussion Papers 15-005, ZEW - Leibniz Centre for European Economic Research.
  • Handle: RePEc:zbw:zewdip:15005
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    References listed on IDEAS

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    1. Mathiowetz, Nancy A & Duncan, Greg J, 1988. "Out of Work, Out of Mind: Response Errors in Retrospective Reports of Unemployment," Journal of Business & Economic Statistics, American Statistical Association, vol. 6(2), pages 221-229, April.
    2. Nicholas T. Longford & Maria Grazia Pittau & Roberto Zelli & Riccardo Massari, 2012. "Poverty and inequality in European regions," Journal of Applied Statistics, Taylor & Francis Journals, vol. 39(7), pages 1557-1576, January.
    3. Ronald Bachmann & Peggy Bechara & Sandra Schaffner, 2016. "Wage Inequality and Wage Mobility in Europe," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 62(1), pages 181-197, March.
    4. Marilena Giannetti & Daniela Federici & Michele Raitano, 2009. "Migrant remittances and inequality in Central-Eastern Europe," International Review of Applied Economics, Taylor & Francis Journals, vol. 23(3), pages 289-307.
    5. Aristei, David & Perugini, Cristiano, 2015. "The drivers of income mobility in Europe," Economic Systems, Elsevier, vol. 39(2), pages 197-224.
    6. Stefan Angel & Benjamin Bittschi, 2019. "Housing and Health," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 65(3), pages 495-513, September.
    7. repec:zbw:rwirep:0386 is not listed on IDEAS
    8. Bachmann, Ronald & Schaffner, Sandra, 2009. "Biases in the measurement of labour market dynamics," Technical Reports 2009,12, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    9. Iacovou, Maria & Kaminska, Olena & Levy, Horacio, 2012. "Using EU-SILC data for cross-national analysis: strengths, problems and recommendations," ISER Working Paper Series 2012-03, Institute for Social and Economic Research.
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    Cited by:

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    2. Ángel Luis Gómez, 2020. "The effects of changes in the composition of employment on euro area wage growth: panel data analysis," Occasional Papers 2028, Banco de España.
    3. 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.
    4. Lara Maestripieri, 2018. "A Job of One’s Own. Does Women’s Labor Market Participation Influence the Economic Insecurity of Households?," Societies, MDPI, Open Access Journal, vol. 8(1), pages 1-32, January.
    5. Chiara Mussida & Luca Zanin, 2020. "I found a better job opportunity! Voluntary job mobility of employees and temporary contracts before and after the great recession in France, Italy and Spain," Empirical Economics, Springer, vol. 59(1), pages 47-98, July.
    6. Ángel Luis Gómez, 2020. "Efectos de los cambios en la composición del empleo sobre la evolución de los salarios en la zona del euro: un análisis con datos de panel," Occasional Papers 2028, Banco de España.

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    More about this item

    Keywords

    EU-SILC; sampling weights; income; Europe; data quality; panel data;
    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
    • C83 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Survey Methods; Sampling Methods
    • D31 - Microeconomics - - Distribution - - - Personal Income and Wealth Distribution

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