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

Author

Listed:
  • 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.
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    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.
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    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. Kaminska, Olena & Iacovou, Maria & 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.
    Full references (including those not matched with items on IDEAS)

    Citations

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    Cited by:

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    2. Haapanala, Henri & Marx, Ive & Parolin, Zachary, 2022. "Decent Wage Floors in Europe: Does the Minimum Wage Directive Get It Right?," IZA Discussion Papers 15660, Institute of Labor Economics (IZA).
    3. John Moffat & Duncan Roth, 2016. "The Cohort Size-Wage Relationship in Europe," LABOUR, CEIS, vol. 30(4), pages 415-432, December.
    4. Bachmann, Ronald & Gonschor, Myrielle & Milasi, Santo & Mitra, Alessio, 2023. "Technological progress and the dynamics of self-employment: Worker-level evidence for Europe," Ruhr Economic Papers 1023, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    5. 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.
    6. 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.
    7. Lara Maestripieri, 2018. "A Job of One’s Own. Does Women’s Labor Market Participation Influence the Economic Insecurity of Households?," Societies, MDPI, vol. 8(1), pages 1-32, January.
    8. 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.
    9. 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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