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Income missing values imputation: EVS 1999 and 2008

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  • SARRACINO Francesco

Abstract

Missing data is a very frequent obstacle in many social science studies. The absence of values on one or more variables can signi?cantly affect statistical analyses by reducing their precision and by introducing selection biases. Being unable to account for these aspects may result in severe misrepresentation of the phenomenon under analysis. For this reason several approaches have been proposed to impute missing values. In present work I will adopt multiple imputation to impute income missing data for Luxembourg in the European Values Study data-set of 1999 and 2008.

Suggested Citation

  • SARRACINO Francesco, 2011. "Income missing values imputation: EVS 1999 and 2008," LISER Working Paper Series 2011-05, Luxembourg Institute of Socio-Economic Research (LISER).
    • Handle: RePEc:irs:cepswp:2011-05
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    References listed on IDEAS

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    1. Joseph Chan & Ho-Pong To & Elaine Chan, 2006. "Reconsidering Social Cohesion: Developing a Definition and Analytical Framework for Empirical Research," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 75(2), pages 273-302, January.
    2. Fernando Rajulton & Zenaida Ravanera & Roderic Beaujot, 2007. "Measuring Social Cohesion: An Experiment using the Canadian National Survey of Giving, Volunteering, and Participating," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 80(3), pages 461-492, February.
    3. Regina Berger-Schmitt, 2002. "Considering Social Cohesion in Quality of Life Assessments: Concept and Measurement," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 58(1), pages 403-428, June.
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    Cited by:

    1. TOURBEAUX Jérôme, 2012. "Intégration et frontières sociales au Luxembourg," LISER Working Paper Series 2012-21, Luxembourg Institute of Socio-Economic Research (LISER).

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    More about this item

    Keywords

    multiple imputation; missing data; income; EVS; cross-section;
    All these keywords.

    JEL classification:

    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models

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