Income missing values imputation: EVS 1999 and 2008

Francesco Sarracino

No 2011-05, LISER Working Paper Series from Luxembourg Institute of Socio-Economic Research (LISER)

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.

Keywords: multiple imputation; missing data; income; EVS; cross-section (search for similar items in EconPapers)
JEL-codes: C01 C11 C31 (search for similar items in EconPapers)
Pages: 28 pages
Date: 2011-01
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Citations: View citations in EconPapers (1)

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