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
References: Add references at CitEc
Citations: View citations in EconPapers (1)
Downloads: (external link)
https://www.liser.lu/publi_viewer.cfm?tmp=2803 (application/pdf)
Our link check indicates that this URL is bad, the error code is: 404 Not Found
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:irs:cepswp:2011-05
Access Statistics for this paper
More papers in LISER Working Paper Series from Luxembourg Institute of Socio-Economic Research (LISER) 11, Porte des Sciences, L-4366 Esch-sur-Alzette, G.-D. Luxembourg. Contact information at EDIRC.
Bibliographic data for series maintained by Library and Documentation (documentation@liser.lu this e-mail address is bad, please contact repec@repec.org).