Imputation of Missing Data in Waves 1 and 2 of SHARE

51 Pages Posted: 19 Mar 2011 Last revised: 18 Jun 2011

See all articles by Dimitris Christelis

Dimitris Christelis

Adam Smith Business School, University of Glasgow; Centre for Studies in Economics and Finance (CSEF), University of Naples Federico II; Center for Financial Studies (CFS); Netspar

Date Written: March 8, 2011

Abstract

The Survey of Health, Aging and Retirement in Europe (SHARE), like all large household surveys, suffers from the problem of item non-response, and hence the need of imputation of missing values arises. In this paper I describe the imputation methodology used in the first two waves of SHARE, which is the fully conditional specification approach of van Buuren, Brand, Groothuis-Oudshoorn, and Rubin (2006). Methods for assessing the convergence of the imputation process are also discussed. Finally, I give details on numerous issues affecting the implementation of the imputation process that are particular to SHARE.

Keywords: Missing Data, Multiple Imputation, Markov Chain Monte Carlo, SHARE

JEL Classification: C81, C83

Suggested Citation

Christelis, Dimitrios, Imputation of Missing Data in Waves 1 and 2 of SHARE (March 8, 2011). Available at SSRN: https://ssrn.com/abstract=1788248 or http://dx.doi.org/10.2139/ssrn.1788248

Dimitrios Christelis (Contact Author)

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