Important empirical information on household behavior is obtained from surveys. However, various interdependent factors that can only be controlled to a limited extent lead to unit and item nonresponse, and missing data on certain items is a frequent source of difficulties in statistical practice. This paper presents the theoretical underpinnings of a Markov Chain Monte Carlo multiple imputation procedure and applies this procedure to a socio-economic survey of German households, the SAVE survey. I discuss convergence properties and results of the iterative multiple imputation method and I compare them briefly with other imputation approaches. Concerning missing data in the SAVE survey, the results suggest that item nonresponse is not occurring randomly but is related to the included covariates. The analysis further indicates that there might be differences in the character of nonresponse across asset types. Concerning the methodology of imputation, the paper underlines that it would be of particular interest to apply different imputation methods to the same dataset and to compare the findings.
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Paper provided by Mannheim Research Institute for the Economics of Aging (MEA), University of Mannheim in its series MEA discussion paper series with number
07121.
Length: Date of creation: 30 May 2007 Date of revision: Handle: RePEc:mea:meawpa:07121
Contact details of provider: Postal: MEA - Mannheimer Forschungsinstitut Ökonomie und Demographischer Wandel, L13, 17, University of Mannheim, 68131 Mannheim Phone: +49/621/181.1862 Fax: +49/621/181.1863 Web page: http://www.mea.uni-mannheim.de/
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