Avoid Filling Swiss Cheese with Whipped Cream : Imputation Techniques and Evaluation Procedures for Cross-Country Time Series

Author/Editor: Michael Weber ; Michaela Denk
Publication Date: June 01, 2011
Electronic Access: Free Full text (PDF file size is 918KB).
Use the free Adobe Acrobat Reader to view this PDF file

Disclaimer: This Working Paper should not be reported as representing the views of the IMF. The views expressed in this Working Paper are those of the author(s) and do not necessarily represent those of the IMF or IMF policy. Working Papers describe research in progress by the author(s) and are published to elicit comments and to further debate
Summary: International organizations collect data from national authorities to create multivariate cross-sectional time series for their analyses. As data from countries with not yet well-established statistical systems may be incomplete, the bridging of data gaps is a crucial challenge. This paper investigates data structures and missing data patterns in the cross-sectional time series framework, reviews missing value imputation techniques used for micro data in official statistics, and discusses their applicability to cross-sectional time series. It presents statistical methods and quality indicators that enable the (comparative) evaluation of imputation processes and completed datasets.
Series: Working Paper No. 11/151

Author's Keyword(s): Missing or incomplete data | imputation quality | statistical matching
Publication Date: June 01, 2011
ISBN/ISSN: 9781455270507/1018-5941 Format: Paper
Stock No: WPIEA2011151 Pages: 27
US$18.00 (Academic Rate:
US$18.00 )
Please address any questions about this title to publications@imf.org